This is a summary of links featured on Quantocracy on Friday, 04/29/2022. To see our most recent links, visit the Quant Mashup. Read on readers!
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The Absorption Ratio: Measuring Financial Risk, Part 2 [Portfolio Optimizer]In the previous post, I reviewed the turbulence index, an indicator of financial market stress periods based on the Mahalanobis distance, introduced by Chow and al.1 and Kritzman and Li2. In this post, I will review the absorption ratio, a measure of financial market fragility based on principal components analysis, introduced by Kritzman and al.3. I will also show how to compute this absorption
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How Does Weighting Scheme Impacts Systematic Equity Portfolios? [Quantpedia]How often do you think about the weights of the assets in your portfolio? Do you weigh your assets equally, or do you prefer value-weighting? The researchers behind a recent research paper analyzed various weighting schemes and examined their effect on factor strategy return. They studied five weighting schemes that ignore prices: equal weighting, rank weighting, z-score weighting, inverse
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Betting Against Beta: New Insights [Alpha Architect]The 2014 study by Andrea Frazzini and Lasse Pedersen, Betting Against Beta, established strong support for low-beta (as well as low-volatility) strategies. The authors found that for U.S. stocks, the betting against beta (BAB) factor (a portfolio that holds low-beta assets leveraged to a beta of 1 and shorts high-beta assets deleveraged to a beta of 1) realized a Sharpe ratio of 0.78 between
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Random Forest on Financial Ratios as an Investment Strategy [Quant Dare]Random Forests are widely used Machine Learning algorithms. In finance, certain financial ratios are used to try and predict whether or not a company will outperform the market. Can we use the random forest on financial ratios to articulate an investment strategy which outperforms a buy and hold strategy? Thesis on financial ratios In previous posts, we have seen how certain financial ratios