I worked in finance for years and kept running into the same gaps in portfolio tools, so I finally built the tools myself. This one is the risk tool. It got into awesome-quant today. The lab compares covariance models side by side and shows you exactly where they disagree. Then it tests your allocation across risk scenarios and prices out what tighter constraints cost you in return, turnover, and fees. The main question it tries to answer is when the uncertainty adjustment is worth paying for. Sometimes it is. Sometimes you're just buying expensive comfort. The demo runs on synthetic portfolios, right in the browser. The Python package runs the full optimizer. pip install portfolio-risk-lab GitHub: https://github.com/garroshub/portfolio-risk-lab Interactive demo: https://garroshub.github.io/portfolio-risk-lab/ If you try it, tell me which scenario is missing. That part I genuinely want picked apart.   submitted by   /u/garros-yu [link]   [comments]