Quant Trading Live Report

G'day, everyone! Brian from quantlabs.net here. In today's episode, we dive into the intricate world of risk management within the banking and financial services sectors. We explore a detailed article from eFinanci   Learn why TradingView is #1 platform to trade from  LEARN | Quantlabs (quantlabsnet.com) Learn about the critical role of risk management professionals in preventing financial shocks and ensuring the stability of financial institutions. We also discuss the career paths, necessary skills, and educational qualifications needed for a successful career in risk management. Moreover, we delve into the compensation structure for risk management roles, highlighting the differences in salaries and bonuses between various ranks from analysts to managing directors. This episode is a must-listen for anyone interested in the financial industry or considering a career in risk management. Source is here What is Risk Management Services with QuantLabs (quantlabsnet.com)   See the source here    Join us as we navigate through the complexities of risk management and provide insights into how you can prepare and thrive in this essential field.

In this episode, we delve into the challenges and opportunities for individuals aged 50 and above who are looking to break into the programming world, specifically focusing on learning C++. We explore a Reddit discussion from the CPP subreddit, where a 50-year-old aspiring programmer seeks advice on navigating this career transition.   Learn why TradingView is #1 platform to trade from    LEARN | Quantlabs (quantlabsnet.com)   We discuss the difficulties of learning a complex language like C++ and the age-related biases in the tech industry. The conversation highlights the importance of building a strong portfolio to showcase your skills, especially when you lack formal experience. We also touch upon the evolving landscape of software development, with a shift towards cloud-based technologies and the persistence of legacy systems in mission-critical environments.   See the source here  Engineer Software Jobs: Learning C++ and Breaking into Tech After 50 (quantlabsnet.com) Additionally, we emphasize the need for continuous learning and the potential advantages of contributing to open-source projects. The episode provides practical advice on creating your own projects, branding yourself, and effectively communicating your skills to stand out in a competitive job market. Join us as we share insights and strategies to help older programmers navigate the tech industry, build their careers, and overcome age-related hurdles.

Welcome to today's episode, where Byyan dives deep into the fascinating world of quantitative analysts, commonly known as quants. It's June 19th, and we are exploring what quants do, the skills required, and how you can become one. This episode is based on an insightful article from eFinancialCareers.com titled "What Do Quants Do and How Do You Become One?" Unraveling World of #Quant Finance: Roles, Skills, and Opportunities #trading The world of Quantitative finance thrives on complex calculations, intricate models, and the ability to predict market behavior. https://www.quantlabsnet.com/post/unraveling-world-of-quantitative-finance-roles-skills-and-opportunities   Quants play a crucial role in the finance sector, combining math and software engineering skills to create mathematical models for trading strategies, risk management, and financial products. We discuss various quant roles, from computational finance and economic analysis to portfolio management and statistical finance. Discover the best-paying locations for quant jobs, the importance of coding languages like C++ and Python, and the significance of prestigious institutions like Imperial College in London.   Find out why TradingView is the #1 platform to build your algo trading business on   We also delve into the evolving landscape of quant careers, the impact of AI and machine learning, and the potential career paths within fintech and traditional financial institutions. Whether you're an aspiring quant or simply curious about the field, this episode offers a comprehensive overview of the opportunities and challenges in quant finance.   For more detailed insights, visit quantlabsnet.com and stay tuned for upcoming events and resources to help you navigate the high-paying world of quantitative finance.

Hello, everybody. Brian here from quantlabs.net. Today is June 17th. In this episode, I delve into a competitor's service that simplifies technical analysis by turning complex data into actionable insights. Although I won't mention their name, I'll compare their offerings with mine, highlighting my unique advantages. This competitor boasts over 3,000 assets, but I can scan up to 60,000 supported by interactive brokers, including 30,000 US stocks and 1,000+ US-based ETFs. They offer custom indicators and 40+ reports, but I focus on avoiding overwhelming my users. While they provide an economic calendar and five years of data, I have decades of historical data. Their service includes intuitive reports and custom TradingView indicators, enabling live trading with odds on your side. However, I emphasize the importance of measuring volatility and timing, which they might overlook. Their pricing ranges from $40 to $200 per month, with varying levels of mentorship and support. Ultimately, while their marketing claims simplicity and institutional-level trading, I'm skeptical without seeing live trading accounts. Visit quantlabsnet.com for more information and stay tuned for our new offerings, including a mobile app.

Join Brian from QuantLabsNet.com as he delves into the revolutionary potential of the new generation of ChatGPT, focusing on GPT-4's application in the financial world. Recorded on June 16th, this episode explores how large language models (LLMs) are transforming data analysis in various fields, including economics and sports.   Join us LEARN | Quantlabs (quantlabsnet.com) Brian discusses a fascinating study by researchers from the University of Chicago, who used GPT-4 to analyze financial statements of over 15,000 public corporations spanning from 1968 to 2021. The goal was to predict future earnings with surprising findings that GPT-4 achieved a 52% accuracy rate—comparable to traditional methods but with unique advantages in identifying outliers and hidden gems. The episode also touches on the limitations of machine learning in capturing market psychology, geopolitical events, and industry trends, emphasizing the irreplaceable value of human judgment. Ethical considerations in the financial industry are scrutinized, particularly the manipulative potential of advanced models and the questionable integrity of major financial institutions. Tune in to understand how LLMs like GPT-4 could revolutionize investment strategies, uncover hidden opportunities, and the ethical implications of these advancements in the ever-evolving financial landscape.

Join Brian from Quantlabsnet.com as he delves into a thought-provoking quant interview question sourced from StackExchange. In this episode, recorded on June 12th, Brian breaks down the concept of R-squared (R2) and its significance in statistical models, particularly in the context of investing. Brian explains the definition and calculation of R-squared, emphasizing how a perfect R2 value of 1 indicates that all movements of a security are completely explained by an independent variable. He discusses the implications of a high R2 value and the potential pitfalls, such as spurious regression. The episode explores various responses to the interview question, including the irony of needing an expected value when you already know the outcome. Brian also covers practical considerations like trading fees and taxes that can affect real-world applications of these models. Whether you're preparing for a quant interview or just curious about advanced statistical measures in finance, this episode offers valuable insights. For more detailed discussions and resources, visit quantlabsnet.com.

Good day, everybody. Brian here from quantlabsnet.com. Let's dive into an essential article that sheds light on transitioning from software engineering to quant research, particularly within systematic hedge funds.   A Guide for What Do Software Engineers Do To Enter Quant Systematic Hedge Funds (quantlabsnet.com)   Published on June 4th by Durlston Partners, this insightful piece by Alex Jouawat addresses the challenges and opportunities for software engineers aiming to break into the high-stakes world of quant research. It emphasizes the importance of advanced academic training, particularly in physics, mathematics, and machine learning, and provides practical advice on further education and self-learning. Key takeaways include the need for a strong foundation in probability, linear algebra, calculus, and the ability to solve complex coding problems on platforms like LeetCode. The article also highlights the value of hands-on experience through open-source projects and competitions like Kaggle, and the importance of building a personal brand on platforms like GitHub and LinkedIn. Additionally, the article discusses alternative paths such as becoming a quant developer or focusing on algorithmic execution research, which leverages strong programming skills in low-latency systems and high-performance computing. For those committed to making this transition, the article provides a wealth of resources, including recommended reading materials and courses. It underscores the importance of networking, staying updated on industry trends, and seeking mentorship from experienced quants. Transitioning to a quant research role is challenging but achievable with dedication and the right approach. For more insights and resources, visit quantlabsnet.com.

Join Bryan from QuantLabsNet.com as he delves into a fascinating discussion on identifying failing trading strategies with insights from BetterSystemTrader.com. In this episode, Brian explores the six key methods shared by Kevin Davey, including analyzing historical performance, using advanced statistical methods, understanding market conditions, and leveraging Monte Carlo simulations.   Six Ways to Detect a Failing Trading Strategy (quantlabsnet.com) Discover how to assess your strategy's robustness through tools like ARIMA and understand the importance of different trading approaches such as trend-following and mean-reverting strategies. Brian also touches upon the significance of regime performance and adapting strategies in response to market changes. For more details, visit QuantLabsNet.com and check out the full interview on BetterSystemTrader.com. Stay informed with daily updates and explore high-level trading strategies through Brian's comprehensive video content.

Welcome to a comprehensive episode where Brian from FontLabsNet.com delves into a series of insightful articles focusing on strategy, development, and allocation in the financial markets. This episode covers key topics such as macroeconomic analysis, technical indicators, and the efficacy of simple momentum strategies. LEARN | Quantlabs (quantlabsnet.com) Dive into Effective Trading Algorithms and Simple Momentum Strategies (quantlabsnet.com) In the first segment, we explore an article from PriceActionLab.com that highlights the use of simple technical indicators for tracking market momentum. Brian discusses how a 12-month moving average model has shown promising results, even outperforming more complex strategies in certain scenarios. The episode continues with a critical examination of why macroeconomic market analysts often dismiss other methods, particularly systematic trading. Brian shares his own experiences and insights, emphasizing the importance of both fundamental and technical analysis for market timing and selection. Next, we shift focus to a DIY trend-following asset allocation strategy from AlphaArchitect.com. Brian outlines the current exposure recommendations for various asset classes, including domestic and international equities, REITs, commodities, and bonds. He provides guidance on how to balance these allocations based on different risk profiles. The episode wraps up with a deep dive into mathematical modeling and spread calculations, featuring discussions from Quant.StackExchange.com. Brian addresses complex questions on modeling bid and ask processes and calculating spreads for trading strategies, offering practical advice for managing market noise and volatility. Tune in for a wealth of knowledge on market strategies, backed by real-world examples and expert analysis. Don't miss out on this informative episode that promises to enhance your understanding of market dynamics and trading methodologies.

