This is a summary of links recently featured on Quantocracy as of Sunday, 02/22/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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Kronos and the Rise of Pre-Trained Market Models [Jonathan Kinlay]The quant finance industry has spent decades building specialized models for every conceivable forecasting task: GARCH variants for volatility, ARIMA for mean reversion, Kalman filters for state estimation, and countless proprietary approaches for statistical arbitrage. Weve become remarkably good at squeezing insights from limited data, optimizing hyperparameters on in-sample windows, and
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Multivariate Break-Even Correlation Tresholds [Yannick Kalber]As we all know, backtesting is not a research tool, but the very end of your research pipeline. If you want to evaluate if a given set of signals is predictive for returns, you can do this more clearly and directly by regressing returns on the signals or measuring their correlations. But how strong do those correlations need to be for the signals to be good enough? A popular heuristic
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Break-Even Correlation Thresholds for Linear Predictive Signals [Yannick Kalber]When Is a Signal Good Enough? As we all know, backtesting is not a research tool, but the very end of your research pipeline. If you want to evaluate if a given signal is predictive for returns , you can do this more clearly and directly by regressing on or measuring their correlation. But how strong does that correlation need to be for the signal to be good enough? A popular heuristic
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Research Review | 20 February 2026 | Forecasting Returns [Capital Spectator]CAPE Ratios and Long-Term Returns Rui Ma (La Trobe University), et al. January 2026 We demonstrate that 10-year equity market returns are considerably more predictable in relation to price-earnings ratios than previously thought. The traditional approach involves relating the current index price level, based on current index components, to the index earnings of previous years, calculated using