This is a summary of links recently featured on Quantocracy as of Tuesday, 06/16/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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The Sharpe Ratio of Pure Noise [Quantt]This week we backtested 2,000,000 trading strategies. Every one of them was pure noise. We generated the returns ourselves with a random number generator, so we know, with complete certainty, that the true Sharpe ratio of every single strategy is exactly zero. The best ones still looked brilliant. Run 1,000 of these noise strategies over ten years of daily data and pick the best, and you get a
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Dual vs. Single Momentum in Commodities: Enhancing Risk-Adjusted Returns [Quantpedia]Commodities represent a vital but highly volatile asset class, characterized by pronounced cyclicality, lack of yield, and susceptibility to severe macroeconomic drawdowns. While cross-sectional (relative) momentum is a well-documented anomaly, its application in commodities often forces portfolios to hold the least declining assets during broad-based bear markets, resulting in unacceptable
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Automating a Volatility Strategy With Python and Interactive Brokers [Concretum Group]It won 5th place at the Quantpedia Awards 2026. The strategy compounds at 16.3% per year over a 17-year backtest, delivers a Sharpe ratio of 1, and keeps equity market correlation near 15%. This article shows how to build an automated VIX volatility trading strategy using Python and Interactive Brokers. Based on our award-winning research, the strategy seeks to capture the volatility risk premium
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FIFA* (*Fitting and Forecasting Actual data) Portfolio Optimisation competition with real returns [Investment Idiocy]This is my fourth post in my summer 2026 mini series on portfolio optimisation. It will very much follow the format of (also with a sports alluding title) blog post number two, so it might be worth rereading that. A reminder if you can't be bothered, I used random data to compare some optimisation methods: monte carlo (random, parameteric) bootstrapping (random, non parametric) double
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Feature selection: Filter-based methods [Trading the Breaking]Financial markets produce mountains of data, spanning simple price movements to limit order book dynamics. A common misconception assumes a larger dataset guarantees superior predictions. Reality proves the opposite. Excessive variables introduce noise, and invite to overfitting. Every input added to a model represents a specific market hypothesis. Including a volatility metric implies price
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A Common Sense Guide to Volatility Trading [Quant Galore]Its a Tuesday morning, you pull up a name youve been watching, and its 30-day implied vol is printing 48, sitting right near the top of where its traded all year. Vol is mean-reverting, everyone knows that, so you do the obvious thing. You sell the straddle, perhaps even an iron condor. Two days later, the print is 61, the short is deep underwater, and the reversion you were promised is
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Market Effect Research: Turnaround Tuesday Effect [TradeQuantiX]This is the fourth article in the small market effect research series. The first looked at the holiday effect on SPY. The second looked at the turn of the month effect, also on SPY. The third looked at the holiday effect on gas and energy assets All three sets of research resulted in tradable systems that I have now implemented as overlays on my personal systematic trading portfolio. If you missed
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Why System Validation Matters More Than Ever [Relative Value Arbitrage]Today, AI and machine learning techniques are evolving at a rapid pace, making the development of trading systems increasingly accessible. Generating signals, building models, and testing ideas is easier than ever. As a result, the challenge is no longer simply developing a trading strategy, but determining whether it is genuinely robust or merely the product of overfitting and data mining. In
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Dividend Timing and Global Dividend Premium [Alpha Architect]Asset pricing research often focuses on risk, valuation, and macroeconomic forces. But this paper highlights another surprisingly powerful driver of returns: the timing of dividend payments. Across 44 international equity markets, the authors uncover a large and persistent dividend premium. Dividend-paying stocks outperform non-payers by a meaningful margin, even after controlling for
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A Hidden Trade Around SpaceX IPO? [Concretum Group]The piece we present today stems from some internal exchange within the Concretum team ahead of the highly anticipated SpaceX IPO, an offering that has dominated headlines for a string of firsts in recent market history, from its record valuation (~$1.75 trillion) to the one that interests us most: the prospect of a fast-track inclusion into the Nasdaq 100. A few numbers can frame why this
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The Factor Zoo Has Hundreds of Animals But Only a Handful of Species [Alpha Architect]Academics have identified hundreds of factors that supposedly explain stock returns. New research shows most of them are telling the same story in different words and only a few truly distinct forces actually drive the market. The problem: too many factors, too little meaning. Over the past few decades, academic researchers have proposed more than 400 factors characteristics or variables,