Hello everybody, Brian here from QuantLabsNet.com. In this episode, we tackle a pressing question from quant.stackexchange.com: Can individual quants still make money nowadays?   Join our new community at https://www.quantlabsnet.com/registration We delve into the complexities of competing with large firms, discuss viable strategies for independent quants, and explore industry trends. Learn about the smallest quant trading operations, the significance of high-frequency trading, and the potential of platforms like TradingView for independent traders.   A Day in the Life of a Quant Researcher at Citadel Securities: Decoding the Algorithmic Magic (quantlabsnet.com) We also emphasize the importance of motivation, trading knowledge, and demonstrating a verified track record to attract recruiters and succeed as an independent quant. Don't miss this insightful discussion that could shape your trading journey! Visit our new domain at quantlabsnet.com and join the community we are building.

Join Brian from quantlabs.net as he delves into a fascinating topic introduced by a helpful viewer: the world of quant interview preparation. Brian discusses a YouTube video from The Quant Guide channel, which features a mock interview for a 2024 Citadel Quant Training position. This episode is a must-listen for aspiring quants, especially those with strong backgrounds in programming, math, or physics.   Join our new community at https://www.quantlabsnet.com/registration The video highlights the rigorous nature of quant interviews and the importance of having a deep understanding of math and probability. Brian scrutinizes the legitimacy of The Quant Guide's program, which promises to prepare candidates with over 500 real interview questions and detailed solutions. He raises concerns about the high price tag and the potential marketing tactics involved. Brian advises listeners to critically evaluate such programs and explore free resources like Reddit and LinkedIn. He emphasizes the importance of having a strong educational background and showcasing coding skills online to succeed in the highly competitive field of quantitative finance. Tune in to get an insightful take on whether these costly prep programs are worth the investment and how you can better prepare for a career as a quant.

In this episode, Bryan from quantlabsnet.com delves into a fascinating article from eFinancialCareers.com on how JPMorgan measures the success of its software engineers. Discover the metrics and methodologies JPMorgan employs to gauge productivity, including the importance of Agile practices and quick implementation of new features.   Join our new community at https://www.quantlabsnet.com/registration Brian discusses the high expectations and pressure cooker environment within the financial sector, emphasizing the need for engineers to balance speed and safety in their work. Additionally, he shares insights on the evolving 24/7 market influenced by crypto and the critical role of safety and security in code management.   Inside the JPMorgan Chase Careers Source Code Machine: How They Measure Software Engineer Success (quantlabsnet.com)   Tune in to learn about the lucrative but demanding world of finance engineering and how you can thrive in it. For more information and to access the article, visit the new website at quantlabsnet.com.

Join Bryan from quantlabs.net.com as he delves into the intriguing world of a Quant Researcher at Citadel Securities in Miami. Discover the daily routine of Will Softhold, a PhD physicist from the University of Cambridge, who now thrives in the high-frequency trading (HFT) environment.   Join our new community at https://www.quantlabsnet.com/registration From early morning swims to late-night coding sessions, this episode provides a detailed look at the challenges and rewards of working in one of the most prestigious financial firms. Learn about the importance of supervisory roles, the dynamics of team collaboration, and the critical role of systematic trading algorithms in the FX market. A Day in the Life of a Quant Researcher at Citadel Securities: Decoding the Algorithmic Magic (quantlabsnet.com) Whether you're an aspiring quant or just curious about the inner workings of finance, this episode offers valuable insights and practical advice. Tune in to understand what it takes to succeed in the fast-paced world of quantitative research.

Good day, everybody. Today is May 30th. This is now Bryan from quantlabsnet.com. Our platform is transitioning to a new web domain, and the previous one will be phased out within the next 30 days. Let's dive into an insightful article from Bettersystemtrader.com titled, A New Approach to Trading Volatility with Rob Hanna. The article highlights the inverse relationship between the VIX and the S&P 500, and how traders can use VIX signals to time their trades on the S&P 500. Interestingly, a similar inverse relationship exists between Bitcoin and the US dollar, providing another avenue for trading strategies. Another key point is that using the S&P 500 to time its own trades can be more effective than relying on the VIX. The article suggests that short-term indicators for the S&P 500 are better predictors of VIX movements. Additionally, traders might find value in using the S&P 500 to time the VIX, potentially reducing the length of drawdowns. For a deeper understanding, the article includes video clips explaining these concepts. If you're into algo trading, these insights could be particularly beneficial. To stay updated, visit quantlabs.net/book and join the email list.

In this episode, Brian from quantlabs.net delves into a fascinating article from eFinancialCareers.com about Better Hand Financial Technologies (BHFT), a high-frequency trading firm based in Dubai. BHFT has been making waves with its remote work model and strategic hires from top competitors.   New website at Home | Quantlabs (quantlabsnet.com) Key hires include Ilya Malinovsky, former head of HFT at Tower Research Capital and Credit Suisse, and Ruslan Reskipov, previously head of derivatives and algo trading at Renaissance Capital. The firm has also attracted talent like Rook Teeter, former managing director at KCG Holding and Tower Research. BHFT stands out by using Rust instead of the traditional C++ for its trading systems, attracting a diverse team that includes chess champions, martial arts winners, and world-class math and science talents. Despite the remote work setup, the company boasts a friendly, multicultural team with a modern tech stack. The episode also covers BHFT's current job listings, including roles for senior quant traders and researchers, with a notable focus on the Chinese and Indian trading markets. Brian wraps up by sharing updates about his new website, quantlabsnet.com, and invites listeners to join the new community group.

Good day, everybody! Brian here from quantlabs.net. In today's episode, we're diving into an often overlooked tool for financial analysis: Microsoft Excel. While many focus on programming and high-frequency trading, Excel provides a powerful platform for non-programmers to conduct financial research and analysis. Get your trading tech books here books2 - QUANTLABS.NET We'll explore various uses of Excel, such as data gathering and cleaning, trend analysis, and fundamental analysis. Learn about essential Excel functions like XNPV, IRR, VLOOKUP, and HLOOKUP, and discover how to leverage Excel's powerful features like Power Query, macros, and add-ins for advanced financial modeling.   Powering Your Research: Using Excel for Financial Analysis - QUANTLABS.NET If you're interested in enhancing your financial analysis skills with Excel, this episode is for you. Plus, don't forget to check out our free trading books and stay updated on our upcoming website changes by joining our email list at quantlabs.net/books. Thanks for tuning in, and have a great day!

