This is a summary of links recently featured on Quantocracy as of Monday, 10/05/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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A Century of Meme Stocks and the Price of Coordination [Quantpedia]Meme stocks are commonly studied through social-media activity, but this approach limits both the historical scope of research and the signals available to practitioners. In A Century of Meme Stocks and the Price of Coordination, Chad Schmerling develops an alternative: a machine-learning model trained to identify the holdings of the Roundhill MEME ETF using market and firm-level data rather than
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Building a Statistically Valid Backtest: The Checklist Nobody Runs [Aligrithm]McLean and Pontiff record stock-portfolio predictors whose performance is 26% lower out of sample than in sample, and 58% lower after publication. Suhonen, Lennkh, and Perez look at 215 smart-beta strategies banks offered and find a median deterioration of 73% in the Sharpe ratio from the backtest to the live period. Arakelian, Bolesta, Liu, Osterrieder, Poti, Schwendner, Sutiene, Vlah Jeri, and
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What Happens After an Analyst Downgrade? [Talval]In August we scored 22,000 analyst upgrades and downgrades against the market and found that the median one is a coin flip. That was the average call. This study asks what the average hides: does the same rating change mean something different depending on what the stock had already done? It does, in one place, and in the direction nobody acts on. A downgrade that lands on a stock that has already
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The 200-day moving average vs volatility targeting [Quanter Lab]Anyone who held stocks through 2008 or the Covid crash has asked the same question: is there a simple rule that gets you out before the worst of it? Two answers are famous. The 200-day line sells when the price ends the day below its average of the last 200 trading days. Volatility targeting holds less of the fund when its daily moves grow larger than usual, and more when they calm down. We tested
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Orthogonal Cluster Risk Parity (OCRP) [CSS Analytics]luster Risk Parity (CRP)was originally introduced in 2013 and conceived in 2012 by David Varadi and Michael Kapler (Systematic Investor). It was designed as an attempt to make ERC by Maillard, and Roncalli aware of the portfolios total asset allocation and allocate risk contributions equally both within and across the portfolio instead of across the individual assets which requires careful