This is a summary of links featured on Quantocracy on Monday, 05/13/2024. To see our most recent links, visit the Quant Mashup. Read on readers!
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Message Arrival Rates and Latency [Mark Best]There is a common debate when people are discussing code optimisation that relates to how fast code needs to be. A recent Twitter post about parsing binance BBA messages stated processing times of around 200ns. This is, in my admission, very fast. To put it into perspective, Serde is a common rust deserialization library and is incredibly easy to use. It is however, a lot slower than the optimised
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Maximum Ulcer Performance Index (UPI) Portfolios [Allocate Smartly]Weve added a new objective to the Portfolio Optimizer. Members can now find the combination of TAA strategies that would have maximized the Ulcer Performance Index (UPI), aka the Martin Ratio. Members: begin exploring the Max UPI portfolios now. UPI is a measure of return relative to drawdowns (i.e. losses). It captures both the length and severity of all drawdowns, not just the single
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Rob Hanna Wins the 2024 NAAIM Founders Award [Quantifiable Edges]It was an exciting week here at Quantifiable Edges as it was officially announced that Rob Hanna won the National Association of Active Investment Managers (NAAIM) Founders Award, which is its annual white paper competition. The paper: Chicken & Egg: Should you use the VIX to time the SPX? Or use the SPX to time the VIX? challenges prevailing market wisdom by suggesting that S&P 500 Index
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Options Trading with Cross-Sectional Volatility Factors [Robot Wealth]A few years ago, I got deep into the idea of constructing a long/short equity options portfolio based on the kind of simple factor sorts that had been so successful in quant equity. My original intention was to set up an index and license it to fund managers. Of course, there are many reasons why this is a very hard business problem so I never really got off the ground with it. But I do keep
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How Volatility and Turnover Affect Return Reversals [Alpha Architect]In the research reviewed here, the authors analyze the relationship of aggregate market liquidity to the time-series performance of reversal strategies. The strength and persistence of reversals and reversal driven strategies appear to be different depending on specific risk features of those providing market liquidity to the stock. Reversals and the Returns to Liquidity Provision Wei Dai, Mamdouh
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Using Machine Learning Programs to Forecast the Equity Risk Premium [Alpha Architect]The ability to predict stock returns and the equity risk premium (ERP) is of great interest to academics, financial practitioners, and investors, as future estimated returns have implications for asset allocations. To date, the best metric we have for forecasting future equity returns and the ERP is current valuations (whether using current P/E ratios or some cyclically-adjusted average such as