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2 episodes with goldmans
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2 episodes with goldmans
ASX 200 pushed 28 points higher to 8268 (0.3%) as results nearly finished. Banks were flat with ANZ up 0.5% and WBC up 0.4% with the Big Bank Basket at $253.25 (). Health insurers raced away on results and increases from April 1. REITs not doing much, GMG down 0.2% as it released the SPP details. Industrials mainly firmer, WTC still suffering down 2.6% with COL reporting and rallying 3.5%. QAN results and special dividend cheered up 5.6% and retail slightly firmer, LOV up 0.5% and PMV up 0.9%. BAP had a solid reaction day up 5.3% and APE shot the lights out, up 19.9% on better-than-expected numbers. IEL crashed 7.6% on worse than expected results. In resources, iron ore stocks found some friends, BHP up 0.8% and FMG up 1.7%. Gold miners pushed higher again, aided by a lower AUD, NEM back up 1.9% with EVN up 1.5%. Lithium and rare earths slightly firmer, PLS up 0.5% and LYC up 0.6%. Energy stocks saw some bargain hunting, STO up 1.2% and KAR posting better than expected numbers up 4.7%. Uranium stocks showed a glimmer of light, NXG up 4.5%. In corporate news, PME fell 3.7% on a 4m share block trade from the founder. NEU jumped 8.9% on better Daybue numbers. RHC jumped 6.8% after it appointed Goldmans to potentially sell its 52.8% in the European business. Nothing on the economic front. Asian markets drifted lower, Japan up 0.4%, HK off 1.1% and China down 0.4%. 10-year yield at 4.34% Want to invest with Marcus Today? The Managed Strategy Portfolio is designed for investors seeking exposure to our strategy while we do the hard work for you. If you're looking for personal financial advice, our friends at Clime Investment Management can help. Their team of licensed advisers operates across most states, offering tailored financial planning services. Why not sign up for a free trial? Gain access to expert insights, research, and analysis to become a better investor.
Court TV unveils original limited series Trial & Error: Why Did O.J. Win?' Seven-part look at the Simpson murder case 30 years later to debut Feb. 16th Marking 30 years since the opening statements of what came to be dubbed "The Trial of the Century," Court TV announced today the launch of a seven-part original limited series, "Trial & Error: Why Did O.J. Win?". The series takes a deep dive into the infamous double murder trial of O.J. Simpson; a case that was captured by Court TV cameras and helped ignite the nation's ongoing obsession with true crime. Court TV will debut new episodes of "Trial & Error: Why Did O.J. Win?" on Sunday nights at 8 p.m. ET/PT starting Feb. 16th Utilizing Court TV's extensive library, "Trial & Error: Why Did O.J. Win?" will explore what went right for the defense, what went wrong for the prosecution and the perfect storm of legal strategies and surprises that led to one of the most controversial verdicts in history. The series highlights myriad vantage points from numerous trial participants, including attorneys, legal experts, Los Angeles police detectives and friends and relatives on both sides of the courtroom. Interviewees include Simpson defense attorneys F. Lee Bailey and Alan Dershowitz, LAPD Detective Mark Fuhrman, LA County and Simpson case Prosecutor Bill Hodgman, Lon Cryer (juror #6), victim Nicole Brown Simpson's sister Tanya Brown and the father and sister of victim Ron Goldman, Fred Goldman and Kim Goldman. "Trial & Error: Why Did O.J. Win?" is hosted by Michael Ayala, an attorney, Court TV anchor and Emmy-award winning true crime journalist. Court TV's Ted Rowlands serves as executive producer. Both Ayala and Rowlands covered the O.J. trial as reporters."Thirty years have gone by, and the O.J. Simpson trial - which Court TV documented as it unfolded - is still one of the nation's most consequential cultural touchstones," said Ethan Nelson, head of Court TV. "Through first-person interviews with people directly involved with the case, this series takes a provocative look into how the feverishly anticipated and deeply divisive jury verdict came to pass." Check out the trailer: Https://www.youtube.com/watch?v=Wd14RTe433I "Trial & Error: Why Did O.J. Win?" episodes with premiere dates: Feb. 16 - Murders in BrentwoodA football star turned Hollywood actor is charged with the brutal murders of his ex-wife and her friend. The O.J. Simpson case enthralled the globe and became the "Trial of the Century". Thirty years later, the detectives, attorneys and families involved share their stories and why they believe the verdict remains divisive. Feb. 23 - The "Racist" CopLAPD detective Mark Fuhrman tells his side of the story after becoming a household name when the defense accused him of planting a bloody glove and labeled him a racist. O.J. Simpson walked away a free man while Fuhrman's life fell into shambles. March 2 - Domestic ViolenceO.J. Simpson's history of domestic violence was a focal point for the prosecution. The defense claimed it didn't prove he was a murderer. Nicole Brown's sister details the abuse within their relationship. March 9 - Racial TensionThe defense used the racial tension in Los Angeles to their benefit during the O.J. Simpson murder trial. The goal: convince jurors that the LAPD could not be trusted and were capable of planting evidence. March 16 - Attack the Timeline Did O.J. Simpson have enough time to murder Nicole Brown and Ron Goldman? The defense dissected the timeline to raise reasonable doubt. Detective Tom Lange and prosecutor Bill Hodgman explain their window of opportunity. March 23 - The Bloody Gloves It's the most infamous moment of the trial, when the prosecution forced O.J. to put on the bloody glove in court. Did this and "shoddy" police work lose them the case? Defense attorney F. Lee Bailey takes us inside the pivotal courtroom moment and how O.J.'s "Dream Team" attacked the flawed investigation. March 30 - Inside the Jury Room The world watched as the verdict in the "Trial of the Century" came down. The Goldmans share their reaction and Juror #6, Lon Cryer, describes what happened behind closed doors. Was justice served or did O.J. Simpson get away with murder? The double murder trial of Simpson - the college football phenom (Heisman Trophy recipient in 1968) who went on to become an NFL Hall of Famer and popular movie and television personality - riveted the nation during its nearly 10 full months in 1995. In addition to numerous dramatic courtroom moments, the trial was most notable for its strong racial overtones, its impact on the judiciary system and how it spurred Americans across the nation to openly discuss the issues surrounding domestic violence for the first time. The in-depth look at the O.J. trial 30 years later will complement a number of major cases that Court TV is closely covering in real-time, including the upcoming Arizona murder trial of "Cult Mom" Lori Vallow who is representing herself in court, the retrial of Karen Read in the killing of her boyfriend, and the trial of Bryan Kohberger, who stands accused of murdering four University of Idaho college students. MICHAEL AYALA BIO Michael Ayala, an attorney and EMMY®-Award winner, has returned to Court TV. Ayala has over 20 years of experience in-front of the camera. He previously was an anchor, reporter, writer and researcher for the original Court TV where he covered and reported on the cases involving O.J. Simpson, Scott Peterson, the Menendez Brothers, Bill Cosby and Dr. Jack Kevorkian. Michael later anchored for CBS in Chicago and has operated his own media company for the past several years.Become a supporter of this podcast: https://www.spreaker.com/podcast/i-am-refocused-radio--2671113/support.
In der heutigen Folge von „Alles auf Aktien“ sprechen die Finanzjournalisten Anja Ettel und Holger Zschäpitz über die China-Entspannung bei ASML, eine Lieferlösung für Airbus und einen kritischen Termin für Frankreich. Außerdem geht es um Atos, Airbus, GE Aerospace, Safran, Unicredit, LEG Immobilien, HeidelbergMaterials, Commerzbank, BPM, Banca Intesa, ABN Amro, Deutsche Bank, Royal Bank of Scotland, Nexi, Flatex, Brenntag, Bilfinger, Nordex, Hugo Boss, ProSiebenSat.1, Scout24, Teamviewer, Amadeus, BP, Glencore, KPN, Umicore, Akzo Nobel und Amundi MSCI USA Mega Cap UCITS ETF (WKN: ETF220). Wir freuen uns an Feedback über aaa@welt.de. Ab sofort gibt es noch mehr "Alles auf Aktien" bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts und AAA-Newsletter.[ Hier bei WELT.](https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html.) [Hier] (https://open.spotify.com/playlist/6zxjyJpTMunyYCY6F7vHK1?si=8f6cTnkEQnmSrlMU8Vo6uQ) findest Du die Samstagsfolgen Klassiker-Playlist auf Spotify! Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. Außerdem bei WELT: Im werktäglichen Podcast „Das bringt der Tag“ geben wir Ihnen im Gespräch mit WELT-Experten die wichtigsten Hintergrundinformationen zu einem politischen Top-Thema des Tages. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? [**Hier findest du alle Infos & Rabatte!**](https://linktr.ee/alles_auf_aktien) Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html
In der heutigen Folge von „Alles auf Aktien“ sprechen die Finanzjournalisten Anja Ettel und Holger Zschäpitz über schwache Zahlen bei Nike, das zweitgrößte deutsche IPO des Jahres und geben Antwort auf die Frage der Fragen. Außerdem geht es um Lufthansa, Air France-KLM, Vonovia, Kratos Defense, Lockheed Martin, Northrop Grumman, LEG Immobilien, Aroundtown, Rheinmetall, Hensoldt, Thales, RTX Corp, Pentixapharm, BristolMyersSquibb, Tui, Covestro, Lanxess, Bayer, BASF, OMV, Springer Nature, Unicredit, Commerzbank, Lamb Weston, Adobe, Applied Materials, IBM, Boston Scientific, O‘Reilly Automotive, IBP, Hormel Food Corp, Westlake und Hershey. Wir freuen uns an Feedback über aaa@welt.de. Ab sofort gibt es noch mehr "Alles auf Aktien" bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts und AAA-Newsletter. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. Außerdem bei WELT: Im werktäglichen Podcast „Das bringt der Tag“ geben wir Ihnen im Gespräch mit WELT-Experten die wichtigsten Hintergrundinformationen zu einem politischen Top-Thema des Tages. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html
As the Fed's interest rate cut cycle approaches, Goldman Sachs forecasts a silver surge. Vince Lanci explains the report and this week's key market moves. Click to watch the video! https://youtu.be/WdPK-MLush8 - To get access to Vince's research in 'Goldfix Premium' go to: https://vblgoldfix.substack.com/ - Today's show is brought to you with the support of Miles Franklin Precious Metals, who we encourage you to consider on your next precious metals purchase or sale! Take advantage of this week's Miles Franklin specials! Back Date Silver Austrian Philharmonics 1 oz: $3.10 over spot per ounce Back Date Gold Krugerrand 1 oz: $60 over spot per ounce Back Date Platinum Maple Leaf 1 oz: $80.00 over spot per ounce Contact us now at: 833-326-4653 Arcadia@MilesFranklin.com Arcadia is a licensed Miles Franklin broker, and we're happy to help with any of your precious metals questions, or put you in touch with Chris Marcus. - To join our free email list and never miss a video click here: https://arcadiaeconomics.com/email-signup/ - To get on the waiting list for your very own ´Silver Chopper Ben´ sterling silver figurine click here: https://arcadiaeconomics.com/get-a-chopper-ben/ - To get your paperback or audio copy of The Big Silver Short go to: https://arcadiaeconomics.com/thebigsilvershort/ Find Arcadia Economics content on these sites: YouTube - https://www.youtube.com/user/ArcadiaEconomics Rumble - https://rumble.com/c/ArcadiaEconomics Bitchute - https://www.bitchute.com/channel/kgpeiwO1dhxX/ LBRY/Odysee - https://odysee.com/@ArcadiaEconomics:5 Listen to Arcadia Economics on your favorite Podcast platforms: Spotify - https://open.spotify.com/show/75OH2PpgUpriBA5mYf5kyY Apple - https://podcasts.apple.com/us/podcast/arcadia-economics/id1505398976 Google-https://podcasts.google.com/feed/aHR0cHM6Ly9teXNvdW5kd2lzZS5jb20vcnNzLzE2MTg5NTk1MjMzNDVz Anchor - https://anchor.fm/arcadiaeconomics Amazon - https://podcasters.amazon.com/podcasts Follow Arcadia Economics on these social platforms Twitter - https://twitter.com/ArcadiaEconomic Instagram - https://www.instagram.com/arcadiaeconomics/ #silver #silverprice And remember to get outside and have some fun every once in a while!:) (URL0VD) We do receive compensation from Miles Franklin from orders placed through our show. For our full disclaimer go to: https://arcadiaeconomics.com/disclaimer-miles-franklin-precious-metals/Subscribe to Arcadia Economics on Soundwise
Good for the Goldmans!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
There is an all-star tribute for Robbie Robertson coming up in October in LA...Ronnie Wood's son married the daughter of Iron Maiden's Steve Harris...and OJ's stuff will be sold off and proceeds will go to the Goldmans.
‘Nothing in my 20-year career in a corporation prepared me to run a business.'Yes, being incredibly successful in a corporate job - even a place like Goldman Sachs - does not naturally mean you have all the skills and experience to launch a successful business.The rules of the game are completely different when you become a solopreneur.Listen to how Evelyn Poh, ex Goldman Sachs VP transitioned from a financially lucrative career at Goldmans to becoming a Financial Educator and Creator of The Financial Styling Academy.Why did Evelyn walk away from an established career to do what she does now?This episode will shed light on what it really takes to launch your business, why your purpose matters, and give you a different perspective on financial security and success.Evelyn is a financial coach who helps people build the lives they want without running out of money. She spent 20 years at Goldman Sachs working in London, Zurich and Tokyo, and qualified as a chartered accountant with the Institute of Chartered Accountants in England and Wales (ICAEW).Connect with Evelyn on LinkedIn: https://www.linkedin.com/in/evelyn-poh/
Join us for an enlightening conversation with Jonathan and Andi Goldman as we explore the healing power of humming. Discover how simple humming exercises can enhance meditation, lower stress, and promote overall wellness. We delve into their book, "The Humming Effect: Sound Healing for Health and Happiness," and discuss the physiological benefits of sound healing, including its impact on the vagus nerve, heart rate, and blood pressure. Uncover the science behind psychoacoustics and vibroacoustics and learn how intentional sound practices can bring balance to your body. Visit healingsounds.com and our podcast page for episode notes, the Goldmans' works, and additional resources.00:00 Doctor Amy welcomes Jonathan and Andy Goldman.03:10 Sound bites, frequencies, vibration in overall health.07:02 Consciousness projected onto sound affects water crystals.09:50 Silence is essential for body, mind, spirit.14:52 Creating self sounds can lower heart rate.18:45 Conscious humming empowers self-therapy through sound.20:29 Pinched nose stops humming, surprising sound fact.25:48 Recommend five-minute mindfulness practice with extra time.27:43 Thankful for time, sharing humming sound healing.***********************************************SUPPORT DR. AMY ROBBINS: If you're enjoying the podcast and finding value in guest interviews, ghost stories, and the content I share, please consider supporting the show by becoming a Patreon member for as little as $5 a month at Patreon.com/DrAmyRobbins As a member you'll get more say in the content we cover and exclusive access to behind-the-scenes goodness! Stay Connected with Dr. Amy Robbins: ● Instagram● YouTube● Website● Facebook ***********************************************FOLLOW JONATHAN and ANDI GOLDMAN https://www.healingsounds.com/ Life, Death and the Space Between is brought to you by:Dr. Amy Robbins | Host, Executive ProducerPodcastize.net | Audio & Video Production | Hosted on Acast. See acast.com/privacy for more information.
You know of the infamous murder trial involving OJ Simpson and the Goldman and Brown families that took place in the 90s. And in case you happened to miss the news, Simpson passed away recently, stirring up the family conflicts all over again. Here at Absolute Trust Talk, we have an affinity for celebrity estate drama, mainly because of the important estate planning lessons we can take away. While the exact details of OJ's estate structure remain unknown, the estate will probably undergo probate due to the presence of creditors. Listen in as we cover all the details we know so far and share some essential estate planning wisdom with you along the way. Time-stamped Show Notes: 0:00 Introduction 1:23 Here's what we know about the executor handling OJ Simpson's estate and the public statement made. 3:35 Next, we're summarizing the current legal tension with the Goldman family. 5:33 The Goldmans want their rightful payout from the Simpson estate. However, much of his assets are tied up. 7:36 Listen in as we discuss what it means to go through the probate process and the executor's role. 8:55 When divvying up money from an estate, the probate expenses and executor must first be paid, as well as super creditors like the IRS.
