Quant Mashup - Sitmo Denoising Correlation Matrices for More Stable Portfolio Optimization [Sitmo]Portfolio optimization lies at the heart of asset management, guiding investment strategies from risk minimization to return maximization. Many of the most widely used allocation methods such as minimum variance, maximum Sharpe ratio, and risk parity rely on the inverse of the correlation matrix to(...) New open-source library: Conditional Gaussian Mixture Models (CGMM) [Sitmo]I’ve released a small, lightweight Python library that learns conditional distributions and turns them e.g. into scenarios, fan charts, and risk bands with just a few lines of code. It’s built on top of scikit-learn (fits naturally into sklearn-style workflows and tooling). Example usage: In the(...) Extracting Interest Rate Bounds from Option Prices [Sitmo]In this post we describe a nice algorithm for computing implied interest rates upper- and lower-bounds from European option quotes. These bounds tell you what the highest and lowest effective interest rates are that you can get by depositing or borrowing risk-free money through combinations of(...) Recovering Accurate Implied Dividend and Interest Rate Term-Structures from Option Prices [Sitmo]In this post we discuss the algorithms we use to accurately recover implied dividend and interest rates from option markets. Implied dividends and interest rates show up in a wide variety of applications: to link future-, call-, and put-prices together in a consistent market view de-noise market(...)