Good day, good day, everybody. Brian here from wantlabs.net. Today is May 28th. I'm going to have some big news coming down the pipe soon. So keep your eyes and ears and all that peeled out for it. Anyways, I came across another interesting article. I do like this BetterSystemTrader.com podcast. It's pretty good. They did a posting called 10 Insights from the Man Who Solved the Market. This is referring back to the book Jim Simons Medallion Fund. It's the book put out by Gregory Zuckerman a few years ago. So this guy, Andrew Swan Scott, read it and thought he'd provide his insights. So let's go through these.   Get your free trading tech books here books2 - QUANTLABS.NET The first one is originality matters. Ignore conventional wisdom about the markets. Innovate and explore unique trading strategies and ideas. Look at the market differently from the herd. I totally agree with that because when you look at the markets, there's usually a star performer out there if you go out and dig for that among all the different data sources. And it could be a long-term trending strategy that you could use based on that. A good one in the past was USD Japanese Yen. Another one that was lesser known was USD Turkish Lira or Euro Turkish Lira. They did really good over the years, but now central bankers have stepped in and taken away those opportunities. Now, I don't know about the yen. That could continue, but that could lead to something that could be the next big catalyst to take us all down. But at the end of the day, looking for those sort of things, finding them, that's what gives you what they call trading edge for sure. Number two, collaborative success. Partner with talented individuals. Foster a collaborative environment to enhance problem-solving and innovations. Again, I cannot stress this. We're hoping to have an interview with Ernie Chan and other people that have kind of trailblazed the whole quant trading space, specifically for those that are coming from the retail trading space. Because as we know, to do true HFT, high-frequency trading, and true low-level quant research and that, people can kind of do it, but you have to have a fairly big account to take advantage of it to really do the pay-to-play thing directly right on the exchanges. As a retail trader going through a retail trading broker, that's pretty hard to do. So you have to find people that are kind of in the same area as you in terms of your account size, maybe your technical chops, as well as your mathematical experience. For myself, I guess I can share this now is that I will be moving my site over to a better technology, to Wix. I'm hoping to build out a better group community through that. That's part of the WIC's features, I guess. I did have an amazing group a few years ago. They're still around. I just want to bring more people together so that they can engage with each other behind the scenes. All at a paywall, but membership privileges have its costs. So that's where you get the collaborative success. So that's what I'm hoping to bring to the table. Okay, number three, embrace scientific rigor. Apply a rigorous scientific approach in model Model testing and validation ensuring robustness and statistical significance. This isn't really HFT, but to make life easier for a retail trader, I find using tools, very popular, very in-depth tools like TradingView helps you here. You can see instantly without going through any of the wonky backtesting packages out there, frameworks. works. Out of the box, you're ready to go. When you're working with an open source trading strategy, if you build your own, buy one, lease one, whatever on TradingView, you get the ability to see it. What's its profit potential? What is its profit factor? Which is another way of saying, if I'm going to put a dollar in, how much can I expect to get return from that via the profit factor? These are right there out of the box. So when you have these sort of instantly viewable to you from a high level, it makes your life a lot easier and a lot less stressful. A lot of people want to build and roll their own solutions. I'm not against that. But when you get up to my age, you will start to see how valuable time will be. That's all I could tell you. Efficient capital allocation. Okay. Develop systems to optimize capital allocation across various strategies to maximize returns and manage risk. One thing I can mention here, a lot of the boutique hedge funds, boutique AGFT shops, a lot of them will trade in the space of options. I don't think you can operate under a really successful trading strategy with a $1,000, $5,000 account. You need to have something fairly significant to play those kind of, I don't want to say gains, but kind of strategy capabilities. You need probably $20,000, $25,000 because you have to add all your premium and all that fun stuff. And that's why one of the reasons why ETFs are popular because they're not really risky. You can dream like a stock and there's no margin requirement any of that so these sort of things matter but if you do do the options training you can do very well if you get something that actually actually works okay let's talk number six leverage with caution use leverage strategically to amplify your returns now most people i talk to who keep their account in check from early blowing up. One of the things they do is they use no more than six times. I've seen in crypto years ago, finance would have 100 times and so on. And that's high risk when things are not going your way, especially when the assets are in a consolidation phase or downward spiraling or falling knife environment. You don't want to use leverage there. If it's a long-term trend and it's doing well, then yeah, add your leverage. Some people may go up to 12, let's say, but no more will not go more than six. Data quality is key. Prioritize the acquisition and cleaning all extensive data sets for accurate model development and testing. Again, this is where I like TradingView. you. You can get all kinds of data sources. You'll get, let's say if you're using free data sources like Yahoo Finance, expect to get the gaps. The gaps are going to be deadweight to you and they're going to be hard to work with. So you got to use good quality data. Obviously, there's lots of sources and most of them, I think all of them are going to be paid. And if you're not willing to do that, you're going to, I don't know, if you're just playing around and experimenting, fine. But if you ever want to get serious, you got to pay for the data. And as I say what you get what you pay for is what you get so if you're going to get free stuff I expect to have a low quality. Experiences and results that's all I can tell you they have the ability to enable you to have. Enable you to have decent success there. But obviously, you got to find your proper strategy. Short-term focus, number eight, concentrate on short-term trading opportunities where predictive power is stronger and more actionable. I know one successful trader, he most likely will hear this, he's trading on one minute. Now, he's probably successful there based upon his experience, based upon his history, and he's probably blown up a lot of accounts. So the short focus can help, but this is, again, for a guy who's built and defined high-frequency trading. And obviously, sub-second, sub-minute matters if you're successful. If you're coming from the free trade world, you want to work with basically. Basically long-term, daily, four-hour. When I was writing for Seeking Alpha, they wouldn't accept articles that timeframes less than four hours. So that's just to give you a scenario depending upon who you are and where you're coming from in terms of knowledge in the world of trading. Execution matters. Invest in technology and processes for efficient trade execution to minimize market impact and slippage the one i've come up with between trading view and the auto trading that's how trading view defines it with something like traders post is exceptional i could be sleeping at night and it trades and it's 100 fully synced that's all i can tell you there unless you try it you're not going to know except luck's rule there is a lot of luck i'm not going to deny that to you and yeah so we'll leave it at that you know basically it's like betting in a casino where if you're betting. If you're betting in Vegas, well, that means you may be riding on luck. You may have to do 10 little trades, take 10 little losses, but maybe that 11th trade may be the big one that you're seeking. But how often does that happen? No one knows. If you have a strategy that may be able to predict that, fine. And then you can work off of that for luck. So basically what this guy was saying, the author of this article here, Peter, this Andrew guy said, what Simmons, Simons and his team achieved is remarkable. We'll probably never see anything like this in our lifetime. Who knows? Computers may come up and do stuff and they may be doing it already through the AI, but we just don't know about it because these are not publicly known. They're not going to go on the internet and say, hey, look at me. I bought a Ferrari because I made an amazing AI trading solution. And if they are, they're just probably BSing. And if they're not showing they're creating journal to achieve that, well, there's a problem there. We may never know the details, but there are enough hints to guide all traders. Very true. Yeah. And then there's interview posted here with the guy, Gregory Zuckerman. Also, I think I can say about this is that Simons was very reluctant to do the interview and to do the book. And apparently, there are some parts in the book that Simons didn't want to get revealed. But this Zuckerman still went ahead and published it. And I don't think Simons was too happy about it. I wanted to leave that as well. And I'll talk to you soon. Have a good day. Remember, get on our training books, quantlabs.net slash books. That may change soon. So do it while you can. Over and out. Thank you.

Hello everybody, Brian here from quantlabs.net. Today is May 23rd. I just wanted to go over two podcasts I'm putting out today. I haven't done anything in a while. If you want to know why, just hold out to the end and I'll fill you in.   Here is a bunch of free tracing tech books books2 - QUANTLABS.NET Weird Algo Strategies, Controversial Claims, and Exciting Website Updates! - QUANTLABS.NET One of the sources that I use is bettersystemtrader.com. And the title I thought was interesting. It's called Weird NASDAQ Algo Strategy. It's a bit weird, but it's also quite profitable. There's an associated video with it on YouTube. The creator, Thomas Nesnidal, shares the source code in easy language for TradeStation. He explains why you shouldn't be afraid of strategies like this and how they can work on multiple markets. Another topic I cover is about a controversial video quoting Jesus, where the creator claims to be better than 99% of all hedge fund managers. He talks about learning programming in three months and making money through ETFs and high-performing ETFs based around big tech, using Robinhood. I also provide an update on the new website coming, which will be 100% custom coded by myself using Python Django with Wagtail. I've been looking for a new web hosting provider and decided to move to DigitalOcean. The new website will be more news-driven, focusing on various investment sectors and providing free samples to generate responses. Additionally, I discuss my new deep scanning analysis for ETFs, which involves analyzing ETFs globally and categorizing them into different sectors. This method helps identify high-performing ETFs based on profitability percentage and profit factor. Lastly, I mention the importance of transparency in trading. I plan to sync my trading account with TraderSync to share my performance and learnings with the community. The new website will also feature a big news section, moving content from my Discord channels to the public site. Thank you for listening. If you want to know more, I've got my newsletter and trading PDFs at quantlabs.net/books. Stay tuned for more updates!

Join Brian from quantlabs.net as he delves into the complexities of high-frequency trading (HFT) and provides valuable insights for software engineers aiming to transition into this competitive field. This episode covers the essential technical and trading concepts you need to grasp, from order books to matching engines, and explores the specialized knowledge required to excel in HFT firms. Get our free trading tech books books2 - QUANTLABS.NET Breaking into High-Frequency Trading: Essential Career Insights - QUANTLABS.NET Brian discusses the journey of transitioning into HFT, misconceptions about the field, and the key areas of expertise needed. Topics include order book dynamics, pricing engines, option pricing, and the intricacies of protocols like FIX. Additionally, he shares practical tips for impressing in interviews and thriving in the fast-paced environment of HFT shops. Don't miss this comprehensive guide to navigating the world of high-frequency trading and setting yourself up for success in one of the most lucrative sectors in finance.

In this podcast, we discuss a recently published Hedgeweek article focusing on Renaissance Technologies, also known as Rentech, and their acquisition of GameStop and AMC shares. These shares surged in value, prompting questions around the validity of Rentech's actions and whether this was a calculated investment decision or potential insider trading. Get your free trading tech books here  books2 - QUANTLABS.NET We delve into the intricate mechanisms of the stock market, highlighting how Rentech's sophisticated quantitative modeling and data-driven investment strategies could have possibly predicted and benefited from this phenomenon. However, with a focus on potential insider trading, we question whether the Securities and Exchange Commission (SEC) should be investigating this situation.   Renaissance's Meme Stock Bet Insider Trading or Savvy Investing? - QUANTLABS.NET The podcast also considers the broader implications of Rentech potentially being involved in this 'Meme Stock' rally, discussing the potential damage to their reputation, potential regulatory changes, and the effect on the general stock market. The participation of other traders and potential collusion via social media are other facets explored in relation to this complicated issue. The potential consequences of the SEC finding evidence of wrongdoing within Rentech are also considered, with the discussion speculating on the possible outcome of hefty fines, criminal charges, and reputational damage. We emphasize the broader message such verdicts would send to other hedge funds and the critical importance of ethical investing. Despite the potential risks, the discussion acknowledges the possibility that if no wrongdoing is found, this venture could be considered a successful well-timed strategy, which could inadvertently solidify the reputation of Rentech. The podcast concludes with the potential impact this 'Meme Stock' saga might have on future regulations aimed at preventing market manipulation and protecting investors, acknowledging that increased participation of retail traders, prompted by social media, could influence stock market volatility and unconventional investment strategies. Sign up for our newsletter for more insights into market trends and get free trading books at quantlabs.net books.

