This is a summary of links featured on Quantocracy on Sunday, 07/23/2023. To see our most recent links, visit the Quant Mashup. Read on readers!
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Recursive least-squares linear regression [OS Quant]I first learned about this algorithm in the book Kernel Adaptive Filter: A Comprehensive Introduction1 sometime in 2012 or 2013. This book goes in depth into how to build kernel filters and does a fantastic job of easing you into the mathematics. I highly recommend having a read if you can. In my trading algorithms, at each time period, I use a linear regression to predict future returns of each
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Quant And Machine Learning Links: 20230723 [Machine Learning Applied]Reinforcement Learning for Credit Index Option Hedging Francesco Mandelli, Marco Pinciroli, Michele Trapletti, Edoardo Vittori In this paper, we focus on finding the optimal hedging strategy of a credit index option using reinforcement learning. We take a practical approach, where the focus is on realism i.e. discrete time, transaction costs; even testing our policy on real market data. We
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Research Review | 21 July 2023 | Forecasting Markets [Capital Spectator]Betting on War? Oil Prices, Stock Returns and Extreme Geopolitical Events Knut Nygaard (Oslo Metropolitan U.) and L.Q. Srensen (Storebrand Asset Mgt.) July 2023 We show that the ability of oil price changes to predict stock returns is largely limited to five extreme geopolitical events: the 2022 invasion of Ukraine, the 2003 invasion of Iraq, the 1990/91 Persian gulf war, the 1986 OPEC collapse,
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Risk of Momentum Crashes: can it be reduced? [Alpha Architect]My August 4, 2022, Alpha Architect article examined the research demonstrating that cross-sectional momentum has provided a premium that has been found to be persistent across time and economic regimes, pervasive around the globe and across sectors and asset classes (stocks, bonds, commodities and currencies), robust to various definitions, and survives transactions costs. And within equities,