This is a summary of links recently featured on Quantocracy as of Thursday, 06/04/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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The software side of replication [Implementing QuantLib]Hello again! Todays post was originally published in the November 2025 issue of Wilmott Magazine. What if you could make it a lot easier for readers to replicate your paper? That was the idea I followed when Wilmott called for articles to be published in a special issue on the replication crisis. Subscribe to my Substack to receive my posts in your inbox, or follow me on Twitter or LinkedIn if
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Does Regression Still Work in Modern Markets? [Relative Value Arbitrage]Regression is one of the oldest and widely used statistical techniques. It has found applications across the social sciences, engineering, natural sciences, and finance. Despite the rapid rise of machine learning and AI, regression remains a useful tool for modeling relationships, making forecasts, and extracting signals from data. In this post, we revisit regression-based trading systems and
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New Feature: Return Contribution Analysis [Allocate Smartly]Every strategy and Model Portfolio now includes a Return Contribution analysis, showing each assets contribution to overall annual return. We further aggregate results by asset category and risk on/off, as well as estimate the drag from trading friction (transaction costs + slippage). Lets walk through a sample return contribution analysis using the most popular strategy on our
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Trend following (2/4): Sector-by-sector replication [Beyond Passive]Part 1 left a gap. Regressing the synthetic backtrack against the whole universe at once recovered the program in ten contracts at a Sharpe of 0.84, against the programs 1.03 a fifth of a Sharpe unaccounted for. I argued there that the gap lived in the regressions blindness to the structure inside the program: equities and bonds, energy and grains, all blended into one optimisation, so