This is a summary of links recently featured on Quantocracy as of Saturday, 10/03/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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Buffett’s be greedy when others are fearful, tested [Quanter Lab]"Be greedy when others are fearful" is Warren Buffett's best-known advice, and CNN's Fear & Greed Index is how many people check what the others feel. We rebuilt CNN's index from the seven market measures it combines, which takes it back to 2007, and followed the advice to the letter: buy the S&P 500 at Extreme Fear, sell it at Extreme Greed. From 2009 to 2026 the
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Polynomial Regression Bands With a Profit Factor Below One [Aligrithm]Gil Cohen fits second-, third-, and fourth-degree polynomial moving regression bands to Nasdaq-100 names from 2017 through March 2024, charges 0.3% on each fill, and names the four-degree model best. Table 3 puts the average net profit at 162.75 dollars per name. The abstract, the conclusion, and Table 4 print 162.73. The risk case next to that crown is a profit factor of 0.55 and a minimum win
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What Really Drives the Asset Growth Anomaly? New Evidence Points to Mispricing, Not Risk [Alpha Architect]One of the most well-documented patterns in the cross-section of stock returns is that firms with high asset growth subsequently underperform firms with low asset growth. This asset growth anomaly is so well established that it now sits at the core of two of the most widely used benchmark factor models: the Fama-French five-factor model (via the conservative-minus-aggressive, or CMA, factor)
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The turn of the month effect tested: where the stock market’s payday is now [Quanter Lab]For most of the last century US stocks made their money on four days a month, the last trading day of the month and the first three of the next, which economists call the turn of the month. The usual explanation is a payday, because salaries and pensions arrive at the end of the month and part of that money goes into stocks. A payday everyone knows about invites buyers to get ahead of it, and US
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Practical transaction cost checks for macro trading strategies [Macrosynergy]This article demonstrates practical transaction-cost checks for systematic macro trading strategies, using a Python class from the Macrosynergy package. The method requires only basic estimates of transaction sizes and costs, which can often be obtained from trading desks or through LLM queries. These approximate cost checks help assess a strategys economic value, scalability, suitable