Quant Mashup - Portfolio Optimizer Hierarchical Risk Parity: Introducing Graph Theory and Machine Learning in Portfolio Optimizer [Portfolio Optimizer]In this short post, I will introduce the Hierarchical Risk Parity portfolio optimization algorithm, initially described by Marcos Lopez de Prado1, and recently implemented in Portfolio Optimizer. I will not go into the details of this algorithm, though, but simply describe some of its general ideas(...) Correlation Matrix Stress Testing: Shrinkage Toward an Equicorrelation Matrix [Portfolio Optimizer]Financial research has consistently shown that correlations between assets tend to increase during crises and tend to decrease during recoveries1. The recent COVID-19 market crash was no exception, as illustrated on Alvarez Quant Trading blog post Correlations go to One for both the individual(...) Residualization of Risk Factors: Examples and Pitfalls [Portfolio Optimizer]The most common approach to measuring portfolio (risk) factor exposures is linear regression analysis, which describes the relationship between a dependent variable - portfolio returns - and explanatory variables - factors - as linear. One of the outputs of this analysis are the partial regression(...) Replicating the J.P. Morgan Efficiente Index [Portfolio Optimizer]The J.P. Morgan Efficiente 5 Index is a tactical asset allocation strategy designed by J.P. Morgan based on a broad universe of 13 ETFs. This post will illustrate how to replicate this strategy with Google Sheets. Notes: A fully functional spreadsheet corresponding to this post is available here.(...) When a correlation matrix is not a correlation matrix and what can be done about it [Portfolio Optimizer]Estimating how individual assets are moving together is an important part of many financial applications1 and the most commonly used measure for this is the Pearson correlation. Unfortunately, for a variety of reasons, what sometimes appears to be a correlation matrix is actually not a valid(...)