USC cancels valedictorian speech. Free speech experts fear USC is offering other schools the playbook on how to silence potentially controversial speakers at this year's commencement season. O.J Simpson never paid the Goldmans the millions he owed them. Can they collect now? News Publishers Group urges government to investigate Google for blocking some California news outlets. How much is a vet visit? Behind the soaring cost of pet care.
Simpson's executor of his estate said that he will fight to prevent the payout of a $33.5 million judgment awarded to the families of his ex-wife Nicole Brown Simpson and her friend Ron Goldman. The Golden Bachelor's marriage to Theresa Nist ended because Gerry "wanted out.” Meghan Markle was captured on video appearing to politely redirect a woman who was trying to stand next to Prince Harry for a picture celebrating his polo team's victory. Rob is joined by his dear pal Garrett Vogel from Elvis Duran and the Morning Show with all the scoop. Don't forget to vote in today's poll on Twitter at @naughtynicerob or in our Facebook group.See omnystudio.com/listener for privacy information.
It's not every day that one of our guests from the world of finance has successfully scaled Everest 5 times, been awarded an MBE by the Queen, raised millions for charity, and is a vocal ambassador for the NSPCC. For his day job, he led trading desks at Goldmans, CS, UBS and Bluecrest. If that wasn't enough for most people, he then became sufficiently intrigued by the changing world of gold to become CEO of the World Gold Council (WGC). In this fascinating conversation, David explains how the WGC is bringing gold bullion into the digital age from regulatory, provenance, ESG, and tokenisation angles. He assesses growing institutional demand (gold prices have hit record highs in recent weeks), describes the supply side dynamics, examines why gold improves the risk/return characteristics in a portfolio, why gold mining companies may be too cheap, and how the future may look for gold. Finally, David reflects on his childhood as a victim of child sexual abuse, the agony and therapy of the film about him, Sulphur & White, and the priorities which need addressing (in the UK alone, 1 in 20 children suffer sexual abuse). The Money Maze Podcast is kindly sponsored by Schroders and IFM Investors Sign up to our Newsletter | Follow us on LinkedIn | Watch on YouTube
Liebe Taschenhalter, Lukerinnen, Perma-Bullen und Stückmünzen-Hodler! Aus dem Münchner Wurstkessel präsentiert u/Battleham_117 besondere Schmankerl. Dieses Mal wieder in auditiver Form! Es war mein erster hochkarätiger Gast, also verzeiht mir die anfängliche Aufregung. Prof. Dr. Holger M. Goldgraf u/prof_goldgraf ist heute mit dabei! Kniet nieder, ihr Dividenden-Jäger, Kompetenz ist zu Gast! Der Deutsche Finfluenza, der eigentlich keine Vorstellung benötigt, ist heute erneut auf der Mauerstraße vertreten. Er ist einer der Wenigen, die es gekonnt mit einer Prise Humor schaffen, einen deutlichen Mehrwert für alle Finanz-Interessierten im deutschsprachigen Raum zu leisten. Die Mauerstraße wird ihn wie bei der INVEST 2024 in Stuttgart vertreten sein. (Communitytreffen - 27.04.2024 - Samstag) // Kommt in die Gruppe! Mehr Informationen folgen (TM). Wie immer auf Spotify, Apple Podcast, Google Podcast und überall sonst. Alle Links sind auch dem Profil von u/monchella420 zu finden. Die Fragen wurden von der Community gesammelt und von mir fachmännisch destilliert: Hauptfragen: 1. Wie geht es dir? 2. Denkst du manchmal an mich?
In this podcast, host Steve Farrell is joined by pioneers in sound healing, collaborators, and dear friends of Humanity's Team Jonathan & Andi Goldman, for an incredible collective and soul-cleansing 22nd annual World Sound Healing Day. During this discussion with Jonathan and Andi, you will learn of the sounds made to send love, compassion, and understanding to the Gaia Matrix and how the power of sound healing will lead our Global Collective to a higher state of consciousness. In this podcast, you will discover… The way sound fosters harmony on the planet The origin of World Sound Healing Day What the concept of seperated self is The effects of sound healing and intention How to listen without judgement and with compassion And much, much more… ***Note: this is a special rebroadcast, and any websites, links, programs, or events mentioned may no longer be active (or dates may have been changed). Thank you!*** For more teachings and rich healing experiences with The Goldmans, be sure to check out Humanity Stream+ here, where you will find dozens of great programs with them Explore Humanity's Team and the timeless truth that We Are All One. Learn more about the Humanity's Team free education programs.
In a recent analysis by Goldman Sachs, 21 stocks were highlighted that can withstand higher borrowing costs and exhibit stability. Join me as I delve into these recommendations, examining the fundamentals, momentum, seasonality, and expert insights from various banking analysts. We'll focus on elements like the price-to-earnings ratio, net leverage, and the overall sentiment surrounding each stock. While some of these options present compelling opportunities, the current market environment calls for a cautious approach. For those looking to navigate this complex landscape, continue reading for a comprehensive breakdown, and be sure to check out our additional resources for more in-depth information. Follow me on LinkedIn: https://lnkd.in/e9FFsybJ Follow my YouTube channel: https://www.youtube.com/channel/UChJeyFshCmwND6-aY3pSs3Q Join My Private Great Investments Programme www.alpeshpatel.com/shares Visit www.campaignforamillion.com to avail of free educational resources to make you a better investor ------------------------------------------------------------------ RESOURCES & LINKS ------------------------------------------------------------------ https://www.pipspredator.com https://www.investing-champions.com https://www.trading-champions.com #tradingonline #investing #trading #pipspredator #alpeshpatel #business Subscribe to my newsletter for more tips: https://www.alpeshpatel.com/blogsignup Subscribe to my Telegram channel for daily market information: https://t.me/pipspredator Follow me on my LinkedIn Page: https://www.linkedin.com/in/alpeshbpatel/ Join my Facebook community: https://www.facebook.com/tradefx4profit Follow more free resources including my book from www.investing-champions.com and www.alpeshpatel.com My daily insights are on my instant messenger app - also free. Alpesh Patel OBE
Are these 12 stocks as good as Goldmans think? I beg to differ. Join My Private Great Investments Programme www.alpeshpatel.com/shares Risk warning: None of this is individual advice and all investing is risky This is part of my www.campaignforamillion.com to teach a million people to be better investors and make an extra million in their pensions as a result across their lifetimes. Follow me on LinkedIn: https://lnkd.in/e9FFsybJ Follow my YouTube channel: https://www.youtube.com/channel/UChJeyFshCmwND6-aY3pSs3Q ------------------------------------------------------------------ RESOURCES & LINKS ------------------------------------------------------------------ https://www.pipspredator.com https://www.investing-champions.com https://www.trading-champions.com #tradingonline #investing #trading #pipspredator #alpeshpatel #business Subscribe to my newsletter for more tips: https://www.alpeshpatel.com/blogsignup Subscribe to my Telegram channel for daily market information: https://t.me/pipspredator Follow me on my LinkedIn Page: https://www.linkedin.com/in/alpeshbpatel/ Join my Facebook community: https://www.facebook.com/tradefx4profit Follow more free resources including my book from www.investing-champions.com and www.alpeshpatel.com My daily insights are on my instant messenger app - also free. Alpesh Patel OBE
Text messages given to FBI: Chinese wanted Biden family name to help acquire U.S. energy assets. “They will be the Goldmans of China,” one of Hunter Biden's business associated boasted about the relationship with CEFC. Learn more about your ad choices. Visit megaphone.fm/adchoices
Margot Robbie är den gemensamma nämnaren då vi både pratar Goldmans penningtvätt och Barbie. Vi upprörs över corporatism, bankernas KYC och pratat om Mattel-aktien och deras nya strategi. Köp eller sälj? Hosted on Acast. See acast.com/privacy for more information.
Jonathan Goldman, author of Healing Sounds: The Power of Harmonics and The Humming Effect: Sound Healing for Health and Happiness, which he co-wrote with Andi Goldman, are the topics of today's show and they are both my guests. Jonathan, an international authority and pioneer in the field of sound healing, also a musician and teacher as well as Andi Goldman, a licensed psychotherapist, specializing in holistic counseling and sound therapy will share their knowledge with us regarding how sound actually heals as well as the methods of using sound for healing. We'll dig deep into frequencies and harmonics as well as the importance of intent when using this modality of healing. The Goldmans will share with us the most important healing instrument and why they think sound can be used for planetary healing. I plan to shake things up a big and ask about the ancient sistrum and how it was used as well as their thoughts on if sound can move large stones in ancient times to build temples.
Kwasi Affum MY PROPERTY WORLD profile podcast with Will Mallard EPISODE #277 Easily the best dressed man in Property, Kwasi Affum is a career banker including stints at Goldmans, JP Morgan and has built up a personal investment portfolio including HMOs in NorthWest London. We cover his early years, the value of education and role models, working in the 2008 banking crisis, realising how risky employment is, starting to invest, the importance of analysis, his slowmoneyclub.com platform and why he believes Spurs is the most successful club in the Premier League. You can contact Kwasi via slowmoneyclub.com. CAPITAL IS AT RISK IN ALL PROPERTY INVESTMENTS. Will Mallard is a social impact investor focused on English housing portfolios. #propertypodcastoftheweek #ukpropertyinvestors #podcastforukinvestors #humanbehaviourinproperty #ukproperty #propertyoutlook #propertyinvestments #wealthknowledge #valuepropertyuk #marketukimpact #measuresofsuccess #investmentworldpostpandemic #financeinpropertydeals #peopleinpropertyuk #partnersinpropertynetwork #propertyinvestingnorthwestpodcast #profilepropertyinvestor #seeingthefuturenow #bankerturnsinvestorukproperty #slowmoneyclubfounder #slowmoneyclubpodcast --- Send in a voice message: https://podcasters.spotify.com/pod/show/my-property-world/message
21st Century Radio Host Dr. Zohara Hieronimus sits down with co-authors Jonathan and Andi Goldman to discuss all the things sound healing. 30 years ago Jonathan wrote the classic Healing Sounds: The Power of Harmonics, published by Healing Arts Press. Does his guidebook still apply? How can harmonics be used in healing? How can humming lead to better health and happiness? How do intention and gratitude effect how we use sound every day? We delve into these questions and much more. About Healing Sounds: Sharing many easy-to-follow sound healing exercises, such as “Vowels as Mantras” and “Overtoning,” Goldman explains in detail how to perform vocal harmonics--a form of overtone chanting--and experience their transformative and healing powers. He shows how harmonics can be used as sonic yoga for meditation and deep relaxation as well as to enhance energy and resonate the chakras, the energy centers of the body. In their book The Humming Effect the Goldmans reveal that humming is one of the simplest and yet most profound sounds we can make. If you have a voice and can speak, you can hum. Research has shown humming to be much more than a self-soothing sound: it affects us on a physical level, reducing stress, inducing calmness, and enhancing sleep as well as lowering heart rate and blood pressure and producing powerful neurochemicals such as oxytocin, the “love” hormone. In this guide to conscious humming, Jonathan and Andi Goldman show that you do not need to be a musician or singer to benefit from sound healing practices—all you need to do is hum. Providing a self-healing method accessible to all, the authors reveal that, even if you have no musical ability, we are all sound healers.
21st Century Radio Host Dr. Zohara Hieronimus sits down with co-authors Jonathan and Andi Goldman to discuss all the things sound healing. 30 years ago Jonathan wrote the classic Healing Sounds: The Power of Harmonics, published by Healing Arts Press. Does his guidebook still apply? How can harmonics be used in healing? How can humming lead to better health and happiness? How do intention and gratitude effect how we use sound every day? We delve into these questions and much more. About Healing Sounds: Sharing many easy-to-follow sound healing exercises, such as “Vowels as Mantras” and “Overtoning,” Goldman explains in detail how to perform vocal harmonics--a form of overtone chanting--and experience their transformative and healing powers. He shows how harmonics can be used as sonic yoga for meditation and deep relaxation as well as to enhance energy and resonate the chakras, the energy centers of the body. In their book The Humming Effect the Goldmans reveal that humming is one of the simplest and yet most profound sounds we can make. If you have a voice and can speak, you can hum. Research has shown humming to be much more than a self-soothing sound: it affects us on a physical level, reducing stress, inducing calmness, and enhancing sleep as well as lowering heart rate and blood pressure and producing powerful neurochemicals such as oxytocin, the “love” hormone. In this guide to conscious humming, Jonathan and Andi Goldman show that you do not need to be a musician or singer to benefit from sound healing practices—all you need to do is hum. Providing a self-healing method accessible to all, the authors reveal that, even if you have no musical ability, we are all sound healers.
21st Century Radio Host Dr. Zohara Hieronimus sits down with co-authors Jonathan and Andi Goldman to discuss all the things sound healing. 30 years ago Jonathan wrote the classic Healing Sounds: The Power of Harmonics, published by Healing Arts Press. Does his guidebook still apply? How can harmonics be used in healing? How can humming lead to better health and happiness? How do intention and gratitude effect how we use sound every day? We delve into these questions and much more.About Healing Sounds:Sharing many easy-to-follow sound healing exercises, such as “Vowels as Mantras” and “Overtoning,” Goldman explains in detail how to perform vocal harmonics--a form of overtone chanting--and experience their transformative and healing powers. He shows how harmonics can be used as sonic yoga for meditation and deep relaxation as well as to enhance energy and resonate the chakras, the energy centers of the body.In their book The Humming Effect the Goldmans reveal that humming is one of the simplest and yet most profound sounds we can make. If you have a voice and can speak, you can hum. Research has shown humming to be much more than a self-soothing sound: it affects us on a physical level, reducing stress, inducing calmness, and enhancing sleep as well as lowering heart rate and blood pressure and producing powerful neurochemicals such as oxytocin, the “love” hormone.In this guide to conscious humming, Jonathan and Andi Goldman show that you do not need to be a musician or singer to benefit from sound healing practices—all you need to do is hum.Providing a self-healing method accessible to all, the authors reveal that, even if you have no musical ability, we are all sound healers.
