This is a summary of links recently featured on Quantocracy as of Sunday, 05/25/2025. To see our most recent links, visit the Quant Mashup. Read on readers!
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Taming OLMAR s 1222% Backtest into a Sustainable 106% CAGR [Paper to Profit]Often as traders, we equate complexity with profitability. A models edge comes from it doing something that no other person on Earth has tried yet. But the data shows that simple rules based on real market factors still outperform most models. Those that continue seeking complexity are headed towards a dead end. Today Im focusing on the Online Moving Average Reversion (OLMAR) system by Bin
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The 1 AI Prompt I Use to Generate 20 Trading Ideas in Seconds [Rogue Quant]My kids love bedtime stories. Like most kids. But theyre not into fairy tales or superheroes. Theyre obsessed with one thing: Dad, can you tell a witch story? A mean witch, okay? Every night. Same request. So I lie next to their bed and say, Alright, buddies. A mean witch story it is. Now, I dont know about you But coming up with original witch plots every single night (for
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No Magic Formulas: How I Actually Decide What to Trade [Robot Wealth]Someone recently asked me if I have a checklist for adopting new trading strategies. You know, a neat little formula like if backtested Sharpe > 1.8, trade it or if drawdown < 15%, green light. I get the appeal. We all want clear, objective criteria to make these decisions easier. But strategy adoption just doesnt work that way. The reality is messier. More nuanced. Your
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Applying Transformers to Financial Time Series [Gatambook]In the previous blog post, we gave a very simple example of how traders can use self-attention transformers as a feature selection method: in this case, to select which previous returns of a stock to use for predictions or optimizations. To be precise, the transformer assigns weights on the different transformed features for downstream applications. In this post, we will discuss how traders can
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I Used AI for 30 Minutes and Discovered 8 New Market-Beating Systems [Paper to Profit]Everyone either naively thinks that an LLM will find alpha for them, or equally naively thinks LLMs cannot develop their own systems with any sort of edge. The reality is quite the opposite. When used properly, LLMs can supercharge your strategy research process by at least 10x. Those who arent using AI in their development workflows are going to be easily smoked by those who are in the next
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Macro-aware risk parity [Macrosynergy]Risk parity is an investment strategy that allocates risk exposure equally across asset types through volatility-based calibration and leverage. A most profitable risk parity strategy in the past decades has been the equity-duration long-long, which harvests combined equity and long fixed-income risk premia, while containing return volatility through diversification. Alas, this position is