Join Brian from Quantlabs.net in this episode as he unveils the impressive revamp of their website, enhancing user experience to new levels and offering a glimpse into the possibilities offered by their services. Understand the evolving landscape of algo trading, the challenges of credibility it faces, and how Brian and his team are finding success through empirical evidence of their trading prowess.   Get your free trading tech book PDF books2 - QUANTLABS.NET Learn about the exciting world of algo trading and auto trading, and how platforms like TradingView are revolutionizing the way we trade and invest. This episode gives a detailed comparison between algo trading and automated trading, underlining the feasibility of the latter for everyday people. Discover how TradingView is experiencing a boom in the social trading community, surpassing giants like Bloomberg and CNBC in terms of audience size. Algo Trading, Transparency, and Building Your Trading Journey with Quantlabs.net V2 - QUANTLABS.NET This episode also dives into portfolio management, emphasizing the importance of being proactive in managing your own investments rather than heavily depending on financial advisors. Explore the potential risks and benefits of integrating cryptocurrencies in your portfolio and gain insights into both passive and active portfolio strategies. Last but not least, the episode stresses the need to showcase real trading results, sift through the lessons learnt from them, and maintain an active awareness of the financial markets. Join the experience to challenge your perceptions about trading, break free from traditional approaches, and dive into the vibrant world of algo/auto trading.

On this episode, I expound on the extraordinary life and legacy of Jim Simons, a mathematician, successful hedge fund manager, and a philanthropist who made an unwavering impact on Wall Street. Simons, the founder of Renaissance Technologies is widely considered one of the world's greatest investors. Get your free trading tech books here books2 - QUANTLABS.NET In the late '70s, Simons switched career paths and entered finance, founding the company we know today as Renaissance Technologies. This marked the beginning of his journey into quantitative finance, an industry to which he would become one of the most innovative pioneers. As I explain, Simons always sought out PhDs in Physics, math, and computer science rather than MBAs, opting for the deep technical knowledge these fields offered - a trend that marks Wall Street's hiring culture today. Simons was driven by the power of data analysis and was always on the lookout for hidden patterns in data that the human eye could not perceive, leading to Renaissance Technology's extraordinary success. We also delve into how Simons' legacy continues through his philanthropic efforts especially in the sphere of mathematical and scientific education. His foundation, the Simons Foundation, has donated billions of dollars to these causes, making a significant impact and demonstrating his deep belief in education. Simons' life stands as a testament to the power of applying a scientific lens to complex problems and his pioneering spirit in the world of finance. He will be long remembered as a visionary in his field. Join me in looking through the life of this extraordinary man and dive into the intricacies that led to his phenomenal success.

In this enlightening conversation, a veteran developer advocate from KX unfolds critical insights about the compelling database, KDB Plus. Journeying through her personal evolution from an apprentice to an advocate, she delves into the launch and progression of KDB Plus and the cost columnar structure that enhances its query efficiency. This is an interview and webinar presentation with Michaela Woods who is Developer Advocate at KX. Beyond the basics, she highlights the extensive resources available for learning KDB Plus — from books to online training academies – and emphasizes the significant role of community spaces such as forums and online platforms for knowledge share and query solution. Ger your free trading tech books here books2 - QUANTLABS.NET More details here Why KX kdb+ and Q Should Be Your Next Financial Power Tools - QUANTLABS.NET The discussion takes a turn, exploring KX Academy's course structure designed to equip learners with fundamental to advanced understanding of handling massive time-series data and creating custom functions. Demonstrating the sandbox feature, Michaela highlights the beauty of learning in a hosted environment without the need for installations. Michaela concludes with a glance at their advanced courses, tailor-made for individuals wanting to master KDB Plus. Moving on, the conversation introduces a more modern development – PyKx. Shedding light on PyKx's rising popularity, it describes how Python integration is expanding KDB Plus's accessibility to software applications with its enticing interfaces for new users, without replacing the underlying Q language. Discussion further covers the inclusive certification programs by KDB and its successful implementation in the manufacturing sector. Lastly, it dives into the recently launched developments: KDB AI and KDB Insights, exploring how they are innovatively reshaping data storage, retrieval, and cloud-based workloads. This comprehensive discussion is designed to equip developers and beginners alike to leverage KDB Plus and PyKx for efficient time-series data handling and enhanced data analysis.

In this enlightening episode, join our host, Brian from quantlabs.net as he delves deep into the exciting world of latency and high frequency trading, with a primary focus on C++. This episode promises to pull you deep into the nuts and bolts of performance optimization, providing a comprehensive exploration of latency-sensitive applications and how they impact the Memory Subsystem. It's a world of code, geekiness, and high-level trading intelligence that promises to inform and captivate any tech-minded enthusiast.   Get out FREE trading tech books here    Follow along as Brian navigates a revealing article found on the CPP subreddit, labeled 'Latency Sensitive Applications and the Memory Subsystem: Keeping the Data in the Cache - Johnny's Software Lab'. From exploring the advantages of hardware-based HFT systems and the importance of effective cache management techniques - the conversation spans critical areas of software and hardware performance optimization in trading environments. Not just an overview, Brian also takes a deep dive into coding techniques designed to minimize latency and maximize performance. You'll gain insight into coding examples, discussions around the use of hardware and software cache warming, the impact of different caching approaches on performance, and why a customized, well-articulated architecture is a must-have in achieving low latency. Get on our Discord to talk about this  Beyond just coding, Brian also looks at the broader landscape, touching on the importance and role of various hardware in reducing latency and even extends the conversation to the cloud space, touching on the challenges and opportunities in leveraging Cloud vNICs. Demystifying Latency: A C++ Deep Dive into High-Frequency Trading - QUANTLABS.NET Whether you're interested in quant, trading, or improving your understanding of C++ techniques for optimizing latency, this podcast promises to leave you with a wealth of knowledge and insights that will help you navigate the world of high-frequency trading. Come along for this engaging journey through the intersection of streamlining software performance and trading technology.

G'day everybody! In this episode, we delve into the nitty-gritty and complex world of high-frequency trading (HFT). Through a detailed analysis of a recent technical post on quant.stackexchange.com, we explore the critical role of market-makers in HFT, their requirements, strategies, and response times in dynamic market conditions. Get on our Email Newsletter while getting some free tech trading books books2 - QUANTLABS.NET   Market makers operate swiftly, adjusting their quotes to reflect real-time market dynamics. The time taken for sending quotes and receiving a hit in HFT could be around 1.5 milliseconds, which exemplifies the speed with which these players operate. The actual figures might vary, depending on the sophistication and speed of the underlying infrastructure. Talk about this on our Discord When a quote is hit, the response time isn't instant because of the computational processes required. Market makers must analyse the complexity of their algorithms, prevailing market conditions, and improve their technical framework for better efficiency and reduced latency. Regulatory and operational considerations also play a part in their decision making.   High-Frequency Trading: Unveiling the Market Maker's Dance - QUANTLABS.NET   Needing no cooling-off period nor limitations, the speed at which market makers replace their quotes depends on the computational capability of their system. They rapidly adjust their quotes in high-frequency trading. If multiple quotes are hit simultaneously, they reassess their strategies, potentially widening their spreads or dynamically adjusting their pricing to manage their risk exposure. Don't be fooled into thinking it's all about speed, though. High-frequency trading also necessitates technologically advanced data processing capabilities, refined algorithms, sophisticated risk management models, and constant vigilance of regulatory compliance. Market makers must be continually looking for strategic enhancements in each of these areas to maintain a competative edge. All things said, this is a fascinating peek into the complex world of HFT and market making. If these concepts intrigue you, perhaps it's worth delving deeper to get a better understanding of what's happening behind the scenes in the world of finance.

Join Brian from Quantlabs.net as he demystifies the world of Forex trading, uncovers the potential origins of Bitcoin, and discusses the evolution of his website, introducing the newly launching Quantlabs.net version 2. He debunks the often overemphasized credibility of 'verified trading gurus' and underlines adaptability and transparency as key aspects of successful trading.   Get your free trading tech books books2 - QUANTLABS.NET Delving into the enigmatic origins of Bitcoin, Brian presents a provocative theory suggesting its creation might be linked to the US intelligence services. By his referencing the NSA and the Bank of International Settlements, he raises fascinating inquiries into the origin and potential influence of Bitcoin.   Demystifying Markets, Unveiling Origins of Bitcoin, and Charting the Future - QUANTLABS.NET In a conversation about the uncertain future of cryptocurrency, Brian provides valuable predictions and reflects on the potential impact of emerging legislative structures in England, Russia, and China. This debate is pivotal for anyone seeking to understand the future of this volatile investment sector. Furthermore, Brian discusses the impending shift in real estate dynamics, exploring potential changes to the landlord-tenant relationship and rent control legislation. With a spotlight on independent landlords, this discussion serves as a comprehensive guide to anyone interested in property investment or the future of the real estate market. Moving to the technological aspect of trading, Brian shares his experiences transitioning from WordPress to Django for his website's advancement. This valuable insight perfectly serves individuals and businesses considering a similar switch to increase control and counter traffic decline. The episode concludes with Brian showcasing a revolutionary trading system that integrates TradingView and TradersPost.io, aiming to optimize trading processes and decrease trader workload. Both trading novices and seasoned investors will find this discussion enlightening and potentially transformational for their trading practices.