There are basically two categories for novelist Elyssa Friedland's work: Jewy and super-Jewy. Friedland has a new book out this week, “The Most Likely Club,” but many listeners will know her from two, very Jewy, earlier works, “Last Summer at the Golden Hotel” and "The Floating Feldmans.” Friedland has written two other novels and is looking forward to the publication of her first children's book soon. Today, in addition to working on her own books, Friedland teaches novel writing at her alma mater, Yale University. She's also a Columbia Law School grad and once upon a time worked as an associate at a major law firm before turning to writing full-time. Her new novel, “The Most Likely Club,” has some of her trademark Jewish flavor in the characters, but weaves together the stories of four women, high school best friends, who are reunited for their 25th high school reunion. Friedland spoke with The Times of Israel for our weekly Times Will Tell podcast, a week before the publication of "The Most Likely Club." The following transcript has been very lightly edited. The Times of Israel: Elyssa, thank you so much for joining me today. Where am I finding you? Elyssa Friedland: You are finding me on Long Island in New York. So we came together, of course, to speak about your newest book, "The Most Likely Club," but also about some of your other great books that, coincidentally actually, I read four out of five of your novels without even knowing that they were written by you, aside from the last one, of course, which I asked for. Wow, that's very flattering. I'm very happy to hear that. You might be the only person other than my mother to do that. You can say that I'm your number one fan, but not in a "Misery" kind of way. I just really enjoyed your work, and I just would read the synopsis of a novel, buy it, read it, and say, this sounds somewhat familiar in tone to another book that I really enjoyed and read. And then I looked up and thought, yeah, same author -- again and again. It was just really kind of coincidental and strange, but fantastic. Well, I'm very happy to hear that. I do think I have a voice that carries through from book to book. So I do try, of course, to vary the plots, create new characters, always keep it interesting for myself, not only for the reader to have something new, but for me. I'm the one who has to be with it a lot longer than the reader does while I'm writing it. And so I do try to always come up with very new ideas, but I think my voice is my voice, so I'm not surprised that there are echoes of it in all the books. So for me personally, I kind of divide your works into extremely, very Jewy and medium Jewy. In the very Jewy category, we have, of course, "Last summer at the Golden Hotel" and "The Floating Feldmans." In the medium Jewy category I would put your newest novel, "The Most Likely Club," which comes out September 6, and then "Love and Miscommunication." Now, the one novel I didn't read, where would that fit in the Jewy or very Jewy spectrum? I would say, "The Intermission," the one you did not read is definitely medium- to low-Jewy. So you haven't missed out on any super Jewy. So let's just very briefly speak about the plot behind "The Most Likely Club." Give us a couple of sentences. What is this book about? "The Most Likely Club" is about four women that were very close friends in high school, and they are reunited. Three of the four of them reunite at their 25th high school reunion and one of them is unable to make it, she says, because of work obligations, and being back together on campus where they went to school. Seeing their former classmates just filled them with all the usual angsty feelings. And they really take a moment to take stock of their lives where they are 25 years out of high school and think about, is this where they wanted to be? Is this where they thought they would end up? After a sort of boozy night of reminiscing and remembering who they once were, they decide to try to make their high school superlative come true. Their "most likely" in the yearbook. And they embark on this plan to actualize some of their dreams from when they were teenagers. And as you can imagine, when you're in your mid-40s, it's difficult to make that kind of life change. And so we follow these women as they try to right the ship of their lives, but of course are met with all sorts of obstacles. And then the fourth friend who is not able to make it to the reunion, of course she folds into the story, and we learn some big surprises about her. And it's really just the story of what it's like to reach middle age, look back and take stock of where you are and really take time to think about if this is where you want to be and when is it too late to make a change. Not only do I know what you're talking about, I live what you're talking about. I realized suddenly when I was reading this book that my high school union will be 30 years in the spring. So, yes, I fully grasped all the different dramas and concerns of each of these women, and it really felt like they were all in me or I was all in them. And when you were writing these characters, did you feel that yourself? That you were splintering off different concerns and challenges of your life as a working mother, wife and professional and putting it into these four different women. Definitely. I mean, when I think about it -- I won't bore your listeners with going into each character -- exactly how I'm similar to them, but for sure there are some that I'm more similar to than others. I would say I'm not a doctor, obviously, I'm a writer. But the doctor character in the book is probably the one that I relate to the most in my day-to-day life, because she and her husband are both working professionals and they have three children, just like me and my husband. We have three children and I definitely still do the lion's share of the child -- I wouldn't necessarily say, like, child raising, I think we share that. But I certainly do the lion's share of the camp forms, the health forms, the dentist visits, the selection of camp and after-schools. I could go on and on. And I know many women who are listening to this can relate to that. And so in her life, Priya the character is named in the book, is really similar to mine. She's really overwhelmed. She doesn't quite understand why it has to be this way, like why her husband, who works basically in the same job, they work at the same hospital, is sort of let off scotch free and he can go out for a run while she's buried and, like, uploading the COVID vaccine cards, essentially. And she just doesn't have a free second to herself. Sometimes when she thinks about what she'd want to do with her free time, she can't even figure it out because she hasn't had free time in so long. And so she's a character that I really relate to in my day-to-day life. Although it was fun making her a doctor because it did still let me escape a little bit because I don't even know that much about the medical profession and I had to research that and it kind of let me have a little bit of distance from her. So I didn't pour every single detail of my life. If she had been a writer, that probably would have been a bit too much. So I have a lot in common with her. But the other women, too, there one character really fixated on her weight. And I'm definitely someone who if I had a reunion coming up, I would try some crash diet and I could see myself getting really obsessed with how I look when I'm going back to school, which is, of course, not the ideal way to be spending your time and your energy. And then the other women as well. There's a very powerful CEO. I'm not her, but she's just someone I don't know if I relate to her as much as I just think about women like that. And the double standard that is applied to women in positions of power and how unfair it is. Like the Hillary Clintons of the world who are just the more ambitious they are, the more maligned they are. So, yeah, I have bits and pieces of myself and all the women and things I see from my friends and just from the headlines that interests me. I just found myself nodding, laughing and wanting to cry with some of the situations. And we won't spoil it because it's definitely worth reading. I just want to mention that while it may sit in the chick-lit category, it is so deep in its message and it so hit home to me as a working mother of seven. It is no question that all of these concerns that especially the Priya character has, every woman I know in our situation of working and having children is facing this mental load challenge. Now, that's turned to the "Last Summer at the Golden Hotel," which is actually, can I say this, referred to in "The Most Likely Club." I loved that. So tell us briefly, what is this book about? That book is about a hotel in the Catskills, very much like the hotel in "Dirty Dancing," if you can picture Kellermans. I know that's a movie that basically everyone with a pulse has seen. So it's about a hotel that was once the place to see and be seen, a thriving enterprise. But it's set in modern times and it's really on its last leg and needs a lot of refurbishment. Isn't attracting guests the way it used to. It's co-owned by two Jewish families, of which there are now three generations of each family, the Goldmans and the Winegolds. And one member of the Winegold family runs the hotel on a day-to-day basis. And he receives an offer from a casino operator who wants to buy the hotel, tear it down and put a casino up in his place, which is what happens at the Concord Resort, which is one of the greats in the area. And he calls a family meeting at the hotel and reluctantly, the three generations make their way back to campus. I guess I like a lot of back to campus because that's also the case in "The Most Likely Club." And so these three generations come back to the hotel and we learn what's going on in all of their lives. They all have full lives outside of the hotel and so we get slivers of their lives and the complications and the issues they're facing and then how those issues affect what they want to do with the hotel, if they want to sell it or if they want to try to revive it. And in some ways it's really an intergenerational story because the grandchildren who are in their 20s have a lot of ideas about how to make the hotel hip and cool and attract millennials and attract people who are living their lives on social media. And of course, the grandparents, the founder generation, can't really make heads or tails of some of these bizarre suggestions like let's make our own honey and have beehives, let's have all vegan food options, let's have goat yoga, et cetera, et cetera. So as I'm sure you can understand, they have very different ideas of what to do with the hotel. But for everyone, it's an important part of their legacy. And so it's really an emotional decision that has to be made. So I won't give away the ending. Don't give away the ending because I was actually surprised by the ending! But both in this book and in "The Floating Feldmans," it's really a tale of several generations getting together and what ensues right in these little microcosms. "The Floating Feldmans" on a cruise. And you are so good at writing the different voices of the different generations. Talk to me about how you capture the voice of an 80-year-old versus how you capture the voice of a 20-something-year-old. First of all, thank you for saying that. I definitely work hard at it. If I had to say why I am good at that, it's probably that I just have a really good ear when I'm out in the world. First of all, I live in New York City. So living in New York City, just going down the block, you are just constantly surrounded by people of all different ages, genders, and backgrounds. I could imagine if I had a more rural existence and I worked from home in a quiet town and went for a walk and maybe saw one person in an hour, it might be a very different experience. Whereas if I go to buy milk in Manhattan, I'm just surrounded by voices. And so I felt really lucky because I have exposure to a wide range of voices just when I walk down my block. And I think that because I am just a curious person and I'm always listening, I am able to absorb the intonation the verbiage, the mannerism. I look around and I listen. And that I think it helps me channel people that are in a different stage of life than I'm in. And so I just feel really grateful. I credit New York City with my ability to channel these voices that are very different than my own because otherwise, I don't know where else I could say that I get it from because yes, do I know older people? Sure. I have parents, I have in-laws. Do I know people in their twenties? I do teach at the college level, but the truth is, I'm in the classroom with them. I'm doing most of the talking for two hours, and I leave. So I don't think it comes from that. I think it really comes from just living in a bustling place and having a good ear. As you mentioned, you do teach. So is this something that you would give as a tip to your students? I mean, not everyone can have the luxury of getting to live in New York City, and not everybody wants to. And for some people, from a writing perspective, that would be a terrible place to live because it's so full of distraction. And there's the Ralph Waldo Emerson version of writing, which is you got to go and tuck yourself in a cabin and have quiet. And so there are certainly many people who wouldn't get a stitch of work done if they lived in such a bustling place and would like to be off the grid. So I don't know that I would necessarily give that advice, but I would say maybe just see what you're good at. And if you feel like it's a really big stretch for you and it's not coming across as convincing to write like an 82-year-old man, don't write an 82-year-old man. Write the person that you feel comfortable writing, that you feel comfortable channeling. And maybe that's someone that's very similar to you. Maybe that's someone that you knew once upon a time. Very closely in life or you have some experience with. But you can tell. I think. If it's a massive struggle to channel someone else's voice. If it's very integral to the story. I would just make it my business to at least find someone. One or two people who can an authenticity read. If you're writing an 82-year-old man, find an 82-year-old man and have them read it and correct it. I mean, when I was first starting out, even just writing a male voice, my husband would read my work and he would say, "No man would say that." He can't speak for all men, but he can maybe speak for a majority of men or at least tell me that something didn't ring true to him personally. And then it was up to me to decide what to do with that. But I don't think there's any reason why someone shouldn't reach out and have someone read the work. For this book, "The Most Likely Club," my publisher hired people to read the book, to read the characters for an authenticity read, because there's an Asian character, there is a bisexual character, there's an Indian character. I am none of those things. And so they have these authenticity reads done, and I'm so grateful for that someone who says, "That's really not the way it works in an Indian family," or, "That's not the way I would phrase it." And I really get my publisher a lot of credit because they said to me, "You don't have to take any of this. This is for you to absorb and decide what you want to do." If there was something very offensive, they would want me to do something about it. But it was up to me, and I took basically almost everything because I just want to sound as authentic as humanly possible. It's interesting that you talk about wanting to sound authentic in these niche identities of the Indian or the bisexual, et cetera, et cetera, because at the same time, while they do to me at least sound authentic, definitely your Jewish voice sounds authentic. But it's always very universal stories that you're writing, too. Well, I think that's really true because we're all still people and we all still feel the same things. Of course you want to be factually correct: The only Indian food you know is the kind served in a restaurant, and that's never something that is served in an Indian home? That's not great. But does an Indian 16-year-old girl feel self-conscious in high school? Yeah. So do the Asian girl and the black girl and the white girl and the Jewish girl. Feeling self-conscious when you're 16 in high school is about as universal as it gets. Being middle-aged and thinking, "Oh, my God, how did I end up here? And is this what I want out of life again?" It's a privilege to be able to take the time to even think about that. And I do want to acknowledge that not everyone has the luxury of making the changes they want to make. But I would say if given the time and the space to think about it -- these women are 43. If you ask any 43-year-old, "Take an hour of quiet and think about where you are in your life, is there anything you want to change? I'm pretty sure they'd be able to come up with a couple of things. No matter what they look like or what their background is. Who has an hour, though, right? Let's talk about how Judaism plays a role in your writing. None of the characters are especially observant or religious Jews, but they are so steeped in the culture. Even in the least Jewy books that we identified, there's such striking cultural Judaism. So how is Judaism playing a role in your writing? I think that it's because it just plays such a big role in my own life that it filters over onto the page. I am not observant, but I'm just very culturally Jewish, as comes across in my books. I went to a Jewish day school. I go to synagogue on the major holidays. We celebrate Shabbat in our home, even if we're not observing it in a religious way. But we like candles, we eat challa, we have a Shabbat dinner. And this is the world I know. It's also, like, the humor I know. My grandparents were immigrants. Even my parents were immigrants from Europe. They were born after the war, and they came here from Eastern Europe. And so that's literally the humor that I grew up with, this sort of very Borsh belt, eastern European Jewish humor, and it's just who I am. I feel like I've just been steeped in Jewish culture from a very early age. And I grew up in a Jewish town. I went to Jewish camp. I could go on and on and on. So I feel like my Judaism is just a really big part of who I am. And so then it ends up becoming a natural part of my writing. Even when I don't set out to write the Jewish book, I end up incorporating some of it because I think I just like it and I feel comfortable. It's the opposite of needing the authenticity reads. Here is where I'm in my milieu, I know what I'm talking about. And that feels good because writing is really hard. And then when I can write about something that I feel like I know, first of all, I feel like I can push boundaries more because I feel more comfortable and I could just be more creative and find even more humor because I'm not first trying to learn about it and then write about it. I already know it. So it's a comfortable space for me to be in as a writer, so I find myself returning to it. Have you ever had any kind of antisemitic blowback because of this? Zero. Absolutely zero. And I love saying that. It's honest to God truth. And I've talked about this in previous interviews, but when "Last Summer at the Golden Hotel" came out, in May 2021, it happened to be the same month that there was a lot of media coverage about the rise in antisemitism, and the statistics were staggering about the antisemitic attacks that were happening across the globe. Up some crazy percentage, like up 100%, something really, really horrifying. And my book came out and it was received with the warmest embrace by so many non-Jewish readers. Most of my readers aren't Jewish. And I could just tell you, go on my Instagram, look at the comments, and it was like 1000 comments of, "I didn't know anything about Jewish culture. This is the first book I've read where I've learned a lot about Jewish identity and Jewish culture. And I'm fascinated." It was one positive thing after another after another after another, and it was a great reminder of,, yes, there are bad people doing crazy things, but most people don't hate Jews, and most people are very excited to read and learn about Jewish culture in the way that I love. And the book sold well enough and was distributed widely enough that I can honestly say that it means something that I never came across a single antisemitic reaction. That's really heartening. I wonder about this next novel's reception because it is basically about the inner lives of women of a certain age, my age essentially, and there's not a lot of empathy for that in American society. There's, of course, the Karen Meme. There's all sorts of things of that nature where we women can't have it all, women want to have it all, but suck it up and move on. Are you worried at all about this kind of reception? Yeah, I would say I am a bit worried about that. That people just are sick of what they would call whining. Enough. But I wasn't so worried that I wasn't going to write it because I feel like I'm living it and I lead a very privileged life, and yet I still feel like I can't take it. Like I'm losing it as a working mom, and I'm trying and I'm just coming apart at the seams. And if I feel it, I can only imagine people who don't have as much privilege and the luxuries that I have in my life. And so I know that I write from a place of privilege, I'm aware how much worse it is for people who don't have the resources to have a babysitter and not have to worry about every doctor bill that comes in. I have mostly female readers. And so it will be interesting. I think that people's responses are going to be very personal. It's going to strike a chord either very positively or negatively. People are going to have very strong reactions to the book, and I have to be prepared for that. All right, I'm reminding our listeners that we're about a week and a bit ahead of the publication of this newest book. So by the time they hear it, everything will be fine. It will be published. The world will embrace it, I feel sure, having read it just recently. And really such a pleasure reading your work -- as coincidentally as it has been. And I will, of course, follow you more intentionally from here on out. So really such a pleasure speaking with you. Thank you. And thank you so much for having me. It was very fun to discuss my books with you. Times Will Tell podcasts are available for download on iTunes, TuneIn, Pocket Casts, Stitcher, PlayerFM or wherever you get your podcasts. IMAGE: Novelist Elyssa Friedland with her new book, 'The Most Likely Club.' (Courtesy)See omnystudio.com/listener for privacy information.
Franny got a weird DM. Tik Tok trends. Uber is now offering car pooling again. Guys, massage her feet, she loves it. The Goldmans say O.J. hasn't paid very much. Should you get a sleep divorce? Tom Hanks is crashing more weddings now than Bill Murray.
Franny got a weird DM. Tik Tok trends. Uber is now offering car pooling again. Guys, massage her feet, she loves it. The Goldmans say O.J. hasn't paid very much. Should you get a sleep divorce? Tom Hanks is crashing more weddings now than Bill Murray.
