This is a summary of links recently featured on Quantocracy as of Sunday, 05/10/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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The NAAIM Exposure Index: Incorporating Active Investment Mgr Sentiment into Asset Alloc [Portfolio Optimizer]The NAAIM Exposure Index represents the average exposure to U.S. equity markets as reported by members of the National Association of Active Investment Managers (NAAIM) in a weekly survey. That index, like any other sentiment indicator, is a useful gauge of the possible future direction of a market1 that can be incorporated into ones asset allocation process. In this blog post, I will analyze
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The Currency You Didn t Choose [Beyond Passive]Run the same three-asset strategy out of New York and out of Frankfurt. The American gets Sharpe 0.97 and a 22% drawdown. The European, holding identical positions but spending in euros, gets Sharpe 0.65 and a 45% drawdown. The trades are the same. The difference is a currency position the European never chose to take, sized by the strategys gross exposure rather than by any view on EUR/USD.
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AI Forex Backtesting with LLM Regime Labels: DeepSeek vs KMeans in Python [Quant Insti]TL;DR: This post builds a forex backtest where a DeepSeek LLM labels market regimes from compact numeric summaries. We compare it to a KMeans baseline, apply monthly walk-forward optimization, and report out-of-sample results from 2023 onward. Prerequisites To fully grasp the regime-labeling approach in this blog, it helps to have a basic familiarity with clustering methods and market regimes. For
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Reinforcement Learning for Optimal Execution [Jonathan Kinlay]Optimal execution is the part of the trading stack where small percentages compound into real money. A long-only equity manager turning over 80% a year on a USD 5bn book pays roughly 4 bps 1.6m for every basis point of slippage. The textbook approach AlmgrenChriss (AC) or its risk-neutral cousin TWAP has been the operating standard for two decades, and for good reason: it is
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Designing State-of-the-Art Logging in Python [Hanguk Quant]Hello friends~ This post, we will discuss the introduction of a state of the art performance Python logging subsystem in quantpylib, and discuss some of the key design principles that allow us to achieve this. To my knowledge, among all Python logging frameworks, it is the lowest latency implementation out there. As an aside, I am focused on making quantpylib into a more mature platform for
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Why Momentum Investing Has Been Struggling And What Volatility Has to Do With It [Alpha Architect]A look at recent academic research connecting market volatility spikes to the underperformance of momentum strategies (especially for long/short versions of the strategy) The Big Picture If youve used momentum as part of your investment strategy over the past decade and found it disappointing, youre not imagining things. Haim Mozes, author of the study Volatility Spikes and Momentum,