In this episode of QuantLabs, our host Ryan delves into the world of algorithmic (algo) trading within the realms of real crypto exchanges and Bitcoin ETFs. Drawing from his experience with TraderPost.io, Coinbase, and Interactive Brokers, he provides an insight-rich perspective on active investment in the volatile crypto market.   Get your free trading tech books books2 - QUANTLABS.NET Listen in as Ryan debates the pros and cons of trading crypto on platforms like Coinbase or Interactive Brokers, versus opting for ETFs such as BlackRock. The episode sparks an intriguing question for traders: "Will the allure of high returns from altcoins triumph over the safety of Bitcoin ETFs or vice versa?"   Should You Algo Trade with a Real Crypto Exchange or a Bitcoin ETF Only? - QUANTLABS.NET Discover the role that firms like BlackRock play in influencing Bitcoin prices, and learn about potential conflicts of interest in this domain. With a consideration on the differences in operational hours between crypto exchanges (24/7 trading) and traditional ETFs. Ryan underlines the significance of customization and flexibility in algo trading. This episode is a treasure trove of knowledge about aspects such as risk tolerance, price control, market participation, and algo trading techniques. Whether you're a full-time trader or a casual one, this guide will help you make calculated decisions in your investment journey. Dive into discussions about the complexity and security concerns related to real exchanges, the reduced risk and high liquidity options of Bitcoin ETFs, and the factors to consider when deciding between the two. You will also gain insight into relevant market conditions, potential benefits, and drawbacks for each option.   Get your free trading tech books books2 - QUANTLABS.NET Cap off this episode with a detailed discourse on BlackRock ETF, Coinbase, and the impact of shifting market conditions on trading decisions. Don't miss out on comprehensive price analyses and a chance to interact with a fast-growing trading community. Tune in to QuantLabs for insights and resources! Happy trading!

Join Brian as he shares valuable insights about the transition from an MBA Finance degree to a career in Algo Trading. As technological advancements spiral, the finance industry is rapidly evolving with a focus on algorithm trading, which currently represents over 80% of all trades. In this episode, Brian points out the financial acumen, analytical competence, problem-solving skills, and trading knowledge required for the transition.   Get your free trading tech books to enhance your algo journey books2 - QUANTLABS.NET In this transformative progression, Brian emphasizes the importance of Python and its libraries for beginners and C++ for advanced trading. However, one must not forget the main aim is to showcase trading skills, not language proficiency. Brian provides information about the Algo Trading concepts, specifically backtesting, different order types, and different algorithmic trading strategies, to aid listeners in their journey. Alluding to the stiff competition in the finance industry, Brian advises listeners to acquire professional accreditations like a Chartered Financial Analyst (CFA) or a Certified Algo Trader to hone their skills and stand out. He also recommends getting involved in LinkedIn groups, webinars, conferences, and coding competitions to further expose their skills. Finally, Brian talks about the necessity of not just having theoretical knowledge but also practical experience in trading real money. He warns his listeners of the fierce competition, especially from Chinese firms, and the importance of staying updated with the latest technology and quant analysis techniques. For those aiming for the best-paying jobs, Brian advises to go all in - equip yourselves with degrees and recognitions from top universities, acquire a CFA, focus intensely on your coding and trading skills, and finally, be prepared to face a challenging and competitive environment. Tune in to this informative talk and embark on your journey from an MBA Finance degree to a successful Algo Trader.

Welcome to the tutorial session for automated cryptocurrency trading. Brian from quantlabs.net will take you through the process of establishing live automated trading on your TradingView account with TradersPost.io and Coinbase. This highly informative discussion, recorded on April 23rd, 2024, explores the seamless connection between these platforms, enabling live trading and automated trading using Coinbase, currently the only supported broker for Traders Post IO when it comes to cryptocurrencies.   Automate Your Crypto Game: TradingView, TradersPost.io, and Coinbase - QUANTLABS.NET   Get your free trading tech books https://quantlabs.net/books The talk further elaborates on the real-time support of Coinbase and anticipates the addition of Kraken broker. Brian helps you navigate through the setup of TradersPost.io and TradingView with his YouTube video playlist, offering detailed insights into payload, messaging, etc., essential for setting up automated trading. There is also a mention of the Traders Post IO's auto-submit option that allows fully automated trade setups once the user becomes a paying customer and gains confidence in the workings of the system. The tutorial provides a Canadian perspective, pointing out the limitations of certain countries in trading US dollar in Coinbase and Kraken. The discussion delves deeper into the creation of alerts in Bitcoin and Ethereum, the triggering of signals into TradersPost.io, and the importance of familiarizing yourself with the full features of TradersPost.io before starting live trading. Successfully managing your position sizing is another critical topic that is covered. You will learn about the different options available, like trading a percentage of your portfolio. This can also vary based on the size of your portfolio. There is also the option to override Traders Post IO settings right from the Pine script of Trading View. The tutorial highlights the importance of understanding the options and using the Traders Post IO's support for any assistance. Finally, the tutorial walks you through the Coinbase section of the TradersPost.io account, ensuring it's live and enabled. On imminent trading, you either approve or reject the order manually or opt for an automated trade. This allows for a smooth trading experience without having to worry about constant maintenance or sitting by a computer placing orders manually. Brian wraps up by inviting those interested to join the conversation on his Discord server. He also encourages viewers to sign up for his newsletter for the latest updates and gain access to quantlabs.net books. Overall, this talk gives a comprehensive overview of the seamless trading experience between Coinbase, TradersPost.io, and TradingView.

Hello listeners, Brian from quantlabs.net here. In this episode, I discuss an intriguing article I read on hedgeweek.com. The title of the article was 'Quant Aspect Up 21% on Currency Market Bets'. It caught my eye, and I wanted to break it down for you all. Aspect is a London-based quant hedge fund with a substantial 7.5 billion. It managed to score a 21% return in its flagship fund in 2021, thanks mainly to its currency market and commodities bets. As a result, Aspect scored above the 14% average for trend following funds and 3% average for discretionary macro managers over the same timeframe.   Get your free trading tech books books2 – QUANTLABS.NET   The majority of the firm's returns came from dispersion in currencies and commodities. These were the most profitable areas given that US market performance has been lackluster recently. Commodities, especially gold and silver, were also performing well, although they dropped off a bit due to an expected US market rally.   Join our Discord https://discord.gg/RGsuVBhVAe Aspect's market-following trading strategies capitalized on a strengthening dollar, shorting the Japanese Yen and the Swiss franc - some of the year's worst-performing major currencies. Furthermore, the firm has been subtly adjusting its commodities position, lowering its stakes in cocoa after a record high while increasing exposure to gold and oil amidst escalating tensions in the Middle East. What I've noticed is how the US markets have a significant influence on global trading trends. For those interested in delving deeper into this topic, check out the link to my Discord server and join my newsletter at quantlabs.net/books for more insights and free trading tech books in PDF format. Tune in to demystify the complicated world of trading currencies and commodities with me, Brian - your guide to understanding the global market pulse.

In this episode, Brian from quantlabs.net takes a deep look at the international expansion of Chinese quantitative hedge funds. Drawing insights from an article on hedgeweek.com entitled "Chinese Quants Look to International Expansion," he analyzes the implications and potential opportunities arising from this trend. Chinese quant firms are rapidly gaining attention in the investment world and their potential for expansion beyond China is massive. Get your free technical trading books here books2 - QUANTLABS.NET Brian underscores how increased domestic scrutiny from Chinese regulators has led some Chinese quant funds to escalate international activity. For instance, companies like MS Capital and DH Fund Management are ramping up their overseas operations. Despite the prevailing pessimistic views about the Chinese market, Brian observes that the Chinese stock market seems to be stabilizing and showing signs of improvement. Citing examples of Chinese quant funds broadening their horizons, Brian recognizes the strides made by MS Capital and DH Fund Management. Both companies are evolving their strategies by attracting offshore investors and prepping to venture into global markets. Even the Beijing-based Ubiquant is planning to establish a U.S. office. The rate of international expansion for Chinese quant hedge funds is accelerating due to domestic market regulations. Finally, Brian also mentions possible investment opportunities in these emerging Chinese quant funds for Western investors. The episode ends with Brian encouraging listeners to join his newsletter and the QuantLabs Discord server for more insights into these promising markets and potential investment opportunities.   https://quantlabs.net/blog/2024/04/a-deep-dive-about-coming-chinese-quant-firm-international-expansion/

Welcome to another episode with Brian from quantlabs.net, recorded on the 22nd of April. In this episode, Brian explores two significant forum posts that have recently caught his attention on quant.stackexchange.com. The central theme revolves around resources to learn algo trading quant development. Our host provides some impressive insights that could be beneficial for those interested in quantitative trading. Get your free trading tech books here books2 - QUANTLABS.NET A user's question on the forum sparks the discussion - the user is a full-time stack developer for three years and is now interested in learning algo trading quant dev development. They are seeking advice on resources, books, and suitable programming languages to learn. Brian shares one effective resource he stumbled upon - Wilmot.com. It isn't just a job-posting site, but it also includes details on who the job postings are for. The likes of JP Morgan, Goldman Sachs, HSBC are just few names from the list. This resource might be useful for anyone looking to delve deeper into the quant industry. Moving on, Brian discusses a vast list of books available on quant.stackexchange.com that can be beneficial for anyone venturing into quantitative finance. He warns about the potential for analysis paralysis given the extensive list. He also shares his top picks from the list, including books from Mark Joshi and Dr. Ernie Chan, and more. He also alludes to some upcoming interviews with industry experts like Robert Pardo and the later Dr. Ernie Chan on his YouTube channel and podcast. Apart from those, Brian recommends three more books to dive into quantitative finance. They include 'The Concept of Practiced Mathematical Finance' by Mark Joshi, 'Paul Wilmont on Quantitative Finance' by Paul Wilmont, and 'Options, Futures, and Other Derivatives' by John Hall. He advises new entrants to start with Paul Wilmott's book series which covers all major components of quant. Finally, Brian introduces TradersPost.io, a service that can help interested individuals to get up and running quickly in the world of algorithmic trading with minimal programming. Once again, he invites listeners to join his Discord community to discuss these topics more and sign up for his email list for some big announcements. He concludes the episode looking hopeful to get Dr. Ernie Chan again on the show for another interview on his latest company launch on machine learning.