Kim Goldman and Fred Goldman join host Renee Williams on Parallel Justice to discuss the loss of their beloved family member Ron Goldman. In this episode, they discuss the rich and wonderful life that Ron lived, the kind and considerate person he was, the media's treatment of him as “the other victim,” the traumatizing experience of the criminal trial and the ongoing journey to seek justice and healing through the civil process. Kim Goldman https://kimberlygoldman.com/ (https://kimberlygoldman.com/) Visit the National Crime Victim Bar Association for referrals to victim-centered attorneys in your area. https://victimbar.org/ (https://victimbar.org/) To contact compassionate, confidential support, call or text 1-855-484-2846 or chat at VictimConnect Resource Center at https://victimconnect.org/ (https://victimconnect.org/)
One of the largest real estate companies, Evergrande, is in an enormous pile of debt, owing $325 billion dollars. In the third quarter of the ongoing financial year, official Chinese data revealed that GDP growth stood at 4.9 percent, down from 7.9 percent in the previous quarter, while Goldmans cut its entire 2022 GDP forecast from an already low 5.8% to just 5.4%.
In der heutigen Folge „Alles auf Aktien“ berichten die Finanzjournalisten Anja Ettel und Holger Zschäpitz über das historische Paradox bei Google, einen Deal mit Win-Win-Potenzial und das schwere Lose einstiger Hype-Aktien. Außerdem geht es um Siemens Energy, Infineon, Eli Lilly, Uber, Wallbox, Alphabet, Apple, Microsoft, Bitcoin, Beyond Meat, Oatly, Rize Sustainable Future of Food (WKN: A2P876), Xiaomi, LONGi Green Energy Technology, Li Ning, China Tourism Group Duty Free, Trip.com, Anta Sports, Xinyi Solar, Han's Laser Technology, Invesco KBW Nasdaq Fintech (WKN: A2DHWJ), Robeco FinTech Fund (WKN: A2JHGU), Paypal, Intuit, Adyen, Nasdaq, Fiserv, Nexi. "Alles auf Aktien" ist der tägliche Börsen-Shot aus der WELT-Wirtschaftsredaktion. Die Wirtschafts- und Finanzjournalisten Holger Zschäpitz, Anja Ettel, Philipp Vetter, Daniel Eckert und Nando Sommerfeld diskutieren im Wechsel über die wichtigsten News an den Märkten und das Finanzthema des Tages. Außerdem gibt es jeden Tag eine Inspiration, die das Leben leichter machen soll. In nur zehn Minuten geht es um alles, was man aktuell über Aktien, ETFs, Fonds und erfolgreiche Geldanlage wissen sollte. Für erfahrene Anleger und Neueinsteiger. Montag bis Freitag, ab 6 Uhr morgens. Wir freuen uns an Feedback über aaa@welt.de. Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören.
In this episode Imran Lakha, founder of Options Insight, talks to Kuda Chinhara, an experienced options trader and technical analysis expert. They discuss when Kuda started trading at Goldmans in 2005 and how he got into charting and technical analysis. Kuda explains why he finds charts so informative and how he is able to gain insights from analysing rich data sets going back decades and identifying repeating patterns in the time series data on stock markets. Outside of the longer term cycles that form from central bank and government policy actions, Kuda, says that he doesn't look at any fundamental news flow to help drive his trading decisions. Some techniques that are mentioned and have been used by both traders include momentum divergence, fibonacci confluence and Elliot wave scenario analysis. Finally, Kuda mentions that the cyclical headwinds for the USD are strong currently and that he looking for a bearish move from DXY into year end To learn more about OPTIONS INSIGHT please visit www.options-insight.com or email enquiries@options-insight.com NONE OF THE MATERIAL IN THIS PODCAST SHOULD BE CONSIDERED AS INVESTMENT ADVISE, IT IS FOR INFORMATIONAL AND ENTERTAINMENT PURPOSES ONLY. ALWAYS CONSULT A REGISTERED INVESTMENT PROFESSIONAL BEFORE MAKING INVESTMENT DECISIONS. THE VIEWS AND OPINIONS EXPRESSED ON TRADER CHATS ARE THOSE OF THE PARTICIPANTS AND DO NOT NECESSARILY REFLECT THOSE OF THE HOST. OPTIONS INSIGHT OR IMRAN LAKHA SHALL NOT BE LIABLE FROM LOSSES RESULTING FROM INVESTMENT DECISIONS BASED ON INFORMATION OR VIEWPOINTS PRESENTED ON TRADER CHATS.
Elyssa Friedland is the author of four novels and a forthcoming picture book. She attended Yale University, where she served as managing editor of the Yale Daily News, and is a graduate of Columbia Law School. She worked as an associate at a major firm before turning to writing full-time. Elyssa currently teaches creative writing at Yale. Her work has been published in The Washington Post, McSweeney's, LitHub, POPSUGAR, RealSimple.com, Bustle, Modern Bride, New York magazine, Columbia Journalism Review, CBS MarketWatch.com, Yale Alumni Magazine and more. Elyssa resides in New York City with her husband and three young children. In this episode, we chat about Elyssa's latest book: Last Summer At The Golden Hotel. In its heyday, The Golden Hotel was the crown jewel of the hotter-than-hot Catskills vacation scene. For more than sixty years, the Goldman and Weingold families – best friends and business partners – have presided over this glamorous resort which served as a second home for well-heeled guests and celebrities. But the Catskills are not what they used to be – and neither is the relationship between the Goldmans and the Weingolds. As the facilities and management begin to fall apart, a tempting offer to sell forces the two families together again to make a heart-wrenching decision. Can they save their beloved Golden or is it too late? You can follow Elyssa here. You can purchase Elyssa's book here. Click here to purchase tickets to my Zoom event with author Nadia Hashimi in conjunction with the Jewish Public Library.
This week Harry sits down with Vangelis Vergetis, the co-founder and co-executive director of Intelligencia, a startup that uses big data and machine learning to help pharmaceutical companies make better decisions throughout the drug development process. Vergetis argues that if you put a group of pharma executives in a conference room, then add an extra chair for a machine-learning system, the whole group ends up smarter—and able to make more accurate predictions about which drug candidates will succeed and which will fail.Bringing better analytics into the pharma industry has been an uphill battle, Vergetis says. One survey by McKinsey, his former employer, showed that financial services companies were the most likely to adopt AI and machine learning tools; the least likely were the building and construction trades. But just one rung up from the bottom was healthcare and pharmaceuticals. "The impact that AI could have on health care is "enormous," Vergetis says. "It's in the trillions. But in terms of AI adoption, we are right above construction—and no offense to construction, but it's not the most innovative industry."But with the proper data, machine learning algorithms can help drug makers form far more accurate predictions about the probability that a new drug will perform well in Phase I clinical trials, or whether a drug that's succeeded in Phase I should be advanced to Phase II. "For years we've seen the productivity of R&D declining in our space in pharma and biotech, and I refuse to accept that," Vergetis says. "In the era of a lot of data becoming available, in the era of us being able to use techniques like machine learning to do something with that data, there's gotta be a way to reverse that trend."Please rate and review MoneyBall Medicine on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:• Launch the “Podcasts” app on your device. If you can't find this app, swipe all the way to the left on your home screen until you're on the Search page. Tap the search field at the top and type in “Podcasts.” Apple's Podcasts app should show up in the search results.• Tap the Podcasts app icon, and after it opens, tap the Search field at the top, or the little magnifying glass icon in the lower right corner.• Type MoneyBall Medicine into the search field and press the Search button.• In the search results, click on the MoneyBall Medicine logo.• On the next page, scroll down until you see the Ratings & Reviews section. Below that, you'll see five purple stars.• Tap the stars to rate the show.• Scroll down a little farther. You'll see a purple link saying “Write a Review.”• On the next screen, you'll see the stars again. You can tap them to leave a rating if you haven't already.• In the Title field, type a summary for your review.• In the Review field, type your review.• When you're finished, click Send.• That's it, you're done. Thanks!Full TranscriptMoneyBall Medicine - Vangelis Vergetis TranscriptHarry Glorikian: I'm Harry Glorikian, and this is MoneyBall Medicine, the interview podcast where we meet researchers, entrepreneurs, and physicians who are using the power of data to improve patient health and make healthcare delivery more efficient. You can think of each episode as a new chapter in the never-ending audio version of my 2017 book, “MoneyBall Medicine: Thriving in the New Data-Driven Healthcare Market.” If you like the show, please do us a favor and leave a rating and review at Apple Podcasts. Harry Glorikian: My guest today is Vangelis Vergetis, the co-founder and co-executive director of Intelligencia. It's big-data analytics startup focused on the pharmaceutical industry. And the argument Vergetis makes to potential clients is that you can take any group of 10 drug development experts in a conference room, and make them a lot smarter by adding an eleventh chair for a machine-learning system.Of course, there's always an art to deciding which drug candidates should advance to clinical trials; which Phase 1 trials should advance to Phase 2; and so on. Decisions that like are risky and expensive, and you can't make them without having a lot of old-fashioned experience and instinct around the table.Even so, sometimes the experts are biased and the experience doesn't apply. And there's only so much data they humans can keep in their heads. And let's be honest: if decision makers at the big drug companies were that smart and talented, they'd have more home runs and fewer strikeouts.Vergetis argues that we've got the historical data and the computing power today to make far more informed predictions about which drug programs to push forward. And if more drug companies used those tools, he thinks, it might reverse the decline in R&D productivity.In the conversation you're about to hear, we talked about how Vergetis and his co-founder Dimitrios Skaltsas started Intelligencia; how they built their own datasets; how they work with clients; and why it is that he and I think a lot alike—to the point of using the same MoneyBall metaphor when we talk about transforming drug discovery and healthcare.So here's my conversation with Vangelis Vergetis.Harry Glorikian: Vangelis, welcome to the show. Vangelis Vergetis: Thank you. Very good to be here. Harry Glorikian: You know, it's interesting. I was looking at the company and looking at what you guys are doing. And I, I've probably talked to, I don't know, close to 70 experts in different areas of healthcare, drug discovery, computer science you know. Out of all those people, I honestly think you and your company Intelligencia might be the most exact reflection of the argument I was making in my 2017 book MoneyBall Medicine. In fact, I actually think you used the MoneyBall metaphor in your own talks. So I want to start out with having you explain the parallels between your company and what Billy Bean did at the Oakland A's.Vangelis Vergetis: it's very funny. You say this Harry, by the way when we started the company, what is it, three, three and a half years ago now, we had a slide actually. You know, baseball did it in the nineties. Is it about time that healthcare does the same? and going through the MoneyBall analogy. So look, the quick or the easiest way to explain it, right, it's the analogy of how do you pick baseball players and build a winning baseball team and how do you pick drug candidates and development programs and build a winning pipeline?So, you know, back in the day, what baseball did is a lot of experts in a big conference room. And these guys have watched—and I say guys, because yeah, they were primarily guys—they watched, you know, thousands of baseball games each, and they had their own perspectives and views and biases and experience in terms of what's you know, who's a good baseball player and who's not, and who they want on the team and how do they complement each other.And that's how they built a baseball team and, you know, the, the kid comes in and, you know, the chubby kid, I think Jonah Hill, right, and tells Brad Pitt, or Billy Bean in real life, I think we can do this differently. And that's a little bit of the analogy here, look, it's not a perfect analogy, like everything. Right? But the analogy here is how do you go from when you design a clinical trial or when you think about the pros and cons and the risks of a development program, how do you take that conversation from a room full of people, the oncology PhD, the statistician, the person who's developed dozens of drugs in the past and so on, and you inject some data science and machine learning capability into that conversation. There is art in drug development. We'll be the first one to acknowledge that, the same way there's art in baseball. So I would not expect that you know, that room gets replaced by a machine in any shape or form and definitely not in the, in the near or even medium, medium future. But the idea is, you know, if you have 10 people in the room, can you pull up an 11th chair, have the machine learning algorithms, sit at a chair. And provide a very unbiased data-driven perspective into that conversation. So that, that, that's what we do. Harry Glorikian: So we're going to, I want to get into some of the details, but I want to step back and fill in some history here for the people and how Intelligencia got started. If I'm not mistaken, your background is computer science, not biology. Right? Okay. And your co-founder Dimitrios [Skaltsas] is trained in law. So you both spent times at McKinsey, is that where you guys met? Vangelis Vergetis: So we, it's a, it's a good, good both of those good points. So you have a former lawyer—which we don't hold against him, we still like him very, very much—and a former computer scientist or electrical engineer who are running a company in drug development. Like, how does that work? A couple of things. As you, as you rightly pointed out, we met at McKinsey. We were both part of the healthcare practice there. Initially I was in the, in the US. Dimitrios was in Europe. We met 10 years before starting a company just running client projects together. We kept in touch over the years. And at some point, I think it was 2014, Dimitrios moved to New York, moved to the US with McKinsey and took some AI responsibilities. McKinsey was doing some internal AI. I think it was called McKinsey Solutions or something like that.So we became closer when he was in New York. We were both in healthcare for the better part of the last a decade, and we were looking for, what is the opportunity? You know, what's the area in, in drug development or frankly in pharma more broadly, where we believe we can have an impact.And it was partly us thinking through different areas. It was frankly customers or clients coming. We were both at McKinsey and we have done this study over and over again. Right. How do you design a better clinical trial? We had, I had done this, I don't know, two dozen times, maybe more. And clients kept asking McKinsey or us, Hey guys, you know, we understand how you do this and you do it very well, but are you using machine learning? Are you using data? And after saying no for about, you know, 50 times we said, okay, we should stop saying no and just go build the damn business. So here we are. Harry Glorikian: Yeah, no, I know that. I mean, from my days having Scientia Advisors, they ask over and over and over again and you keep it. It's great profitability by the way, but because you sort of know the answer. But you couldn't have picked a harder space though this is not a trivial exercise, especially if you go back to 2014 where some of the data was not even truly available or not in a format or not labeled or, or, or, or, or, or—right, to where we are today.Vangelis Vergetis: We started the company basically in 2018. The biggest challenge, I think you, you, you rightly put it, it's getting your hands on the right data. You need to answer the question you want to answer. And we took that view by the way. And some people go differently and I'll have my biases, my own biases, I'll admit. In a lot of places, what we've seen, particularly some big pharma, because they're sitting on a vast amount of their own data, but whether it's CTMS data or whatever clinical trial data they have, and the exercise they mentally do is okay, I have all this data. What questions can I answer? What can I do? And there's a lot of value there. We can answer a lot of good questions. But sometimes the question you ask needs more data than what you have, and you're kind of force-fitting it a little bit and say, yeah. Okay. But maybe I can answer most of it. Well, not really. So we flipped it. We asked the question, the question is, what is the risk of this clinical development program or the flip side of it? How likely is it that this clinical program or this drug will eventually reach a patient, will eventually receive approval by the FDA and be used by a patient. Then we went there. We said, okay, if that's the question, what data do we need to answer that question? Some of it very easily accessible. Some of it doable, but you need to build data pipelines. You need to clean it up. It's a little bit messy, whatever. Some of it doesn't exist. We've got to build it from scratch. So if you do it the other way and say, what do I have, you'll ignore that piece that says, doesn't exist. I have to build this from scratch. You're going to try to solve the problem with the other stuff.And then you realize it's not enough. So we asked the question and then we went very systematically to get all the data we needed to train the machine learning models. To answer that question. Harry Glorikian: Sounds like a consulting approach. What do we need to fill the two by two? So I totally get it. What are the biggest limitations you see right now from pharma's current method of assessing clinical trial risk? Vangelis Vergetis: Yeah, there is, there's a few and some are bigger. Some are smaller. And it's, it's hard to paint the whole industry with a broad brush, but there are some technical limitations that everybody has like as humanity, as a scientific community. Do we really understand drug biology or biology? Really well, human biology. I don't know. We understand it well enough, but from the, total knowledge, biological knowledge, we probably know this much. That's one challenge and it's a technical challenge or a scientific challenge.A technical challenge is and I think you put your finger on it, data availability. But it goes beyond, can I get my hands on the right data? Is it curated in a particular way? Is it well annotated? Is it labeled? Does it have the same quality? Is it consistent? You know, I, I take data from this genomic database. I pick data from that genomic database. Are they structured the same way? Kind of combine them or how much work do I need to do combine them. Now, it's a solvable problem. You know, the understanding of biology. It is solvable over time, but not immediate. The technical aspect of, can I make data consistent, solvable, is incredibly painful, and very few people have the patience for it or are willing to, I mean, we've killed a lot of brain cells pulling that data together, but we've done it.And then there's a third group, I think, of challenges that I would put in the broader, you know, cultural umbrella. You know, there is the, what I call the “every drug is unique” syndrome. A lot of people out there will say, well, you know, there's so many differences between drugs and programs and all that, there's no way you can use machine learning to estimate the success of this drug. Most