This is a summary of links recently featured on Quantocracy as of Tuesday, 04/22/2025. To see our most recent links, visit the Quant Mashup. Read on readers!
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Uncovering the Pre-ECB Drift and Its Trading Strategy Applications [Quantpedia]As the worlds attention shifts from the US-centric equity markets to international equity markets (which strongly outperform on the YTD basis), we could review some interesting anomalies and patterns that exist outside of the United States. In the world of monetary policy, traders have long observed a notable positive drift in U.S. equities on days surrounding Federal Reserve (FOMC) meetings.
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New Feature: Walked-Forward Optimal Strategy Combinations (aka “Meta Walk-Forwards”) [Allocate Smartly]Members: See the complete list of Meta Walk-Forwards In our previous post, we introduced this concept of walking forward optimal strategy combinations. In other words, were finding the optimal combination of strategies, in real-time, based only on data available at that moment in time. We call these Meta Walk-Forwards. For members who dont want the complication of handcrafting
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The unreasonable effectiveness of volatility targeting – and where it falls short [Unexpected Correlations]This is part 1 of our in-depth investigation of how quantitative risk management could help improve risk-adjusted returns: I'll explain what volatility targeting is, explore a seemingly paradoxical phenomenon, and highlight its blindspots. Volatility targetings goal is to keep an asset or portfolios volatility within reasonable boundaries, by actively adjusting exposure – its among
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Weekly Research Recap [Quant Seeker]Its time for another round of great investing research. Below is a curated selection of last weeks highlights, each linked to the original source for easy reading. If youre enjoying these posts, a like or subscribe is always appreciated, thank you for your support! And may I kindly ask you to take a moment to fill out the short poll below? Your input helps shape future editions.
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Making Factor Strategies Work for Everyone [Alpha Architect]This article explores the difference between tradable and on-paper (theoretical) risk factors in investing. Risk factors are strategies that help explain stock market returns, but many work only in theory and not in real life. Researchers developed ways to make these factors tradable by using mutual funds and ETFs, making them accessible to both large institutions and everyday investors. However,
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Machine Learning in Financial Markets: When It Works and When It Doesn t [Relative Value Arbitrage]Machine learning (ML) has made a lot of progress in recent years. However, there are still skeptics, especially when it comes to its application in finance. In this post, I will feature articles that discuss the pros and cons of ML. In future editions, Ill explore specific techniques. How Accurate is Machine Learning Prediction in Finance? Machine Learning has many applications in finance, such
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What Works Below the 200-Day Moving Average? [Quant Seeker]Given the recent market downturn, marked by the S&P 500 and the Nasdaq trading well below their 200-day moving averages, the familiar adage Nothing good happens below the 200-day moving average has once again gained traction in financial media. The 200-day simple moving average (200SMA) is among the most widely followed indicators of long-term market trends, and a sustained breach below