In this informative and thought-provoking episode, Brian from quantlabs.net discusses a significant topic pertaining to the future of Quant. He addresses a subreddit post regarding the inherent demand for quant in the next five to ten years. While highlighting the undeniable potential impact of AI on the growing industry, he also offers listeners invaluable advice, critical insights and answers to various comments from the online community. Brian contemplates on the matter of AI developing to replace many sectors, regardless of seniority, and further changing the landscape of Quant. Utilizing both ChatGPT and Google Gemini's latest version, Brian encourages users to employ AI to generate lucrative ideas and implementations. He responds to a comment suggesting domination by those with PhDs in statistics and physics, and shares his insights on the drastic influence AI will have on making markets more efficient. Moreover, Brian delves into further comments about the future of math PhDs in the industry. He dissects how AI influences the software engineering field and the potential implications for quant and modelling research. Brian ponders over a statement suggesting no need for quants in the future due to market efficiency and draws parallels with the SEO industry. The discussion further extends to the introduction of AI in markets and the resulting consequences for various sectors. Drawing the podcast to a close, Brian addresses several humorous and thought-provoking comments, leading back to the role of AI. He provides a fitting conclusion to the conversation about the future of quant, emphasizing both the potential opportunities and threats AI imposes. For individuals keen on learning more about the quant world, Brian points you to informative resources on quantlabs.net and invites you to engage in the discussion on their Discord server. Tune in for unique perspectives and valuable insights.

In this insightful episode, Brian from quantlabs.net reveals how to maximize your trading experiences using TraderPost.io and Interactive Brokers. This step-by-step guide covers setting up and connection processes, benefits of the platform, and how to deal with potential difficulties. From Interactive Brokers' unique single connection feature to TraderPost.io's automatic daily reset option, this episode provides all the need-to-know details. Learn how to set up confirmation via email for every trade, ensuring utmost security and peace of mind. In the latter part of the discussion, Brian simplifies TradingView's alert box setup with practical tips and addresses the common confusion between strategy definitions in TradingView and TraderPost.io. This segment is invaluable for anyone seeking to harness the full potential of these incredible platforms. The episode further delves into TraderPost.io's strategic code usage with Pinescript and its seamless integration with popular platforms like TradingView and Interactive Brokers. For safeguarding your transactions and mitigating risks, solutions are shared that are proven to be effective and reliable. Additionally, Brian unveils the future plans of TraderPost.io involving support integrations with renowned brokers such as Coinbase and Kraken. This episode not only offers tangible tips but also provides an adaptable outlook on trading techniques in relation to market changes. It is an essential listen for savvy investors and beginners alike who want to explore and excel in automated trading.

In this instructive video, Brian from SmallLabs.net provides a detailed walkthrough of TraderPost.io's back-end functionalities. This trading solution hosts a range of user-friendly features - from custom code support to Discord bot creation, and comprehensive live trading options. Get your free trading books at https://quantlabs.net/books/ One of TraderPost.io's most impressive features is its extensive webhook connectivity, enabling users with no programming knowledge to execute trades in supported platforms such as TradingView. Moreover, the platform supports a plethora of reputable live brokers, including Interactive Brokers, TradeStation, TD Ameritrade, and Coinbase, with more to come in the future. Prior podcast here  Your Solution for Executing Trades with TradingPost.io - QUANTLABS.NET In this detailed discussion, Brian focuses on the importance of understanding the asset classes available, the associated costs, and selecting the correct account tier based on desired asset class. Explore the potential of trading three asset classes at a cost of $200 per month, and the restrictions linked with opting for a single asset class. Cryptocurrency trading is highlighted as a case study, with emphasis placed on the volatility of the asset class, and the options available for trading ETFs through Interactive Brokers. In addition, Brian speculates on the future inclusion of Bitcoin and Solana on the same platform. The video also delves into the benefits of employing TradingView's open-source strategy, providing viewers with a guide on selecting their preferred strategy, and utilizing the platform's extensive Pine script library. We also explore the challenges and potential solutions related to linking with the Trader Workstation (TWS), and connecting with Interactive Brokers via TradingPost.io's web portal. In regards to security, Brian discusses the risks associated with connecting to a broker via a public URL or webhook, while simultaneously highlighting how TraderPost.io mitigates such concerns by ensuring a secure connection with the chosen broker. Finally, dealing with the setbacks of high-frequency trading on TradingView and TradingPost.io is discussed, alongside advice on testing paper trading for Interactive Brokers and live trading on Coinbase. To conclude, viewers are invited to join the SmallLabs.net Discord group and email list, and are given a sneak peek into upcoming plans for a new website.

Join Brian of QuantLabs.net as he delves deep into the world of automated trading. In this podcast, he shares his insights into the limitations of TradingView's automated trading feature and discusses some alternative solutions. Discover how to work around these limitations and take your automated trading strategies to the next level. Brian also introduces tradingpost.io, a service that promises to simplify the process and make trading faster and easier. Throughout this podcast, Brian stresses the importance of fully understanding the vulnerabilities of any trading system. Whether it's the potential for hacking or unexpected trading hiccups, being aware of these issues is crucial for success. As he explores the services offered by tradingpost.io, he explains what makes this platform stand out in the world of automated trading. If you've wanted to streamline your trading process but didn't know where to start, this podcast could provide the insights you've been searching for. Brian also discusses the potential benefits and drawbacks of working with multiple brokers. With a platform like tradingpost.io, managing and monitoring trades across different accounts could become an easier task. Listeners also get a firsthand account of the types of programming required for such a system. Discover why Brian believes that traders could reap considerable advantages from integrating tradingpost.io into their trading strategies. Beyond automated trading and tradingpost.io, listeners can also expect to receive insights into the latest developments in AI, brokerage support, and more. With Brian's years of experience and technical expertise, this podcast promises to deliver valuable knowledge for any trader interested in automated trading.

In this podcast episode, Brian from Quantlabs.net shares his opinions on managing open source dependencies and software upgrades, with a focus on the amalgamation of AI and expert developers. He highlights the significant difficulties these tasks can pose, but also indicates potential solutions - notably artificial intelligence (AI) co-generation techniques. Further, Brian explores the concept of code generation, and its effectiveness in completing these arduous undertakings. He puts to the test various options regarding AI, including Google Gemini and Microsoft Copilot. He underscores the key aspect of how effective the AI model depends on how prompts are formulated, commonly referred to as "prompt engineering". He showcases the power and convenience of such AI models through concrete examples, notably an arbitrage script for gold assets. The conversation also covers the accessibility of different tools, their advantages, and potential drawbacks. Particularly, the constraints and complexities of open source software such as Lama 2 and Startcoder 2 are examined. Lastly, Brian opens the door to further discussions on tools for managing software upgrades and dependencies on his Discord channel and his Sub Stack.   Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 GET OUR FREE TRADING TECH BOOKS HERE BOOKS2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack See more here Trader bryandowningqln — Trading Ideas & Charts — TradingView

Welcome to the latest episode of Brian from quantlabs.net's podcast. This discussion dives into the current debate concerning the regulation of artificial intelligence (AI) in the trading industry. Brian examines an article from risk.net which covers the concerns raised by market participants about the Monetary Futures Trading Commission's approach towards managing AI in trading. Jennifer Hahn, Chief Counsel and Head of Regulatory Affairs at Managed Funds Association, argues for leveraging the existing regulatory framework instead of developing redundant regulations. In the backdrop of the rise of web3 projects and state control over software development, Brian asks pertinent questions about the balance between upholding a free society and ensuring scams are mitigated against. Reflecting on the revolution AI has brought to trading and the risks associated with it, Brian's in-depth analysis explores how automation of trades and remote hosting of code could pose threats to not only markets but entire economies. Brian believes regulators have a role in countering systematic risks, particularly when it might threaten financial stability. Although the extent and process of regulation remain contentious. Drawing parallels from the military and banking sectors, he raises concerns about the seeming lack of regulation on AI in the trading operations of large companies. He calls for scrutiny of the practices of large trading entities like Citadel, Black Rock, and Vanguard. Wrapping up the episode, Brian invites his listeners to join discussions via the podcast as well as on platforms like Substack and TradingView. With his hard-hitting reflections on a topical issue, this podcast sparks profound thoughts on the intersection of AI, trading, and regulation.

In this riveting episode, we dive into the world of algorithmic trading with one of its pioneers - Robert Pardo. With decades of market analysis and strategy creation under his belt, Pardo is an expert high-performance trader, application professional, and the founder of Pardo & Company. A man of stellar reputation, his trading program XT99 Diversified has been recognized for its top-tier performance over and again. Robert Pardo, widely recognized as a trading industry titan, has been a consultant to prestigious trading firms such as Goldman Sachs and Daiwa Securities America. His groundbreaking efforts in the industry are unsurpassed, particularly his creation of Walk Forward Analysis - the gold standard in strategy validation.   Get all links here  What are Your Questions Algo Trading Legend - Robert Pardo - QUANTLABS.NET  In this enlightening podcast episode, we offer the opportunity for our listeners to forward their pressing questions to this industry pundit by emailing us. Don't miss this chance to gain invaluable insights from an industry legend. Send us your questions, subscribe to our podcast to keep abreast of this impending interview, and join our discord server for engaging trading discourse. Also, get free trading book PDFs at quantlabs.net/books. Stay tuned as we have a new, advanced, and highly flexible website in the works that will provide a customized strategy integrating seamlessly with our current strategies and analysis. We are excited to bring you something truly special so watch this space!  