of it not true, actually there's that syndrome there is the—and it's actually very interesting in the pharma industry, particularly, or in biotech—here is the “I want to see very quick results. I want to try this AI thing, whatever this AI thing is. Let me try it for two, three months. Show something quick. If I can show us a quick win. Great. If not, I'll throw it away. I don't have the patience for it.” And this is an industry that will easily not even think about investing 10 years and a billion dollars to develop, forget clinical, in the preclinical world, to discover a new target or a new molecule that could cure Alzheimer's or pancreatic cancer or something. So we are an industry that we're very much into putting an enormous amount of resources, time, patience, to discover a drug, but when it comes to incorporating an AI system methodology model that may help us tremendously, we are impatient. “Three months. Let's see what I can do. Oh, no results? Throw it away. I'll never see it again.” And there's a little bit about this, I think in all fairness, companies are getting better. So most of the large pharmas, they have now chief digital officers or chief innovation officers with a whole structure underneath them and mandates and all that. So I don't want to be too, too pessimistic here. Right. There's a lot of effort. And I think the industry at the very least has acknowledged they have a cultural barrier that needs to be overcome. But I don't think we're fully there in how we overcome it. But we're making progress, Harry Glorikian: But it's interesting, right. I look at existing big pharma and the lumbering ways they sort of move forward in fits and starts. And, you know, do I want to disrupt my kingdom to implement this thing? I mean, there's, there's a lot of human psychology that's involved here and a lack of understanding right. Of fully understanding this and what it can do for them in different areas.Then I look at the startups that literally from day one are totally data purpose-built right. Everything they're looking at is, “What's the data. How do I label it? Where are we going to use it? How do I manipulate it?” I mean, literally it is from the ground up. And I always think to myself sooner or later on my bet is that the startup is going to out maneuver the big guy.I mean, Google started from as a purpose-built entity and it's, you know, it, it outstrips most of its competitors and reshapes industries. I always think it's harder to take an existing entity and reprogram its DNA rather than have a predesigned piece of DNA from, from day one. Vangelis Vergetis: Harry it's an incredibly interesting thought, and I don't have an answer for it. And only time will tell. I would expect some pharma companies, whether we're talking about big pharma, you know, the big 10 or, you know, the, the massive guys or some of the, you know, in our industry, it's very funny, like a mid-sized biotech, it's still a $20 billion business. So, but I would bet some of them, to use your words, will adapt, will reprogram their DNA to some degree, a little bit painfully, it's going to be a little bit slow or they're going to have some false starts, but somehow they'll, they'll get there. Some others will just buy and we've seen this in the industry, right? So, interesting startup, I'll just buy them. And a few of these have already happened. We've seen, what is it, Flatiron was bought by, I believe it was Roche, right? Yes. There's many other similar examples. That's probably one of them more, the bigger ones, the more prominent ones. So I would expect this reprogramming of DNA will not fully happen organically. Some of it will happen by big pharma realizing, “Yeah. We need to play, you know, if we, if we're not a data company in a few years from now, we're, we'll be nowhere, right? How do we get there? Let's get our stuff stuff organized, and maybe we'll go make a couple of select acquisitions and eventually we'll get there.”So I think all of these flavors will materialize in some shape or form, and some companies will lose. Some companies will do the investments and put the, hire the right people and make the right acquisitions and, and, and they will continue to grow. Harry Glorikian: Yeah. And I look at it as an analogy to like, if I look at say JP Morgan or Goldman Sachs, I mean, they are the amount of money that they're spending trying to transition to this new capability is, we're not spending the same amount of money in pharma for sure. Right? Not even close. Vangelis Vergetis: I don't know the actual amount of money, because I haven't done the analysis. I haven't seen numbers. But my former employer, McKinsey, has done quite a bit of work. I think it was MGI. So MGI is McKinsey's think tank, it's the McKinsey Global Institute. They had done a lot of work on this. And I remember seeing a chart that I thought was, was mind boggling. Areas that are way ahead in AI, or industries that are way ahead in AI, I would say financial services. So the Goldmans and JP Morgans and Morgan Stanleys and some of the world's high-tech of course, and a few others. Who's at the bottom? I think it was like building materials or construction, which I get it. Second from the bottom? Health care. It was literally that bad.Well, it's true. If you look at the data, the, the sad thing for me the part that we need to think about as an industry, the promise or the impact that AI can have in healthcare. And I'm talking about healthcare more broadly now, including hospitals and payers, not just drug development or a pharma. But the impact that AI can have on health care is enormous. It's in the trillions. But in terms of AI adoption, we are right above construction and no offense to the construction, but it's not the most innovative industry.Harry Glorikian: So, this is why I love investing in this area, because it's such an incredible, I mean, some of the other opportunities are still incredible, don't misunderstand me, but this is at its nascent stage in my mind, where the opportunity is dramatic to sort of move the ball forward. Okay. Which brings me to the next question, which is, you know, and you don't have to name any names or anything like that. Walk us through sort of a real world example of how you help a client in practice. Vangelis Vergetis: Ooh. Maybe I'll give you two examples. You asked for one, I'll give you two. Actually I'm gonna give you more, but let, let's start with that. So where do we typically you know, we work with several flavors of customers, right? So we, we serve some of the largest, you know, top five big pharma companies we serve. Some of the smaller, even private biotechs. And we serve a bunch of the mid sized biotechs or midsize pharma companies. One area that that comes or one example is a specific program. So I'll, I'll pick on an actual example. So a specific, it's a phase two asset on a phase two program. It was a combination program, I believe for pancreatic [cancer] that our client was running. It was the phase two. It had been going on for about a year, I want to say. So it was in the middle of phase two, they were starting to see some interim results.They hadn't published anything. They were starting to see some interim results, but they were still waiting for the phase three to complete. And then there were basically three questions with increasing degrees of difficulty, if you will. Question number one, how likely is it that this program, so this combo, so our molecule with, I believe it was chemo for pancreatic cancer, will eventually reach a patient, will eventually receive regulatory approval by the FDA? That was question number one, which is our bread and butter. This is what our algorithms do. I'll make up the number now. It's a, you know, 13%, which by the way, for pancreatic cancer, phase two, that's not bad. The second question was, okay, now let's start thinking forward. So at the end of phase two, we're able to show ABC, how does that probability change? Because given the interim results we've seen, we have pretty decent conviction we'll be able to show something in that range when it comes to OS or ORR or whatever end points we're measuring. What will our probability to change to. It's 13 now, will it go to 20 or we'll go to zero?What if we managed to show something better or something worse. So in that sense, we're trying to calibrate and say, based on what we show at the end of phase two, how do we make a decision? Should we go to phase three or not? Is it too risky still? And it needs to be derisked further? Or are we comfortable with the risk we're taking, and we're willing to write a, you know, $200 million check to run a phase three program. So we did the simulations, if you will, of the analysis to say, based on what your phase two will show, here's what you should expect your risk to be at the beginning of phase three. That was the second layer. The third layer went even a step further and said, okay, let's assume we are now comfortable moving forward. So the risk is within what we're willing to take given the size of the prize, right? Because if you do get this drug approved, we estimate an enormous commercial potential. So we're willing to take significant risks here. How should we do this? So help us think through how different choices for continuing our development program affect our chances for approval.For example, should we run a smaller phase two-B and then two large phase three trials. Should we scrap the phase two-B and go straight to pivotal phase three and do a much larger trial. And there are different trade offs there that have to do with costs, time and risk. We help them think through from the middle of phase two where they are today, how likely is it that they go approved? How will that evolve once they publish results? And if they decide to move forward, what the best path forward is from a risk point of view. So that's one example. Well, I'll spare you. The second one, I spent too long on the first one. Harry Glorikian: So you've written this machine learning model, right? So, and I want to say there's at least a hundred factors, clinical trial, design outcomes, regulatory process, you know, the biology itself that you mentioned, right? The history. You have to train a model like that. Where did you get the data to train this complex model?Vangelis Vergetis: There's no single. So I wish there was. So we we've been to now dozens of data sources. So I think what I said at the very beginning, right? Some of the data was easy to get. So for example, there is a bunch of data that clinical trials.gov has. Of course we have that, and everybody else has that. That's very easy to get right. Valuable, but very easy to get, which is good.There are some data where you need to, it's publicly available, but you need to spend a lot of time cleaning up and curating. So think of genomic databases, whether it's TCGA or GTX, or, you know, dozens of other genomic databases that needs a lot of analysis and lot of processing and a lot of cleanup before you create features out of that data to put in your machine learning algorithms. So that's a, probably a second group.And a third group that goes back to the point initially that, you know, not all the data you want to answer, the question, is available. So you have to build it yourself. We built it ourselves. So an example, there is clinical trial outcome. So there is no to our knowledge and we looked hard. There is no data you can buy that has in an incredibly consistent, systematic way, all the outcomes of clinical trials in a particular therapeutic area for the last 20 years. So let's say, I mean, I mean, oncology, I'll give you an example. There's been a few thousand trials in the last 20 years. Let's say since 2000, we need to know every end point that this trial measured. How many patients were in each patient cohort or in each arm of the trial. What was the value of that endpoint? What ORR did they achieve? What OS did they achieve? Whatever. When was that? Because sometimes we say, OS, Overall Survival, well, was it measured at six months or 12 months. One layer more of specificity of exactly how the end point was captured. And then you need the number. How many patients survived at the six month mark or whatever it is. So there's all that, all that stuff that you need, and then you need it, not just for the trial or the program you're assessing, that's easy to do, right? It's one program. We can get it from the, from the pharma company themselves. We need it for every single trial that has ever succeeded in the past. And for every single trial that has ever failed. That's how you train a machine learning algorithm. That was very painful. We have a whole team in Athens, actually. So if the name didn't give it up, I'm from Greece originally. I've been in New York for like 25 years now, but I'm from Greece originally. So a lot of the team is based in Greece and part of that team, they're a very highly educated team and, you know, PhDs in biology, oncology, immunology, pharmacology, all the ologies. And that team curates in an incredibly systematic way all that data, before our data engineers and before our machine learning team can take over to build models. Right? So to answer your question in a short way, dozens of data sources, some easy to get some much harder with a lot of processing. And some we had to just create from scratch. Harry Glorikian: I mean, that was just thinking about what you were saying. That, that last piece we were just discussing. I mean, I can imagine to hospitals and to doctors that would be—if you could put that into interesting matrix, they could get an interesting view into these drugs instead of memorizing off the top of their head. It's it, you know, I always find all these discussions with companies that have data. I can think of five other things to do easily. Once you've got the data source. Vangelis Vergetis: We've been discussing internally, both as a team, but also with our advisors and even our customers at this point where they're coming to us on the saying, Hey guys, that's amazing what you have. We'll pay you money. Can we now do this. Can we now do that. And some of that we would love to do and we're entertaining it. Some of it, you know, we, we're still a growing company or, you know, there's 40 of us total in the company. You also don't want to get distracted by too many shiny objects. You know, find the right shiny object and focus on a couple of them, but not too many.So for some of them, we'll say, look, we could do it. We can, we don't have the time. We don't have the bandwidth today. Maybe later. For some of them we would say, yeah, that's incredibly interesting. And we were planning to go there anyway. Let's do it faster together. So we're discussing with one of our customers today about building something that goes beyond risk and starts thinking about the commercial implications of what happens when a drug actually gets approved. So it's not just predicting approval, but can you predict anything in the commercial space, whether that's revenue reimbursement market shares and so on. [musical transition]Harry Glorikian: I want to pause the conversation for a minute to make a quick request. If you're a fan of MoneyBall Medicine, you know that we've published dozens of interviews with leading scientists and entrepreneurs exploring the boundaries of data-driven healthcare and research. And you can listen to all of those episodes for free at Apple Podcasts, or at my website glorikian.com, or wherever you get your podcasts.There's one small thing you can do in return, and that's to leave a rating and a review of the show on Apple Podcasts. It's one of the best ways to help other listeners find and follow the show.If you've never posted a review or a rating, it's easy. All you have to do is open the Apple Podcasts app on your smartphone, search for MoneyBall Medicine, and scroll down to the Ratings & Reviews section. Tap the stars to rate the show, and then tap the link that says Write a Review to leave your comments. It'll only take a minute, but it'll help us out immensely. Thank you! And now back to the show.[musical transition]Harry Glorikian: If you have it to say, what is your defensible advantage, your special sauce? Like, what is it that you're doing for pharma that they can't somehow reproduce for themselves? Vangelis Vergetis: That's a great question, Harry. I will say a couple of things. Some are softer, some are harder. On the softer side, and probably more important by the way, is the persistent focus you know, unrelenting pursuit of what we're here to build. In a larger company, it's too easy to lose focus, budgets, get cut, people, get reassigned, promoted, change departments, move.So it's very hard to get a team together to focus on something for an extended period of time and only do that. So that's probably one thing when, when you compare it to a larger pharma company, right. The, the second thing would be. Bringing together people with very different expertise and experiences.So if you go to our office in Athens—and not the last year, given all the mess, we're all living in with coronavirus—but if you go to our office in Athens either before that, or hopefully very soon, it's a room and you have, you know, the data scientist is sitting here. The oncology PhD is right next to her. Right across is the data engineer. The drug developer is sitting over there. The statistician is there. So it's literally having all those people in one room or in, you know, a series of rooms in one floor, let's say, where they work together on the same topic. And it sounds a little bit mundane and it sounds a little trite, but it makes a difference for the biologist to be listening into, as these computer scientists or data scientists are talking about their models. And I'm sitting here entering all the biological clinical data from this New England Journal of Medicine article that I'm reading. I actually understand how they use it and I can offer an idea. I can say, Hey, actually, I can capture it in a way that will help you guys given what you're discussing. So all those things help.So that's the second element, which is a team of you know, we use diversity in many ways. So a diverse team, not just in the, in the racial or, or, you know any other perspective, but also in experiences and backgrounds. And the third one, which is the more technical one. It's the data we actually do have. It does take an enormous amount of time, a lot of people, an enormous amount of effort to actually build and create the data cube that we have. Nobody else has this. It's incredibly painful but we've done it. So that does set us apart. There are companies out there that are trying to solve the same or very similar questions or answer very similar questions based on a much more limited set of data. And they fall short. They're okay. But they will short of, of our predictive power. Not because they're not doing anything wrong, not because they're not good data scientists, all of those things are fine. They just don't have the data we have. Harry Glorikian: And so that brings me to that next question. In all of these models, there there's little issues, fraught throughout the process…Vangelis Vergetis: Oh my God. There's so many. And some of them are longer. Harry Glorikian: Many, right, that you have to think through. Right. That's why whenever somebody says, oh yeah, I've got the perfect answer, I'm like, it's impossible. Perfect? No, right. So what is the accuracy? I mean, if you said your predictive algorithm, how do you, how do you, first of all, what do you compare it against? And then let me just pick and say, if I will, putting it against a traditional way of making decisions. How do you measure your accuracy? And then do you go back and look at real world evidence versus the system?Vangelis Vergetis: Yeah. So we we've done a few things that are very interesting. There is a standard metric for machine learning. So let's not get too technical or I don't know how technical your audience is. But there's the AUC, which is Area Under the Curve, which means the area under the ROC curve…whatever, there's a metric called