Modern statistics and econometrics with applications to financial markets
This post discusses the need for smoothed version of the statistical bootstrap. I start with a negative result of the standard bootstrap, and introduce smoothing as a practical, and necessary improvement. Suppose you have 100 unique values and you draw a new sample of 100 observations with replacement. How many unique values would you expect...
My work on covariance estimation has recently been published as an Advanced Review in WIREs Computational Statistics, a highly regarded, peer-reviewed journal in the field. It feels remarkably rewarding to see a decade of my curiosity finally bound together in one place. The writing process started about 4.5 years ago on evenings, weekends, and holidays...
I recently dipped my toes into fairness concepts in machine learning. What does being fair mean, practically? is it fair that I was not born with the physique required to qualify for the NBA? Absolutely it s fair. In the lottery of life, my genes were decided on in the same way as they were for...
In the classical regime, when we have plenty of observations relative to what we need to estimate, we can rely on the sample covariance matrix as a faithful representation of the underlying covariance structure. However, in the high-dimensional settings common to modern data science where the number of attributes/features is comparable to the number...
Today is the last day of 2025. Depending on where you’re reading this, the party might have already begun. I begin this end-of-year post by wishing you a safe and fun time tonight. This blog is just a personal hobby. When I m extra busy as I was this year the blog is a front-line casualty....