This podcast by Brian from QuantLabs.net dives into the world of High-Frequency Trading (HFT) and the role of KDB+ in this domain. KDB+: Developed by KX, KDB+ is a high-performance software used for data handling in HFT. It excels at working with large time-series datasets and is known for its: Efficiency Uncomplicated code structure Python integration Cloud interoperability KDB+ and Ticker Plant: Ticker Plant can be used to feed data into KDB+, making it a popular combination for HFT applications. Cost: A major barrier to entry for KDB+ is its high cost, estimated to be around $100,000 per year. This limits its use primarily to the well-funded fintech industry. Future Potential: Despite the cost, KDB+ remains a dominant player due to its performance and features. Brian discusses the potential of KDB+ to evolve even further with advancements in technology and AI. Call to Action: Brian invites listeners to join his Discord community to discuss KDB+ and related topics. Exploring the Power of KDB+ for High-Frequency Trading and Data Analytics - QUANTLABS.NET Welcome everyone, Brian from QuantLabs.net is here with another intriguing episode. In this episode, Brian dives deep into the world of High-Frequency Trading and advanced data analytics, emphasizing the role of KBD+ in it. Touching upon a previous episode of the podcast on the same topic, he delves into the intricacies of software like the Ticker Plant. Brian explains that KDB+, produced by KX, is a high-standard enterprise-level software known for its efficient data handling capabilities. As he deconstructs the workings of this software, he highlights how Ticker Plant could write all incoming records to a log file, pushing all data to the RDP. This software, although widely unknown, is an industry standard. The focus then shifts to the price aspect of KDB+, and the barriers it poses for widespread market adoption. Discussing a comment on Hacker News, Brian brings to light the exorbitant cost of KDB+, estimated at around a hundred thousand dollars per year. As per the comment, software is extremely lucrative and can only be afforded by the fintech industry. Despite the cost, KDB+ comes highly praised. A comment Brian brings up highlights KDB+ as an elegant solution for running analytics on large data sets, especially those with time series. Known for its performance, uncomplicated code structure, Python integration, and cloud interoperability, KDB+ has been a dominant player in electronic trading analytics on Wall Street for over 20 years. In conclusion, Brian discusses the potential of KDB+, which opens avenues for potential business opportunities. He emphasizes how innovations in technology and AI could lead to exploring beyond the limitations imposed by network cards. Following his exploration of KDB+ and its potential, he invites listeners to join his Discord community and actively engage in stimulating discussions.   Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Get our free trading tech books here books2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack

Dive into an insightful discussion with Brian from QuantLabs.net, as he takes us through the challenges and prerequisites of becoming a successful quant developer, the highly intriguing intersection of finance, math, and computer science. This episode is a comprehensive guide that unravels the essential skillsets, high-stakes industry expectations, and potential pathways for ambitious quant aspirants. From mastering foundational knowledge in math and English, to proficient coding and impressive trading records, understand the key requirements to thrive in the industry, be it in major financial entities, startups, or small firms. Brian illuminates the rigorous educational prerequisites, emphasizing the need for a profound understanding of mathematical concepts, computer languages, financial markets and instruments, and risk and analytics management. Understand the importance of participation in competitions, contributions to open-source projects, and showcasing coding abilities to enhance your career prospects. The podcast also conducts a comprehensive analysis of requisite tools such as Python, Excel, C++, MATLAB, FPGA, SQL, machine learning libraries like TensorFlow and PyTorch, and more. All while emphasizing the importance of soft skills, statistical model understanding, and prowess in programming and machine learning. This illuminating examination concludes with a comparative analysis of quant developer's salaries across various regions. From $118,000 in London to surprisingly lower figures in Canada and Singapore, discover the promising markets, factors affecting career moves, potential earnings, and prestigious firms like Citi and JP Morgan. Get insights into starting your own ventures, becoming a consultant, and resources for further learning. All this and more in this wide-ranging guide for aspiring quant developers!   Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Get our free trading tech books here books2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack

Welcome to another episode of the Quantlabs podcast. In this episode, Brian delves into the exciting and ever-evolving world of Quant development as it applies to high-frequency trading (HFT). High-frequency trading is a complex and nuanced topic, but Brian brings it down to earth with practical insights and thoughtful commentary. He sheds light on the importance of retail trading bots, the innovative use of Discord and Telegram as trading platforms, and the rise of unique Cryptocurrency trading techniques.   Exploring High-Frequency Trading and Data Processing with DPDK - QUANTLABS.NET One of the highlights of the episode is when Brian introduces us to the concept of Data Plane Development Kit (DPDK)—an intriguing open-source project that take centre stage in discussions around rapid packet processing. This segment not only clarifies what DPDK is and why it matters for high-frequency trading, but also explores the potential of using this library for high-speed data processing in large scale applications. A deep dive into the nuts and bolts of the open-source project, its licensing, users, functionality, and supported hardware follows. The episode ends with an invitation for listeners to engage further on these topics via Discord or delving deeper with materials available on Substack. For those interested, Brian also generously offers access to free tech books he's written, available at quantlabs.net. This podcast provides a fountain of knowledge for anyone interested in the intersection of Quant development and high-frequency trading, regardless of their level of expertise.   Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Get our free trading tech books here books2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack

Hello, everybody. Brian here from swanlabs.net. On March 25th, an insightful article was shared with me via my usual source. The piece originated from eFinancialCareers.com and reveled in the surprising new hiring trend within high-frequency trading firms: recruiting video game CEOs and former UBS directors. Usually, these wouldn't be the people you'd expect leading the charge in high-frequency trading, but from an executive standpoint, it can make a lot of sense. It's interesting to note that pathways into a hedge fund or high-frequency trading are not always straightforward. An individual to highlight in this unique hiring trend is Heath Newton, who joined Susquana as a software engineer. Having spent nine years at Bloomberg and thirteen years as the CEO of independent game studio INOVAE, Heath offers an unconventional background to this financial niche. Another mover in this space is Domenico Mangieri, who's pathway into Jump Trading was a little more traditional - starting in finance with an AI firm Altair before joining UBS and Morgan Stanley. I found this development quite fascinating - these unusual hiring patterns opens up more interesting ways to enter the high-frequency trading industry. So, stay tuned, and don't forget to pay attention to my links for Discord, Substack, and the books I have on offer. Have a good day!   Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Get our free trading tech books here books2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack   efinancialcareers.com/news/high-frequency-trading-engineer-video-games-ubs

Welcome to the latest episode of our podcast where host Brian from quantlabs.net speaks on the fascinating world of High Frequency Trading (HFT). A shout rests on his lips for his audience as he appreciates their unwavering support that's taken his podcast to new heights on both YouTube and various podcast networks. Brian retreats into the two areas his listeners crave - High Frequency Trading and Trading Systems. Dive into the insights shared by Naveen Kumar Suppala, a Software Development Leader and Principal Global Quant, Research and Dev professional based out of India. Suppala brings to the table a series of articles filled with the golden nuggets of wisdom on key subjects such as the memory layout, HFT C++ core techniques, low latency programming, market order vs limit order backtesting, kernel bypassing in HFT, and more. A goldmine of valuable information awaits as we traverse through these various areas. The journey doesn't stop here. Brace yourselves as we navigate through a Github repository filled with the intricate concepts of the Operating System (OS). Find out how some HFT shops customize the Linux kernel and build systems on top of these tailored operating systems. The repository covers diverse areas such as hardware basics, the layers involved in an OS, task scheduling, multitasking issues, synchronization objects, and much more aimed at enhancing your understanding of the OS nuances. Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Get our free trading tech books here books2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack A call to action from Brian invites you to engage in insightful discussions over on his Discord channel, receive updates about his trading on Substack, and explore the trading books via quantlabs.net. Dive into the episode to amplify your knowledge on High Frequency Trading and Trading Systems!   A Deep Dive into Techniques, Tools, and Systems - QUANTLABS.NET linkedin.com/in/naveensuppala/recent-activity/articles/   github.com/braboj/tutorial-os?tab=readme-ov-file#operating-systems

Hello everyone! In this episode, our host, Brian from quantlabs.net, dives into a discussion regarding the upcoming book, "C++ High Performance for Financial Systems," by Ariel Silihan. Throughout the podcast, Brian provides an overview of the book and shares his opinions about the chosen publisher, PACT. The book promises to guide experienced programmers seeking to break into the finance industry by teaching them how to build high-performance trading systems. It covers subjects such as system design and architecture, low latency strategies, risk management, and machine learning. Although the author is highly capable, Brian presents some concerns about the publishing company's credibility as it has been criticized for its lack of editorial contribution. Brian also talks about the inherent challenges in teaching these complex concepts through a book, given the rapidly evolving landscape of this field. He also provides some insights on what it takes to gain a real competitive edge beyond what one can learn from such books. It's suggested that the book is primarily intended for experienced C++ developers looking to enter the finance industry and anyone interested in creating scalable, robust trading systems. Familiarity with C++, basic understanding of finance, and trading concepts is assumed for readers.   reddit.com/r/cpp/comments/1bjkkos/c_high_performance_for_financial_systems/?rdt=64280 amazon.ca/High-Performance-Financial-Systems-leveraging-ebook/ Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Get our free trading tech books here books2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack Although the helpfulness of the book is still to be determined, Brian extends an invitation to discuss the subject further in his Discord community. Listen to the podcast to get a full understanding of Brian's take on this upcoming release, and don't miss his recommendations for learning and trading!    