AUC. It's pretty much a number between 0.5 and 1. I mean, technically it could be low as 0.5, but that's a silly, so it's a number between 0.5 and 1. The higher it is the more predictive your model is. We are in the high eighties, low nineties, which is, which is incredibly predictive for a problem this nuanced and this hard. If you do image recognition and you use deep learning for image recognition, you get close to 0.999.These are very different problems. So with a standard AUC metric, we score very highly and we've compared that with what others have published in literature. And we are higher than at least what we've seen published. But by others then you do obvious things, right? So, so what do you do, you say, okay, let me take an example of hundred trials or a hundred programs for which my algorithm predicts that they are, let's say in the 20 to 30% success.All right. So my algorithm says all of these hundred fall in the 20 to 30% range. Now let me follow them over time and see what happens. What do you want? Ideally you want 25% of them to succeed, you know, somewhere in the middle. And it most often that's what happens. So when we say zero to 10 on average, let's say 7% of them succeed.When we say 10 to 30 on average, 22% succeed. When we say 30 to 50 on average, 39% succeed. So you do that on a large amount of trials, and then you start gaining confidence that dammit, what this algorithm or what this model is telling me eventually reflects reality. Now, of course, these are averages, right? So there will be trials for which you say 5% and they succeed. Now the obvious thing there to say is, and what we like about this actually, it's a true probability measure. So 5%, what does it mean? Right. I don't need to tell you. 5% means one out of 20 should succeed. Otherwise it's not 5%. If every, if every trial for which you say 5% fails, well, it's not 5%. It's zero. So if you say 5%, you should have one out of 20 succeeding. So you want to see that and you do see that, which is good. Similarly, if you go to a drug developer and you say, you know, 80%, they've never heard a higher number in drug development. Those numbers are rarely exist. So 80% to a drug developer means success. Well, no, it means two out of 10 will fail. Right. So you want to see that you run statistical checks, like the bins that I mentioned, Brier scores, AUC. So you run a bunch of statistical tests and you get very high predictive power. Look, I'll summarize it like this in the beginning of phase two, which is pretty early in drug development, right? So you still have, five, six years of, of development left ahead of you. The predictive power of our algorithms are about 90%. So we can tell you with 90% confidence that the probability that we give you is the right probability. When we tell you 20 it's 20, when we tell you it's 60 it's 60, we don't give you a one-zero estimate, we'll give you a number. And we're 90% confident on that number. Harry Glorikian: That's a pretty bold statement. So I'll, you know, let's, let's think about it here though. Right? So two things, right? Mof this stuff at some point has to be explainable, which is typically an issue in machine learning is the explainability of the model. So how have you designed it in a way where you can be like, yeah. Okay. This is why I got to this answer. Vangelis Vergetis: It's a great point. I wish we could do exactly what you said. But we can come close. So a couple of things, culturally, and for the right reasons, if you go, eh in front of the EVP of R&D in a large pharma company or the head of portfolio, whatever, and you tell them the answer is 42, they're going to throw you out of the room. They want to know, “Where does the 42 coming from? Why are you telling me this? Give me some, I need to know what can I do about it? I need to understand it.” Which it's very human and it's also the right thing. So we run, by design, we run machine learning models that are explainable. And there is explainability work being done in the academic community even for, let's say deep learning models, which are still much less explainable than a random forest or a KNN or, or something like that. So we run explainable machine learning algorithms. We spend a lot of time on explainability.And if one goes on our platform or uses our software, if you look at the number and then you literally click on a thing that says, explain to me why, and you see all the features that contribute to that answer and how important each feature is. So the reason I'm telling you that your probability is 42 is because on the positive side—and I'm making it up for a second, right?—a target that's a gene that's highly expressed in the tissue. You're going after let's say the lung or, or, or the breast or the liver or whatever it is. The cancerous tissue versus the healthy tissue. You've designed a very good trial with the right endpoints. It's well sized with the, the amount of patients you're putting in. You have a biomarker, which is a good thing, blah, blah. And maybe we'll also say on the negative side, by the way you know, as a company, you may not have that much experience in this particular disease area. So I'm dinging you a little bit. And the regulator hasn't said anything special about you, you haven't received any breakthrough or accelerated approval or anything like that. The gene you picked is highly expressed, but there has been zero, it's a first in class indication. If it's a first in class molecule that has been no approvals in the past of that target. So that tells me it's a little more risky than the 20th PD1 in the market. So it will give you all that.And people can do two things with that. One, and perhaps less important, but important. It gives them confidence that they understand why the machine is telling something. They can wrap their head around it and they can get more confident, even though I can tell you, yeah, I've run the statistics and the predictive power is 90%, you want to be able to understand it. You want to touch it. You want to feel it. You want to understand why? So it does that. The second thing it does is you might be able to do something about it. So back to the simulation, right? What do we help our customer? I can maybe assess for you what the difference will be if you use the biomarker versus not. If you have a larger trial with another arm or not. If you use this endpoint versus that endpoint. So you may be able to say, okay, I understand that the probability is 42%, but if I change these three things, can I make it 50? And those eight points in PTRS and probability of approval are massive in terms of NPV or whatever, evaluation you use. Harry Glorikian: That was going to be what I would, one of my next questions is, so you're doing all this. And so do they always act on the data or in some cases, do they make a different decision based on what the model said?Vangelis Vergetis: Both. So, and, and the model is not a black or white model, right? It's not going to tell you do this, or don't do this, or move to phase three or don't move to phase two. I'll give you an example, if you are in oncology if I tell you that this asset has a 80% probability of success versus 60% probably of success. It probably doesn't matter. You're going to move ahead. Anyway. It's high enough and the risk is too low. You might as well do it. So sometimes, you know, at the extreme, it may not make a big difference whether if I tell you it's a 5% probability versus a 3% probability, do you actually care? It's pretty damn low. Now in a lot of cases though, they, they fall somewhere in the gray zone and this is where a lot of other factors come in. So what do we think of that commercial potential. What are our competitors doing? How does it fit broadly with the rest of our pipeline and all of the other assets, both approved and the programs we have out there. So there's a lot of other considerations that go into making a decision, whether I move to phase three or whether I de-risk it, or you know, what I do.But for the most part what we've seen is our customers act on the information. They are able to take that information, enhance their decision-making process and make at the end of the day, a better decision either because they stopped something they should have stopped, they progressed something they should have progressed, or they designed the trial a little bit differently, or they you know, put a program in place that maximizes the potential of the asset they have in their pipeline.So all of those things happen. The last thing I'll say, Harry, and this one is where we see a lot of action as well, is in business development. So while most of our, we're not, most actually, a lot of our work is in R&D. So pharma companies developing their own molecules. We see two more areas where this approach is gaining a lot of steam.Actually one is business development. So as I'm looking not for my own pipeline, but as I'm looking to identify or attract programs out there that I may want to go buy or partner with or in-license and do all sorts of things. So we work with a customer early on phase one and they said, you know, what are the innovative, if you will, first-in-class assets in phase one, so risky stuff for a particular indication, RA or IBD or Parkinson's or pancreatic cancer, whatever it is for the indication that I care about, what are the phase one programs out there that one are scientifically innovative. So I don't want the me-too drugs. I don't want the 21st PD1 in the market, but I want something innovative. And two, can I see that list ranked from a risk point of view or from an attractiveness point of view, you know, some have a 2% chance of approval. Some have a 20% chance of approval. Well, I want to talk about the 20.Yes. And we've, we've helped customers identify molecules and programs like that, where they go and they have a conversation with a biotech in south San Francisco or in Zurich, Switzerland, or in Tokyo or wherever, with that biotech about in-licensing or partnerships or acquisitions or whatever it is. So with that we've seen quite a bit of action.Harry Glorikian: Machine learning takes hold in drug development. What's the big picture outcome. What do you think, you know, how do you think…is it the Intelligencias of the world that are going to change the dynamic? Is it going to be the companies themselves? You know, I believe this is going to have a profound impact on how things are done and what goes forward. Vangelis Vergetis: Here's what I'd love to see Harry, I'd love to see… For years we've seen—and there's some change recently—we've seen the productivity of R&D declining in our space in pharma and biotech. I refuse to accept that. In the era of a lot of data becoming available, in the era of us being able to use techniques like machine learning, to do something with that data, there's gotta be a way to reverse that trend, that declining trend in R&D productivity, and see it going up again. Who benefits? Patients, where they see better drugs reaching them faster and curing disease. And of course the broader community of pharma companies, biotechnology companies and so on. So the, the big picture is I'd love to see the productivity of R&D in our space increase.And AI, whether it's Intelligencia—and I'm hoping, and I'm sure we will, but there we'll be honest there and that's great. We all need to think through, you know, how do we reverse the trend? So in, in pharma or, or in drug development, I see that as the big picture you know, how do I pick the winners? How do I invest behind the winners? How do I make sure I don't create any, you know, biases in that way where I miss some of the drugs that would have existed had I made the right choice and make my R&D dollars and R&D hours and effort much more productive at the end of the day for delivering drugs to people that need them.Harry Glorikian: So I saw you were quoted in a report from a law firm called Orrick that I liked. I think you were paraphrasing Derek Lowe from Novartis where you said, “It is not that AI will replace drug developers. It's that the drug developers who use AI will replace those who don't.” And coming back to the beginning, you know, do you think this is happening across the board in all businesses? Whether it's on experimental drugs or winning baseball teams.Vangelis Vergetis: Yeah. So it's a great question. Look, I think it is happening across all industries but each industry is different. So I think the scale of impact and the scale of adoption to date are very different across industries.We talked about, you know, we used construction as an example earlier. If you think about construction, the impact that AI will have a construction, it's not zero. I know one, a friend and a mentor runs a cement business and their AI. I'm not joking. They're using AI in cement production to make it more environmentally friendly, increased productivity, increased—he'll do all those things. So yeah, there will be impact. But it's going to be less in construction and building materials than it is in healthcare. Or it's going to be built different in, in, in financial services, let's say that, than it is in travel and tourism. Again there are opportunities for machine learning in travel and tourism. Probably less than in banking or financial services broadly or healthcare. To attempt to answer your question, because I don't know, I don't know what the answer is, I can tell you what my bias is or my view. Yes, it will be used across industries, but the scale of impact will be materially different, whether you're in healthcare or in travel.And two, the adoption to date is very different. All this excitement about AI and all this energy and all this impact that it can have, it's fantastic, and it will have it, but let's also be thoughtful here. I think we all are. But you need experts. There's a lot of art and a lot of things that happen. There's art in drug development. There is art in baseball, there's art, in a lot of things. There is instincts, gut feels that humans have. Some of it is bad because it's biased, but some of…he didn't miss it. There's decisions that doctors make every day as they treat patients. Forget drug development, that yes, that can be made better by AI. Maybe they can be guided by AI, but I'm not sure an AI will take over a physician's job and anytime soon.Harry Glorikian: No, I mean, I think the two together always, at least right now, will equate to step wise function up, right? The AI may not miss a piece of data that the physician didn't see. I've been with physicians where they call it and they were missing a piece of data. Had they had that data, that decision would have been different. The machine isn't going to miss that last piece, right, necessarily. And so I think the two together can be much more powerful than any one alone per se.Vangelis Vergetis: Yeah. And it varies a lot by the use case, meaning can a machine read a lung image or can it tell me if this picture is a dog or a cat? Yeah. Probably can do it better than a human or, or equally good, equally well. But in use cases that are much more intricate than, you know, reading looking at an image, whether it's building a baseball team or designing a phase three trial or anything approaching that level of complexity, the two need to come together and will for a long time to come. So I think Derek is right in that sense. Yeah. If, you know, the ones that use drug development will replace the ones that don't, but AI by itself is not going to replace everybody. Not anytime soon. Harry Glorikian: Yep. I agree. Well, listen, it was great to speak to you. I look forward to continuing our conversation, because I can see that there's many areas of overlap. And it's been great. Vangelis Vergetis: Thank you, Harry. I appreciate it. Harry Glorikian: Thank you. Vangelis Vergetis: Bye.Harry Glorikian: That's it for this week's show. You can find past episodes of MoneyBall Medicine at my website, glorikian.com, under the tab “Podcast.” And you can follow me on Twitter at hglorikian. Thanks for listening, and we'll be back soon with our next interview.
In LAST SUMMER AT GOLDEN HOTEL - acclaimed author Elyssa Friedland chronicles a family reunion for the ages when the Goldmans and the Weingolds convene for a long summer weekend at their beloved “Borscht Belt” getaway nestled in New York's Catskill mountains. With the fate of their once-luxurious resort hanging in the balance, the boomer, millennial and greatest generations jockey for power. In its heyday, The Golden Hotel was the crown jewel of the hotter-than-hot Catskills vacation scene. For more than 60 years, the Goldman and Weingold families - best friends and business partners - have presided over this glamorous getaway which served as a second home for well-heeled guests and celebrities. But the Catskills aren't what they used to be - and neither is the relationship between the Goldmans and the Weingolds. As the facilities and management begin to age and fall apart, a tempting offer to sell forces the two families together again to make a heart-wrenching decision. Can they save their beloved Golden or is it too late? Long-buried secrets emerge, new dramas and financial scandal erupt, and everyone from the traditional grandparents to the millennial grandchildren wants a say in the hotel's future. Business and pleasure clash in this fast-paced, hilarious, nostalgia-filled story, where the hotel owners rediscover the magic of a bygone era of nonstop fun even as they grapple with what may be their last resort. About the author: The author of 4 novels, ELYSSA FRIEDLAND attended Yale University, where she currently teaches creative writing, and is a graduate of Columbia Law School. Her work has been published in The Washington Post, McSweeney's, POPSUGAR, RealSimple.com, Bustle, Modern Bride, New York magazine, Columbia Journalism Review, CBS MarketWatch.com, Yale Alumni Magazine, and Your Prom. Her previous novels have been praised by People, “SkimmReads,” Cosmopolitan, Bustle, Good Housekeeping, National Geographic, Woman's Day, Woman's World, Kirkus, Publisher's Weekly, Library Journal, Booklist and more.
In LAST SUMMER AT GOLDEN HOTEL - acclaimed author Elyssa Friedland chronicles a family reunion for the ages when the Goldmans and the Weingolds convene for a long summer weekend at their beloved “Borscht Belt” getaway nestled in New York's Catskill mountains. With the fate of their once-luxurious resort hanging in the balance, the boomer, millennial and greatest generations jockey for power. In its heyday, The Golden Hotel was the crown jewel of the hotter-than-hot Catskills vacation scene. For more than 60 years, the Goldman and Weingold families - best friends and business partners - have presided over this glamorous getaway which served as a second home for well-heeled guests and celebrities. But the Catskills aren't what they used to be - and neither is the relationship between the Goldmans and the Weingolds. As the facilities and management begin to age and fall apart, a tempting offer to sell forces the two families together again to make a heart-wrenching decision. Can they save their beloved Golden or is it too late? Long-buried secrets emerge, new dramas and financial scandal erupt, and everyone from the traditional grandparents to the millennial grandchildren wants a say in the hotel's future. Business and pleasure clash in this fast-paced, hilarious, nostalgia-filled story, where the hotel owners rediscover the magic of a bygone era of nonstop fun even as they grapple with what may be their last resort. About the author: The author of 4 novels, ELYSSA FRIEDLAND attended Yale University, where she currently teaches creative writing, and is a graduate of Columbia Law School. Her work has been published in The Washington Post, McSweeney's, POPSUGAR, RealSimple.com, Bustle, Modern Bride, New York magazine, Columbia Journalism Review, CBS MarketWatch.com, Yale Alumni Magazine, and Your Prom. Her previous novels have been praised by People, “SkimmReads,” Cosmopolitan, Bustle, Good Housekeeping, National Geographic, Woman's Day, Woman's World, Kirkus, Publisher's Weekly, Library Journal, Booklist and more.
