Quant case studies, worked step by step
- Cases
- 100
- Traced to a firm
- 43
- Topics
- 11
- Hard
- 30
Topic
All topicsSignal research and data tasks10Options and volatility trading10Market-making games14Portfolio construction10Strategy evaluation and backtests9Execution and market microstructure8Fixed income and credit8Regression and model review8Risk measurement and limits9Statistical arbitrage and event trades8Position sizing and bankroll6
Showing 1–5 of 5 · filtered from 100Clear filters
- 008An illiquid mid-cap has a beta of 0.55 from daily returns but 0.85 from weekly returns. Explain the gap, and compute a Dimson beta from lag coefficients of 0.55, 0.22 and 0.08.Quant researchRisk quant
- 019A signal's slope is 0.12 with an OLS standard error of 0.05, a t of 2.4, but the heteroskedasticity-robust standard error is 0.08. Recompute significance, say which to trust, and explain why the errors grow in volatile months.Quant researchSystematic hedge funds
- 036A stock's 36-month rolling beta has ranged from 0.7 to 1.5 and its 12-month rolling beta from 0.3 to 2.1. How much of that is estimation noise, how would you test for genuine change, and which window would you use?Quant researchRisk quant
- 057A factor model of monthly returns shows a Durbin-Watson of 0.9, residual variance rising with market volatility (Breusch-Pagan p = 0.01) and variance inflation factors of 12 on two value factors. Which assumption does each break, what happens to the coefficients and t-statistics, and what is the fix?CitadelLondon · 2026
- 084Regressed on the market alone, Suryamandal's fund shows alpha of 0.8% a month (t = 2.9). Adding size and value factors gives alpha of 0.35% (t = 1.4), with loadings of 0.95 on the market, 0.6 on size and 0.4 on value. Where did the alpha go, and what does the fund really deliver?State StreetCambridge · 2019
Company names and figures are illustrative.