This is a summary of links recently featured on Quantocracy as of Wednesday, 10/22/2025. To see our most recent links, visit the Quant Mashup. Read on readers!
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The End-Of-Month Effect in Value Growth and Real Estate Equity Spreads [Quantpedia]The clustering of excess returns on the final trading days of the month constitutes a robust empirical regularity with significant implications for portfolio construction. We document a month-end premium that is both statistically and economically significant, distinct from the canonical turn-of-the-month (ToM) effect. Our strategy highlights systematic style rotationsparticularly shifts in
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Optimization: Adaptive regret for regime-shifting markets [Trading the Breaking]In our preceding discourse, we talked about the features of parameter-free optimization, a methodology designed to liberate quantitative strategists from the sinister task of parameter tuning. The allure was undeniable: escape the perilous cycle of tweaking lookback windows, volatility thresholds, and rebalancing frequenciesa process that often culminates in overfitted models, brittle
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Weekly Research Recap [Quant Seeker]Cryptocurrency as an Investable Asset Class: Coming of Age (Borri, Liu, Tsyvinski, and Wu) This paper describes 10 stylized facts about cryptocurrencies, including their 5 higher volatility but similar Sharpe ratios to equities, a rising correlation with stocks (2% to 37% post-2020) yet strong diversification benefits, frequent large jumps that complicate risk management, and the declining
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Effectiveness of Covered Call Strategy in Developed and Emerging Markets [Relative Value Arbitrage]Covered call strategies are often promoted as an income-generation tool for investors seeking steady returns with reduced risk. But how effective are they in practice? In this post, we take a closer look at their real-world performance across different markets. Do Covered Calls Deliver Superior Returns? The covered call strategy is a popular and conservative options trading approach. It involves
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Can Machine Learning Predict Factor Returns? [Alpha Architect]Nusret Cakici, Christian Fieberg, Carlos Osorio, Thorsten Poddig, and Adam Zaremba, authors of the study Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns, published in the April 2025 issue of The Journal of Portfolio Management, set out to answer a critical question: Can machine learning techniques improve the prediction of cross-sectional factor
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Can Technology Sector Leadership Be Systematically Exploited? [Quantpedia]The U.S. equity market has periodically been dominated by a few technology-driven stocks, most recently the so-called Magnificent Seven. Historically, similar dominance occurred during the Nifty Fifty era in the 1960s1970s and the dot-com boom in the 1990s. These periods of concentrated leadership often led to temporary outperformance, but systematically capturing such gains has proven
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The crucial difference in price momentum vs. earnings momentum [Klement on Investing]Sometimes, you dont know what you know until somebody spells it out crystal clear for you. At least thats how I felt when I read the analysis of Kewei Hou and his colleagues on price momentum and earnings momentum. Most investors know that both price momentum and earnings momentum are factors that can be employed to create outperformance vs. the market and to select attractive stocks. Price