Welcome to Finance and Fury. This episode we will continue looking at the crypto markets. In particular, we focus on the regulatory frameworks that have been released by the Bank for international settlements, BIS for short. One division of the BIS - the Basel Committee on Banking Supervision - released a consultation paper this month to provide a framework to every nation's regulator of financial institutions on how to treat cryptocurrencies - Now – the Basel Committee on Banking Supervision is the world's most powerful regulator of banking standards and rules – it gets to decide what capital adequacy banks should focus on, as well as what assets should be classified as capital – if you have been listening for a while, you would have heard me mention this group – they are who APRA, who regulates superfunds and banks in Aus take their directions from So this recent release is meant to provide the framework for banks on how to treat different forms of cryptocurrency on their balance sheets - if they wish to start purchasing crypto The big question of this episode is if this is a major win for cryptocurrencies, as it was initially treated as purely based around market price reactions, or is this something that could actually damage the crypto markets through a financial system takeover? Firstly, it is important to note that this paper does not refer to crypto as a currency – such as the name cryptocurrency would imply – instead, they call them cryptoassets – implying that these are assets for banks or for the financial system to hold or trade these as assets – this off the bat could be viewed as an implied intent, where in the BIS's view, existing cryptos will never be treated as a currency in the mainstream – but I wanted to mention this as I will be using the term cryptoasset throughout most of this episode when it is in relation to this prudential paper – please forgive me in advance as cryptoassets will be mentioned a lot Another important point is that this report specifically states that central bank digital currencies will not fall under this legislative framework – which also implies that this is a serious option that they are looking at and will fall under a different legislative framework – as an actual currency, not a crypto asset – which we will come back to next week Start with the introduction to the BIS report – The BIS have noted that over the past few years, they have seen rapid growth in cryptoassets – with market capitalisation of these assets rising – sitting at an estimated $1.5 trillion But while the cryptoasset market remains small relative to the size of the global financial system – there continues to be rapid developments, with increased attention from a broad range of stakeholders – these stakeholders are some investment banks, since banks like JPM, Goldman and Citi have already launched their own crypto-focused businesses – I find it hard to believe that the BIS would view individuals as stakeholders In this report the BIS brings up the normal rage of concerns with Cryptoassets – including consumer protection, money laundering and terrorist financing, as well as their carbon footprint from the electricity usage But the big point of concern they focus on is that, quote: “The Committee is of the view that the growth of cryptoassets and related services has the potential to raise financial stability concerns and increase risks faced by banks.” In other words, crypto can be destabilising on the financial system – anything that provides some potential competition is destabilising if you are used to monopoly controls – this happens in all aspects of commerce – if you have a monopoly business operating who can fix prices and provide poor services, then a competitor appears, this is destabilising for your business practices, you will lose customers – so what to do? In most cases they simply buy out the competitor or have them shut down If banks were to start trading crypto using derivatives, then this could also pose a risk to the financial system The report also mentions that certain cryptoassets have exhibited a high degree of volatility, and could present risks for banks as exposures increases – these risks include liquidity risk; credit risk; market risk; operational risk (which include fraud and cyber risks); money laundering / terrorist financing risk; and legal and reputation risks – this basically ticks all the risk boxes beyond political/legislative risk – but to the BIS this isn't a concern, as they impose these risks on the market To that end, the BIS Committee has taken steps to address these risks through producing this legislative framework – and they first started looking at this over two years ago, back in March 2019 – where the Committee published an article on the risks associated with cryptoassets – then in December 2019, the Committee published a discussion paper seeking views of stakeholders on a range of issues related to the prudential treatment of cryptoassets – remember stakeholders are entities with direct connections to the BIS – i.e. Central Banks and megabanks It is important to note that mega banks like JPM, Goldman and Citi group are very interest in securitising crypto – anything that can be securities to make a profit off is a bonus in their eyes – remember in the mid-2000s they were creating synthetic contracts off collateral debt obligations – i.e. peoples mortgages to try and made more money than simply what the interest payments could provide to a commercial bank How does this legislative framework treat cryptocurrencies – or cryptoassets as the BIS refers to them – I won't be covering the minute details for the sake of time, as this report is 20 something pages long – but if you are interested the links will be in the show notes at financeandfury.com – or you can look up Prudential treatment of cryptoasset exposures – but I will be covering the higher level implications of this framework Cryptoassets are defined as private digital assets that depend primarily on cryptography and distributed ledger or similar technology – these digital assets are a digital representation of value, which can be used for payment or investment purposes The prudential treatment of cryptoassets has been guided by three general principles: Same risk, same activity, same treatment: a cryptoasset that provides equivalent economic functions and poses the same risks compared with a “traditional asset” should be subject to the same capital, liquidity and other requirements as the traditional asset. The prudential treatment should, however, account for any additional risks arising from cryptoasset exposures relative to traditional assets. Simplicity: The design of the prudential treatment of cryptoassets should be simple. Cryptoassets are currently a relatively small asset class for banks. As the market, technologies and related services of cryptoassets are still evolving, there is merit in starting with a simple and cautious treatment that could, in principle, be revisited in the future depending on the evolution of cryptoassets. Minimum standards: Any Committee-specified prudential treatment of cryptoassets would constitute a minimum standard for internationally active banks. Jurisdictions would be free to apply additional and/or more conservative measures if warranted. As such, jurisdictions that prohibit their banks from having any exposures to cryptoassets would be deemed compliant with a global prudential standard This is an important point – as the framework is the minimum standards that need to be applied – if a regulator wishes to go above and beyond, or even ban banks for holding crypto, that is well within their rights and would be deemed compliant In essence – what these principles do – assuming a bank is allowed to trade crypto - is break it down into groups of assets – Group 1 (broken down into A and B) and then Group 2 Group 1 cryptoassets – these fulfil a set of classification conditions and as such are eligible for treatment under the existing Basel Framework (with some modifications and additional guidance). These include certain tokenised traditional assets and stablecoins Group 1 cryptoassets will be subject to at least equivalent risk-based capital requirements based on the risk weights of underlying exposures as set out in the existing Basel capital framework. The cryptoasset either is a tokenised traditional asset or has a stabilisation mechanism that is effective at all times in linking its value to an underlying traditional asset or a pool of traditional assets. In the case of underlying physical assets, they must verify that these assets are stored and managed appropriately All cryptoasset arrangements must ensure full transferability and settlement finality at all times. In addition, cryptoassets with stabilisation mechanisms must ensure full redeemability (ie the ability to exchange cryptoassets for cash, bonds, commodities, equities or other traditional assets) at all times. Group 2 cryptoassets – are those, such as bitcoin, that do not fulfil the classification conditions. Since these pose additional and higher risks, they would be subject to a new conservative prudential treatment These coins are the ones that people would be more familiar with – such as BTC, ETH, ripple, really any coin that isn't a stable coin or a tokenized version of an asset like a share, bond, commodity or currency Each of these groups therefore have different Capital requirements for each banks reserve requirement - Similar to activities related to traditional assets that the banks hold, such as loans, bank activity related to cryptoassets will increase the operational risk charge to a bank within the Basel framework – due to cryptoassets being new and rapidly evolving, there is potentially an increased likelihood that they pose unanticipated operational risks in most cases to the banking system – this is basically saying that they don't know the true risks to the financial system if banks start trading crypto Group 1 cryptoassets will be subject to the requirements set out in the Basel Framework for a normal asset that the banks hold – group 1 is broken up into two categories depending on the classification of the asset Group 1a cryptoassets: tokenised traditional assets – i.e Tokenised traditional assets use an alternative way of recording ownership of traditional assets through the use of cryptography - may be treated as equivalent to a traditional asset for the purpose of calculating minimum capital requirements for credit and market risk - In practice this means that a tokenised cryptoasset is treated the same as - Bonds, loans, commodities, deposits and equities in regards to capital adequacy requirements This is because this form of cryptoasset must confer the same level of legal rights as ownership of these traditional forms of financing, eg rights to cash flows, claims in insolvency etc. For example, a tokenised corporate bond held in the banking book will be subject to the same risk weight as the non-tokenised corporate bond held in the banking book. Similarly, if a bank holds a derivative on a tokenised asset, it will be reflected in the market risk charge in the same way as a derivative on the non-tokenised asset – so in the banks eyes there is no difference in holding a bond or a tokenised version of the bond so – a tokenised cyptoasset can be recognised as collateral for the purposes of credit risk mitigation if it falls within the framework Group 1b cryptoassets: cryptoassets with stabilisation mechanisms that seek to link the value of a cryptoasset to the value of a traditional asset or a pool of traditional assets through a stabilisation mechanism. Cryptoassets under this category must be redeemable for underlying traditional asset(s) (eg cash, bonds, commodities, equities) – things like a stablecoin – so whilst not a tokenised version of the asset, its value is linked to the underlying asset, therefore it is treated relatively similar – however Group 2 cryptoassets – are those that pose unique risks compared with Group 1 - as such are subject to the newly prescribed capital requirement – these are coins like BTC and ETH – anything that doesn't have a tether to the value A risk weight of 1250% is applied to the greater of the absolute value of the aggregate long positions and the absolute value of the aggregate short positions to which the bank is exposed. A 1250 percent risk-weight is the equivalent in banking terminology to a 100% capital requirement So for bitcoin and Ethereum - this would require banks to hold $1 dollar for every $1 in "exposure" to those assets This is in line with the toughest standards for banks' exposures on riskier assets, such as illiquid shares or junk bonds - So if the bank has a $100 exposure in bitcoin this would result in a minimum capital requirement of $100 This also applies to cryptoasset derivatives positions with the potential maximum loss value under a RWA formula – This can be a bit of an issue for the derivative markets – as the RWA is often not the total loss based around the value of the trade, but the cost of the derivative contract – which is often many times smaller – as you are paying for a premium So in summary – if the assets are a tokenised version of an asset, or use an asset as an anchor for their value, then the banks can hold these and it can be treated as part of their capital requirements under the existing Basel III requirements – so banks can use this as part of CAR to against their RWA – under Basel III – you need to hold 8% of your RWA – which in Aus is calculated as 35% of your loans My take on all of this This could be good news for crypto markets, as they now may see greater recognition by the most powerful financial institution on earth when it comes to providing direction on regulatory frameworks Or, it could be that the financial system sees another way to make some money – so why not take the plunge? There is nothing inheritably wrong with making money – but the way that banks do this, especially in the US is different from you or I purchasing crypto The issue with this is the structure of the financial system – as these banks are TBTF If you buy one BTC for $50k and it drops down to $10k, you have lost $40k which sucks – you will likely feel bad – but you can hold onto this and hope the price recovers But the way a bank like JPM or Goldmans make these trading positions is normally though the use of derivatives on these assets – they only put up a fraction of the funds and cannot simply hold if the prices decline – because of counter party risk – as each bank tries to get out of a position at one point of time – this can create major issues -financial system collapse – If you go bankrupt – then too bad – if a bank goes bankrupt – this becomes your problem – as banks will get bailed out – remember, they are Too big to fail The BIS notes that the extreme price volatility of some of these assets – particularly those in group 2 – have unproven track record of liquidity will make it challenging to hedge positions when providing derivative instruments or when manufacturing investment products that reference crypto assets There are any number of ways that this can explode in the future – here are just three I can think of off the top of my head One – Requirements for additional dollars or bonds to be printed to absorb the increase in the RWA for any bank holding category 2 of the crypto assets – Say BTC does go to $500k - Banks need to increase cash they hold if prices rise – banks don't hold much cash relative to their overall asset and liability position – the balance sheet of banks is basically neutral – they have the same amount of liabilities as assets – so if the price of cryptos increases massively, then banks would need to have central banks expand the money supply further for them to maintain their CAR requirements Reminds me a little bit of the Mississippi bubble – the price of assets increases to the point that people want to cash out – but not for a worthless form of conversion such as the paper money being issued – if cash like the USD continues to be expanded at its current pace – people could request alternative assets destabilising the financial system - could create a major issue down the road Two – asset bubble through bank speculation and derivative practices – The GFC period was bad enough when you have banks speculating on newly created assets – whilst mortgages have been around for hundreds of years, the CDOs were relatively new – Through entering into crypto – banks are entering into a new territory of pure speculation – the buying and selling of cryptoassets by itself isn't the issue – but the speculative practice of derivates and who knows what else they come up with in the years to come could become a major issue for the stability of the financial system – could both collapse crypto markets as well as shares and bonds if economic confidence gets hit Three – Additional risks, such as AML issues – if the banks do not act in good faith, because to be honest they do not have a good history of this – there could be a call by regulators for additional crack downs on crypto So in summary – this legislation Creates a two tiered system for Cryptos – and opens the door for the largest financial entities to begin speculating on what is already a volatile asset For the two tiers - one is seen as good as the assets underlying it - The other – is seen as a very risky asset class So we may also see the rise of tokenised assets and a new wave of how the economy works In addition – it means that you will now be competing with the most sophisticated traders on earth – complex computer algorithms dictating market prices could see larger swings in volatility It goes without say that governments are increasingly focused on issues surrounding cryptocurrencies – especially with some central banks exploring digital currencies – this even came up in the recent G7 meetings this month So we will finish off the crypto series next episode looking at China's Central bank digital currency Thank you for listening to today's episode. If you want to get in contact you can do so here: http://financeandfury.com.au/contact/ https://www.bis.org/bcbs/publ/d519.pdf
In der heutigen Folge „Alles auf Aktien“ berichten die Finanzjournalisten Anja Ettel und Holger Zschäpitz über eine Wette um Vantange Towers, einen Star aus dem SDax und die Reaktion auf Zahlen bei Microsoft und Google. Außerdem geht es um Vantage Towers, Stratec, Digital Holdings, Square, Riot Blockchain, Visa, Facebook, Nvidia, Mastercard, PayPal, Tesla, JPM, MicroStrategy, Silvergate Capital, Overstock, Invesco Elwood Global Blockchain (WKN: A2PA3S), Commerzbank. "Alles auf Aktien" ist der tägliche Börsen-Shot aus der WELT-Wirtschaftsredaktion. Die Wirtschafts- und Finanzjournalisten Anja Ettel und Holger Zschäpitz diskutieren über die wichtigsten News an den Märkten und das Finanzthema des Tages. Außerdem gibt es jeden Tag eine Inspiration, die das Leben leichter machen soll. In nur zehn Minuten geht es um alles, was man aktuell über Aktien, ETFs, Fonds und erfolgreiche Geldanlage wissen sollte. Für erfahrene Anleger und Neueinsteiger. Montag bis Freitag, ab 6 Uhr morgens. Wir freuen uns an Feedback über aaa@welt.de. Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++Werbung+++ Hier geht's zur App: Scalable Capital ist der Broker mit Flatrate. Unbegrenzt Aktien traden und alle ETFs kostenlos besparen – für nur 2,99 € im Monat, ohne weitere Kosten. Und jetzt ab aufs Parkett, die Scalable App downloaden und loslegen. Hier geht's zur App: https://bit.ly/3abrHQm
In 1853, Trooper John Goldman shot his superior Corporal William Harvey in his tent at Buningyong following an altercation with a local shopkeeper over some boxes. Harvey died 24 hours later and Goldman disappeared for 9 months before being arrested. Goldman was convicted of wilful murder and was sentenced to death. It was to be the first public execution in the town of Geelong. But many people were uneasy with the sentence and appealed to Governor La Trobe which were denied. The day before the scheduled execution, a local Cobb and Co man rode for Goldmans life with a last ditch appeal. Listen to find out the full story of John Goldman and what happens next .... Once you have listened to the podcast, join us over on Facebook to ask any questions or check out the website for any additional information and pictures. Locked up with History - www.lockedupwithhistory.com.au Facebook Group - https://www.facebook.com/groups/lockedupwithhistory Geelong Gaol Museum - www.geelonggaol.com.au Twisted History - www.twistedhistory.net.au --- Send in a voice message: https://podcasters.spotify.com/pod/show/lockedupwithhistory/message
SPAC SPAC SPACA popular and approximately true thing to say about special purpose acquisition companies is that a company that goes public through a S... Private Securities Litigation Reform Actsafe harbor for forward-looking statements like sayexceptions to the safe harbor regulatory arbitragethe Wall Street Journal pointed outSPACs, IPOs and Liability Risk under the Securities Lawsincluding at the SEC That is kind of the dealin SPACs Joe Weisenthal writes about I wrote I wrote And improving institutional custody solutions going public this week buy Teslas with BitcoinsSure, why notthe job listingmore of thisWallstreetbets forum40,000 Goldmans in the U.S.over 12,000 Sachses talked a few years ago he left in 2018 company productthe timing here is perfect Buy Nuanceput off derivatives rulesGreensill Financial Holding FirmWhat Sort of a BusinessCEO Pay Surgedantitrust fineDefaults Fall Again 15,000 Tons of Silver Comes to ESGhonest & fungible chain letter Atomic Superyachtbogus yeti sightings on Odd Lotssubscribe at this linkherepages 52-53 of the proxyfootnote 15Paul Glenn anticipated
After another wild day in the silver market, there was more news from Goldman Sachs' commodities expert Jeff Currie. Where this time he made the rather unusual claim on Bloomberg TV that the silver market is now apparently even bigger than the equity markets. So to find out more about this shocking development, click tolisten now!
