This is a summary of links recently featured on Quantocracy as of Tuesday, 07/08/2025. To see our most recent links, visit the Quant Mashup. Read on readers!
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The Lumber-Gold Strategy [Allocate Smartly]The Lumber-Gold Strategy was first published a decade ago, won the 2015 NAAIM Wagner Award, and continues to be cited today. The strategy trades based on the relative strength of lumber as a leading economic indicator, versus gold. How has the strategy performed since publication? Strategy results from 1987 follow. Results are net of transaction costs see backtest assumptions. Learn about what
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Backtesting [Trading the Breaking]Introduction You know, after more than a decade in this business, I've come to think of backtesting as the ultimate paradox of our profession. It's like being handed the top one lie detector in the world, only to discover it's been calibrated exclusively on your own personal brand of self-deception. Let me tell you something about that momentand every quant knows exactly which
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Weekly Research Recap [Quant Seeker]Hi there. Its time for this weeks recap of top investing research, with direct links to the original sources for easy access. As mentioned last week, there wont be a Thursday post this week as Im away on holiday. Normal posting resumes next week. Commodities Political Uncertainty and Commodity Markets (Hou, Tang, Tao, and Zhang) Commodity markets often respond sharply to political
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Should Investors Combine or Separate Their Factor Exposures? [Alpha Architect]If youre a factor investor, there will come a time when you will have to choose between mom and dad: Should you combine or separate your factor exposures? And make no mistake: You will have to make a decision! While theres no right answer, the way you structure your portfolio can have significant implications for returns, costs, and even your own behavior as an investor. Lets walk through
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How Machine Learning Enhances Market Volatility Forecasting Accuracy [Relative Value Arbitrage]Machine learning has many applications in finance, such as asset pricing, risk management, portfolio optimization, and fraud detection. In this post, I discuss the use of machine learning in forecasting volatility. Using Machine Learning to Predict Market Volatility The unpredictability of the markets is a well-known fact. Despite this, many traders and portfolio managers continue to try to