I was one of the original members of a start-up macro hedge fund as a quant analyst/risk quant. I built trading analytic tools/models, risk management infrastructure and related risk models. I eventually founded a consulting company specialized in providing quantitative tools and models to hedge funds. My main research interest is in risk modelling, and decided to share some interesting techniques in this blog.
Let’s talk about tail risk modelling today. In this blog, I want to introduce Extreme Value Theory (EVT) which concerns itself with modelling of the tails of a distribution, and its key results. As we go along we will work through a toy example with basic R implementation. There are two popular parametric approaches to … More Extreme Value Theory
In this post, I would like to quickly introduce what I believe to be an underutilized modelling technique that belongs in most analysts’ toolkit: the quantile regression model. As I am discussing some of the main points, I will be working with R’s quantreg package that is maintained by the inventor of quantile regression. See … More Quantile Regression
It is commonly known that financial returns exhibit characteristics that are not captured by the widely applied normal and log-normal distributions. In a series of posts I want to present some flexible distributions that are well suited to model financial returns. We will work our way through quick modelling exercises in R that show how … More Flexible Distributions for Asset Returns – Part I [Generalized Lambda Distribution]
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