Sign up to our newsletter for more in-depth insights | Follow us on LinkedIn It's difficult enough to train to become a Doctor and then practice in some emerging countries with fragile health systems like Papua New Guinea. But then to switch tack completely, give all that up, win a place at Harvard Business School and join Goldman Sachs in asset management before going on to launch your own fund in emerging markets, may be considered brilliance or heresy, particularly when you come from Germany, a country that reveres technical expertise and is less enthusiastic about the merits of finance. So in this conversation I am delighted to unravel an unconventional journey and welcome Dr Christina McGuire, CEO of Elephant Asset Management as our guest. We discuss her upbringing and German attitudes to finance, before touching upon her medical journey, her decision to go to Harvard Business school and then join Goldman Sachs. She discusses working and investing in China, the skills taught and culture encouraged at Goldmans, before she explains her decision to go it alone. She describes the investment approach of her firm Elephant Asset Management, where she manages a concentrated, stock-specific, emerging market equity fund. She explains her philosophy and style, detailing geographic, sectoral and company disciplines as well as the significant opportunities created by the post-Covid world for her domestically-focused companies. She describes the due diligence process, the need to eye ball CEO and CFOs and why she believes company visits and sitting in the staff canteen of investing companies are great ways to gauge culture, and sense the mood. Christina also explains why the S&G in ESG are significantly more measurable in the countries in which she invests. Finally Christina talks about how women should really think about asset management as a career, and offers some other great advice for young people thinking about their futures. To celebrate our upcoming episode with Tilly Franklin, CIO of the Cambridge University Endowment Fund, we are re-releasing some past interviews with other inspiring women in finance. In this episode, Simon spoke to Dr. Christina McGuire, who discusses her extraordinary journey from working as a doctor in low income countries to becoming an emerging market equity fund manager. Are you a young woman looking to break into the investment industry? Discover free resources, news, events and support at www.gainuk.org. To learn more about the charity, listen to our new episode with Tilly Franklin, who co-founded the organisation (alongside running the endowment fund of one of the world's most renowned universities!). The full interview is out tomorrow, so stay tuned!
Sign up to our newsletter for more in-depth insights | Follow us on LinkedIn It's difficult enough to train to become a Doctor and then practice in some emerging countries with fragile health systems like Papua New Guinea. But then to switch tack completely, give all that up, win a place at Harvard Business School and join Goldman Sachs in asset management before going on to launch your own fund in emerging markets, may be considered brilliance or heresy, particularly when you come from Germany, a country that reveres technical expertise and is less enthusiastic about the merits of finance. So in this conversation I am delighted to unravel an unconventional journey and welcome Dr Christina McGuire, CEO of Elephant Asset Management as our guest. We discuss her upbringing and German attitudes to finance, before touching upon her medical journey, her decision to go to Harvard Business school and then join Goldman Sachs. She discusses working and investing in China, the skills taught and culture encouraged at Goldmans, before she explains her decision to go it alone. She describes the investment approach of her firm Elephant Asset Management, where she manages a concentrated, stock-specific, emerging market equity fund. She explains her philosophy and style, detailing geographic, sectoral and company disciplines as well as the significant opportunities created by the post-Covid world for her domestically-focused companies. She describes the due diligence process, the need to eye ball CEO and CFOs and why she believes company visits and sitting in the staff canteen of investing companies are great ways to gauge culture, and sense the mood. Christina also explains why the S&G in ESG are significantly more measurable in the countries in which she invests. Finally Christina talks about how women should really think about asset management as a career, and offers some other great advice for young people thinking about their futures.
We have been talking a lot about the spread of the coronavirus and also about all of people held in quarantine on air bases and cruise ships for fear that they might come down with it. One such couple from Santa Clarita, CA has had their Diamond Princess cruise extended by 14 days, but not by choice. A passenger on their ship contracted coronavirus, leading to a quarantine aboard the ship, now docked in Japan. Carl Goldman surprised his wife, Jeri Seratti-Goldman, with a 16-day cruise aboard the ship as a birthday gift, but now they're stuck in their cabin at port in Yokohama, Japan until Feb. 19. The Goldmans are owners of the radio station KHTS in Santa Clarita and have been have detailing parts of their quarantined experience on the station's website, hometownstation.com We got a chance to hear from Carl Goldman about his experience being trapped on the ship. Learn more about your ad-choices at https://www.iheartpodcastnetwork.com
WATCH the VIDEO on YOUTUBE > https://www.youtube.com/channel/UCTlJUkInU4r7TMNFSHHkpiQ Former Goldman Sachs professional runs through the 21 Trickiest Goldman Each Interview Questions! Find the full video on our YouTube channel, WorkLife TV. CONNECT: Leave a comment or message, we would love to hear your questions, what you think about our podcast and what you would like to see next! FOLLOW US: Instagram: https://www.instagram.com/worklifetv Facebook: https://www.facebook.com/worklifetv Twitter: https://www.instagram.com/worklifetv Follow WorkLife TV Founder & Host Sunil Kaushal: Instagram: https://www.instagram.com/sunilkaushal_ Twitter: https://www.twitter.com/sunilkaushal_
In the tenth episode of Confronting we focus on grief and reflection. The Goldmans have carried grief with them every day for the last 25 years and in this episode Kim talks to grief expert David Kessler. Kim shares with David how she’s dealt with the loss of her brother and how she has been able to move forward while still holding on to his memory. Together they discuss loss, healing and how grief looks different for all of us. Kim reflects with both Fred and Nancy on her journey and how Confronting has impacted her.
Codex is joined by comedian Peter-john Byrnes to burn it all to the ground (hypothetically). You can find the book online and at the local Bronco dealership. If I Did It: Confessions of the Killer by OJ Simpson Get the full story in O.J. Simpson’s own words! On July 31, 2007 Federal Court Judge A. Jay Cristol awarded the Goldman family the rights to If I Did It. Thus began one of the strangest odysseys in publishing history. The book, called “one of the most chilling things I have ever read” by Barbara Walters, skyrocketed up bestseller lists across the country in fall 2007 as the national media relentlessly covered O.J. Simpson’s dramatic Las Vegas arrest for armed robbery and kidnapping. Originally written by O.J. Simpson, this edition includes essays by the Goldmans and a member of the Goldman family legal team that reveal the fascinating story behind the bankruptcy case, the book’s publication and the looming court proceedings, that would eventually lead to his conviction. In 1994, Ron Goldman and Nicole Brown Simpson were brutally murdered at her home in Brentwood, California. O.J. Simpson was tried for the crime in a case that captured the attention of the American people, but was ultimately acquitted of criminal charges. The victims' families brought a civil case against Simpson, which found him liable for willfully and wrongfully causing the deaths of Ron and Nicole committing battery with malice and oppression. In 2006, HarperCollins announced the publication of a book in which O.J. Simpson told how he hypothetically would have committed the murders. In response to public outrage that Simpson stood to profit from these crimes, HarperCollins canceled the book. The Goldman family views the book as his confession, and has worked hard to ensure that the public will read this book and learn the truth. This is O.J. Simpson's original manuscript, approved by him, with up to 14,000 words of additional key commentary. SHOW NOTES: Previous Episodes: 5. ‘Doc Savage: The Man of Bronze’ w/ Peter-john Byrnes 16. ‘White Rabbits’ w/ Jill Bernard 24. "SCUM Manifesto" w/ Kelly Stone 25. ‘Days of War Nights of Love’ w/ Goodrich Gevaart 29. ‘American Boomerang’ w/ Chad Briggs 33. "The Protocols of the Elders of Zion" w/ John-Michael Bond 48. 'The Coming of the Fairies' w/ Peter-john Byrnes & Tamara Lynn Chambers 57. "Hogwarts School of Prayer and Miracles" w/ Peter-john Byrnes & Sherman Edwards 74. 'Bachelor Pad Economics' w/ Peter-john Byrnes & Patrick McManus 83. 'Atlas Shrugged' w/ Peter-john Byrnes & Kevin Lobkovich 100. 'My Awakening' w/ Bill Bullock & Peter-john Byrnes 104. 5-Year New World Order Anniversary LIVE 132. ‘Communion' w/ Peter-john Byrnes Currently Reading: ’The Twelve Caesars’ by Suetonius Topics: a surprising amount about Claudius and hot tubs Follow TOMEFOOLERY for information about upcoming episodes & books: @Tomefoolery and Facebook.com/Tomefoolery. Please rate and review on iTunes! WEBSITE: http://Tomefoolery.com STORE: http://squareup.com/market/Codexotica PATREON: http://patreon.com/Codexotica FAN GROUP: https://discordapp.com/invite/5mq7tPV
The Goldmans didn’t get justice during the criminal trial, but the family had a second chance by filing a civil case against Simpson for the wrongful death of Ron. This time, it wouldn’t be “the People vs. Orenthal James Simpson”, it would be the Goldman’s name on the lawsuit. Kim speaks with Dan Petrocelli, the Goldman’s attorney for the lesser-known civil trial. Dan reflects on everything from his strategy in the courtroom, to the pressure he felt to win the case. Kim also speaks with Pablo Fenjves, a witness during the criminal trial who was later hired to ghostwrite Simpson’s book, If I Did It – a hypothetical account of the night of the murders. Pablo and Kim discuss how this book came to be and Pablo expresses what he learned as he wrote what was essentially a pseudo admission of guilt with Simpson.
This week, Paul goes behind the curtain with law Journalist (CNBC, Fox) and Professor Stanley Goldman who wrote a book on his Mother’s experiences and struggle to survive a life in the death camps of Nazi Germany. In “Left to the mercy of a Rude Stream,” Goldmans mother’s life was spared by Nazi Heinrich Himmler […]
Barry Shore, the Ambassador of JOY, brings to YOU the remarkable team of Jonathan and Andi Goldman, world renowned experts in Healing Sounds. This lively session will literally ENLIVEN YOU with information, practices, tips, and tools in one the art helming via sound. Both Jonathan and Andi have dedicated their lives to helping people utilize their own being in the process of healing and achieving health and happiness. This particular segment will explore the positive powerful affects of HUMMING. Now on the surface that might seem odd but Humming is a sonic anchor for creating a balanced state. The focus of their work was on a compound called nitric oxide (NO), a neural transmitter that is fundamental to our health and well being. The sound produced by Humming spikes NO release in the body. The Goldmans urge everyone to bring greater harmonies into life and even though it's only Humming: Make Sound and Music. You'll be listening to this often and sharing with everyone You LOVE.
The Wynwood neighborhood has received a lot of attention over the last couple of decades. However, its history is more than a hundred years. The neighborhood was originally named Wyndwood Park. Later the name would drop the park from the name and the ‘D’ from the spelling of Wynwood. The area was mostly occupied by working class residents. It featured companies such as the Coca Cola bottling plant, as well as, the American Bakeries. Northwest Fifth Avenue developed into a garment district. Miami History Channel: www.miamihistorychannel.com Miami History Blog: www.miami-history.com
In this episode, Josh and Maureen Goldman of Vernacular Podcast Network's The Popped Cast join us to talk about their show and what pop culture has to do with being human. We get to know Josh and Maureen and at the end of the show, we put the Goldmans through the paces of one of our lightning rounds, and ask them to make difficult decisions like "Jurassic World or Jurassic Park"?Listen to The Popped Cast on Apple Podcasts | Overcast | Google Play | PocketCasts | Castbox Become a supporter of this podcast: https://anchor.fm/vernacular/support
Soumaya Keynes, our economics correspondent, asks why cars are the sticking point in the NAFTA negotiations. Also Simon Long, our finance editor, interviews Lord Jim O’Neill, former Goldman Sachs economist and BRICS man. Is he a China bull and does he think Goldmans will catch up with Morgan Stanley? See acast.com/privacy for privacy and opt-out information.
Soumaya Keynes, our economics correspondent, asks why cars are the sticking point in the NAFTA negotiations. Also Simon Long, our finance editor, interviews Lord Jim O’Neill, former Goldman Sachs economist and BRICS man. Is he a China bull and does he think Goldmans will catch up with Morgan Stanley? See acast.com/privacy for privacy and opt-out information.
In today's podcast we discuss In today's podcast we discuss 2017, Roy Moore, climate change, cows, methane, seaweed, tax bill, NXT Takeover Wargames, Triple Cage, Jeff Sessions, Liberals, Justin Trudeau, Justice League, Batman vs Superman, Stanton, Patrick Stewart, Donald Trump, Al Franken, Keystone Pipeline, TransCanada, Christian Bale, Dick Cheney, Sylvester Stallone, The Flash, Marvel, DCEU, Dusty Rhodes, Giants, Marlins, NFL, NFL Draft, Obama, Elon Musk, semi, Matt Hardy, Cactus Jack, ECW, November to Remember, 1995, GOP, Alabama, mall, Santa Claus, Godzilla, Tokyo, God, Goldmans, If I Did It, Pence, turkey legs, elf, viagara, hannity, ted cruz, dick pics, gerbil, & Richard Gere.Also, we are on iTunes! Subscribe, download and review at https://itunes.apple.com/ca/podcast/papa-johns-brain-droppings/id1278787736Listen to the Papa John's Brain Droppings Podcast on Stitcher at http://www.stitcher.com/s?fid=149731&refid=stprFollow us on http://www.Twitter.com/TheJohnDNewton or https://www.facebook.com/PJBDPodcast for the latest updates. Favorite us on TuneIn at https://tunein.com/radio/Papa-Johns-Brain-Droppings-Podcast-p1026907/For video of the podcasts subscribe to https://www.youtube.com/channel/UCnBY8t1-2xJCr7jxYn6evfg
In today's podcast we discuss In today's podcast we discuss 2017, Roy Moore, climate change, cows, methane, seaweed, tax bill, NXT Takeover Wargames, Triple Cage, Jeff Sessions, Liberals, Justin Trudeau, Justice League, Batman vs Superman, Stanton, Patrick Stewart, Donald Trump, Al Franken, Keystone Pipeline, TransCanada, Christian Bale, Dick Cheney, Sylvester Stallone, The Flash, Marvel, DCEU, Dusty Rhodes, Giants, Marlins, NFL, NFL Draft, Obama, Elon Musk, semi, Matt Hardy, Cactus Jack, ECW, November to Remember, 1995, GOP, Alabama, mall, Santa Claus, Godzilla, Tokyo, God, Goldmans, If I Did It, Pence, turkey legs, elf, viagara, hannity, ted cruz, dick pics, gerbil, & Richard Gere.Also, we are on iTunes! Subscribe, download and review at https://itunes.apple.com/ca/podcast/papa-johns-brain-droppings/id1278787736Listen to the Papa John's Brain Droppings Podcast on Stitcher at http://www.stitcher.com/s?fid=149731&refid=stprFollow us on http://www.Twitter.com/TheJohnDNewton or https://www.facebook.com/PJBDPodcast for the latest updates. Favorite us on TuneIn at https://tunein.com/radio/Papa-Johns-Brain-Droppings-Podcast-p1026907/For video of the podcasts subscribe to https://www.youtube.com/channel/UCnBY8t1-2xJCr7jxYn6evfg
Episode 44 with Rachael Goldman of Goldman's Pawn Shop. Episode show notes available at http://www.evansvillepodcast.com/goldman/ Rachael talks about what a pawn shop actually does and how she got started doing stand up comedy. We also talk about the benefits of living and working in Downtown Evansville.
Det kaxiga sjätte avsnittet är ute! Massagen i Getinge, Goldmans tokhöjning av Kinnevik och Cassandra Oils alkemist-maskin diskuteras.
Why listening to departing employees is foolish See acast.com/privacy for privacy and opt-out information.
Is Fabrice Tourre one of the most boastful men in the world, or is the Goldman Sachs trader a man who looks dispassionately at himself and is well aware of his weaknesses? See acast.com/privacy for privacy and opt-out information.
Fred and Kim Goldman discuss their view of O. J. Simpson and his confession in "If I Did It."
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