Welcome everyone to another episode with Brian from QuantLabs.net. Our topic today is the striking performance of systematic hedge funds in the first quarter of 2024. We delve into a recent article from Hedgeweek.com revealing their significant outperformance against other strategies under erratic markets triggered by geopolitical tensions. These hedge funds, which use algorithms to find investment-worthy market trends, have seen a nearly 9% gain in the first two months, far surpassing the wider 2.6% average, drawing from data offered by Barclays Prime Brokerage Division. This observation aligns with our own analysis, which has identified particular sectors that have outperformed the S&P 500. However, not all is smooth sailing, the current American market is heavily skewed, notably by NVIDIA. As we explore instruments to invest in, we emphasize prioritizing low volatility to avoid large drawdowns, which can jeopardize your performance. Hence, it is crucial to design a system that will enable you to find a consistent metric for your volatility threshold, ensuring you invest only into suitable instruments. Despite the volatility of the global market, which impacts different regions and assets differently, the use of systematic strategies results in appreciable gains when greater risk is embraced. Nevertheless, even those funds with lower risk thresholds have also made substantial gains. Lastly, we stress the importance of not basing your trading on opinion or hunches, but on data and strategies instead. Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Get our free trading tech books here books2 – QUANTLABS.NET Know what I trade on my Substack Quantlabs Substack | Substack To stay updated with my trading insights and engagement, feel free to join our Discord community, check out my Substock page, or sign up for our insightful newsletter. All of the details will be in the description. Thanks for tuning in! Systematic Strategies Shining - QUANTLABS.NET https://www.hedgeweek.com/systematic-hedge-funds-shine-in-q1/

In this podcast episode, Brian discusses the evolution and appeal of various programming languages, particularly Java and Python, and their roles in the development of robust, enterprise-level applications. Drawing from his extensive experience, Brian shares why Java's "write once, deploy anywhere" feature, vast standard library, strong community support, and mature ecosystem make it a popular and reliable choice for developers. He impresses upon the unique aspects that separate Java from Microsoft technologies - its independence and diversity of features.   In this fascinating episode, Brian delves into the latest advancements in the tech world, focusing on Microsoft's new technological wonder – AutoDev. This AI-driven software development framework is designed to transcend traditional code assistance tools, marking a leap towards more autonomous, efficient, and secure development methodologies.   Go here to see the question. Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2   Get our free trading tech books here books2 – QUANTLABS.NET However, Brian also stresses on the emerging power of Python and its growing significance in the realms of cloud computing and machine learning. The transition from Java to Python presents challenges - from the intricacies of upgrading the Python interpreter to the after-effects of deprecated libraries that could potentially disrupt the existing code. Java vs. Python - A Multifaceted Take on Programming Languages - QUANTLABS.NET Our conversation also branches out to the wide array of programming languages, such as JavaScript, Kotlin and C++. The pros and cons of these languages are discussed, touching on lively debates from coding subreddits. Particular attention is given to web application development technologies, including Spring Boot, React, Next, Flask, Django, and Fast API. It provides a balanced analysis, showcasing how JavaScript dominates on the front end while Python flexes its flexibility. Delving into the multifaceted world of coding and exposing the constant evolution, the episode offers effective strategies programmers can adopt to stay relevant. The podcast concludes with insights on using excel in Java's open-source project and extends an invitation to the audience to continue the conversation on our discord server.

Welcome back, everyone. This is Brian from quantlabs.net. In today's podcast, we're diving deep into the world of hedge fund internships, particularly the ones offered by Steve Cohen's Hedge Fund, Point72. These aren't your average internships. According to an article from efinancialcareers.com, the Quibus Systematic Strategies team at Point72 is paying Quant interns a whopping $25,000 per month.   Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2   Get our free trading tech books here books2 – QUANTLABS.NET This might sound out of the ordinary, but from my experience working with the Canada Pension Plan Investment Board (CPBIB), I can confirm that top-tier organizations are willing to pay top dollar for talented interns. CPBIB, regarded as a prestigious firm in Canada, was known to pay University of Waterloo interns quite generously.   High-Paying Opportunities In Trading - QUANTLABS.NET But coming back to Point72, it's not just about the money. Their internships are also tremendous opportunities for career advancement and learning cutting-edge technologies. The K-E-P-L team specializing in trading medium-frequency statistical arbitrage strategies is particularly interesting, promising lucrative careers meriting competitive pay. In 2020, their Quantitative Research Internship exclusively for PhD candidates offered a base salary between $250,000 and $300,000. This is just the base pay, not including bonuses which can catapult some interns into the million-dollar earning bracket. The bar had been set high last year when a quant teacher was offered a $300,000 case. If you're vying for a top spot in these hedge fund internships, understanding Python, C, or C++, among other languages, is essential. These opportunities aren't just limited to PhD candidates. Undergrad student positions are also available, promising a minimum salary of $240,000. Interested in such quant internships or want to share your thoughts? Visit my substack to engage in insightful discussions or check out the quantlabs.net/books to get your hands on some useful trading tech books. Thanks for tuning in!

In this fascinating episode, Brian delves into the latest advancements in the tech world, focusing on Microsoft's new technological wonder – AutoDev. This AI-driven software development framework is designed to transcend traditional code assistance tools, marking a leap towards more autonomous, efficient, and secure development methodologies.   Go here to see the question. Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2   Get our free trading tech books here books2 – QUANTLABS.NET Listen as he breaks down how AutoDev empowers AI agents to manage a broad spectrum of software engineering tasks independently. From intricate code editing and comprehensive testing to advanced Git operations, this framework is sweeping the tech world with its robust capabilities. Microsoft's AI-Driven Framework – AutoDev - QUANTLABS.NET Brian also discusses the shift in the industry as AI takes a central role, allowing developers to concentrate on higher-level strategic tasks. Learn about the rigorous evaluations AutoDev underwent and its impressive results – achieving a first-pass success rate of 91.5% for code generation and 78% for test generation. Discover how this level of automation is redefining AI-driven software engineering, setting new standards in the industry. In addition, Microsoft's other offerings, like the free Artificial Intelligence for Beginners course and Microsoft Student Learn Ambassadors program, are also highlighted in this informative episode.

Step into the world of hedge funds and quantitative finance with Brian in this riveting podcast episode from quantlabs.net. The episode kicks off with a comprehensive discussion on the basics of getting a job in a hedge fund: from academic prerequisites to critical soft skills and technical know-how. Expect an insightful walk-through on necessary certifications such as CFA, MBA, FRM, and a sneak peek on job opportunities in high-profile locations like England. GET SOME FREE TRADING TECH BOOK PDFS HTTP://QUANTLABS.NET/BOOKS Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Don't forget to subscribe to my Substack for more trading tips and strategies! Let's keep learning and growing together. https://quantlabs.substack.com/   This episode also offers a candid view on the fiercely competitive job market and strategies to stay ahead. From marketing oneself as a brand through platforms like GitHub to the importance of internships, Brian expands on emerging opportunities and the constantly changing nature of the finance industry. With banks evolving into technology companies and Goldman Sachs hiring coders, avenues for diverse skill sets are opening up in this sector. Transitioning to discussions on hedge funds, the episode shares a list of leading hedge funds, different job roles, and the corresponding compensation packages you can expect. While cautionary tales of the high-pressure and cut-throat work environment underscore the industry's complexity, the chance to work with diverse asset classes and network with talented professionals, make for a rewarding career choice. A Glimpse into Hedge Fund Jobs and the World of Quantitative Finance - QUANTLABS.NET Finally, the episode winds up with an exploration of the different types of quantitative analysts in banks, prop shops, and hedge funds. From traders and researchers to financial engineers and developers, the roles are diverse, each with its unique challenges and learning curves. Tune in for an upfront conversation on what to anticipate in the rapidly evolving world of quantitative finance.

In this episode, Brian of QuantLabs.org discusses two important topics regarding Bitcoin. Firstly, he addresses the increasing difficulty levels for Bitcoin miners, tying it back to articles from newsbtc.com. He explains their implications and how such changes affected the value of Bitcoin in the past. The conversation gets technical, touching on important concepts such as the meaning of mining difficulty and its possible impact on the price of Bitcoin.   GET SOME FREE TRADING TECH BOOK PDFS HTTP://QUANTLABS.NET/BOOKS Join our Discord for quant trading and programming news https://discord.gg/k29hRUXdk2 Don't forget to subscribe to my Substack for more trading tips and strategies! Let's keep learning and growing together. https://quantlabs.substack.com/ The second article discussed is from JP Morgan, focusing on how Bitcoin has overtaken gold in investor portfolio allocation. This part of the conversation delves into why Bitcoin's allocation to investors is 3.7 times greater than that of gold, and what this could mean in the long term. Brian also takes time to question the assumptions made about Bitcoin's demand and how the constant volatility affects perception. Throughout the episode, Brian also casts a critical eye on other crypto debates, such as the energy efficiency of Bitcoin mining and Ethereum's high gas fees. Potential futures for Bitcoin and crypto ETFs are explored too with some skepticism, as Brian questions the stability of these financial products and the viability of deriving them from Bitcoin. The episode concludes with a call to join the QuantLabs.org community for anyone keen on deepening their understanding of crypto trading.   Bitcoin Mining Difficulty and Portfolio Allocation Insights - QUANTLABS.NET