This is a summary of links featured on Quantocracy on Friday, 12/16/2022. To see our most recent links, visit the Quant Mashup. Read on readers!
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100 Years of Historical Market Cycles [Quantpedia]Which assets perform best when rates are rising, and inflation is high? And what happens if rates are still rising but inflation is already falling? And whats the impact of the business cycle? These are the questions that everyone is currently trying to answer. Today, we will start a longer series of articles with the goal of giving an exact quantitative answer to all questions related to
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The Informativeness: Measuring the Homogeneity of a Universe of Assets [Portfolio Optimizer]In this post, I will describe a measure of the homogeneity of a universe of assets, called the informativeness, introduced by Brockmeier et al.1 in their paper Quantifying the Informativeness of Similarity Measurements. After quickly going through the associated mathematics, I will present two examples of usage of this measure – one as potential indicator of systemic risk and the other as as a
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Machine Learning and Emerging Market Stock Returns [Alpha Architect]More specifically, the paper differentiates between: Traditional linear models (ordinary least squares regression and elastic net) and Machine learning methods that allow for non-linearities and interactions (tree-based models such gradient boosted regression trees and random forest and neural networks with one to five layers) What are the main results? #1 Return forecasts based on machine