All audios from videos by Andrea Unger, the only 4-time World Trading Champion.

The end-of-month rally, also known as the "Turn of the Month Effect", is one of the most well-known seasonal anomalies in financial markets. According to numerous studies, stock and index returns tend to concentrate during the last trading days of the month and the first trading days of the new month. But does this effect still work today? In this podcast, we analyze more than 100 years of historical Dow Jones data, from 1910 to the present day, to determine whether the end-of-month rally has remained stable over time, how it behaved across different market regimes, and what may actually be causing this seasonal anomaly. The analysis is also divided into three major historical periods of roughly 40 years each, allowing us to evaluate the long-term statistical robustness of the phenomenon. We will also discuss:buy and hold vs seasonal strategydrawdowns and risk managementhistorical outliers such as 1929, 2008, and 9/11institutional flows and capital inflowspossible explanations behind the Turn of the Month EffectEnjoy listening and happy trading!

Roberto, an accountant with a strong passion for financial markets, spent years trading discretionarily, focusing mainly on individual stocks without following a truly structured method. Like many traders, this approach led to highly inconsistent results: profitable periods alternated with more difficult phases, including significant losses. Over time, the frustration became so intense that he nearly stepped away from trading altogether.Then something changed. Roberto decided to explore a different approach, built on data, clear rules, and structured processes, moving closer to the world of systematic trading. And from that point on, not only did his results begin to change. His entire way of approaching the markets changed as well: "Today, I no longer invest because someone recommended a stock to me or because I heard a piece of news. I look for data, analysis, and concrete results."In this testimonial, Roberto shares his journey, his transition from discretionary trading to a more structured approach, and the changes that helped him achieve an overall return close to +100% in approximately 18 months. Watch the full video interview below... enjoy listening and happy trading!

Manuela has been a professional Forex trader for more than two decades, and for years she traded discretionally, spending hours in front of charts every single day. Then an important question came up: how could she turn all that experience into something more solid, repeatable... and above all, transferable?That's what led Manuela to Unger Academy:

When it comes to systematic trading trading, one of the most common objections concerns the reliability of backtesting itself. Many people believe that trading systems only work on past market data and that the results achieved through historical testing have no real predictive value. And to some extent, that criticism makes sense. Achieving excellent backtest results is not particularly difficult: all you need to do is keep adapting rules, filters, and parameters to past market data until you create a strategy that appears almost perfect. The problem is that, in many cases, you are not actually measuring the true statistical effectiveness of the strategy, but simply how well it fits the historical data used to build it. And this is exactly where one of the most common mistakes in systematic strategy development comes into play: overfitting. Overfitting refers to the tendency to create systems that are too closely "tailored" to historical data and therefore tend to lose effectiveness once applied to real markets. So does this mean that backtesting is useless? Absolutely not. When used correctly, historical testing is an essential tool for evaluating the robustness of a strategy and verifying whether a market logic actually has a certain level of statistical validity. The key is understanding how to build robust, simple strategies based on realistic market concepts, while avoiding excessive optimization and overly specific parameters. In today's episode, we will explore these aspects in depth, showing practical examples and discussing several useful techniques for developing trading systems with a higher probability of remaining effective in the future. Enjoy listening and happy trading!

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