This paper rationalizes the LASSO algorithm based on uncertain fat-tail priors and max-min robust optimization. Our rationalization excludes heuristic learning or restrictive prior assumptions in the original interpretation of LASSO (Tibshirani (1996)). In our setting, economic agents...

We study aversion to model ambiguity and misspecification in dynamic portfolio choice. Investors with relative risk aversion gamma 1 fear return persistence, while risk-tolerant investors (0 gamma 1) fear return mean reversion, to confront model misspecification concerns when facing a model...

We address the calibration issues of the weighted-indexed semi-Markov chain (WISMC) model applied to high-frequency financial data. Specifically, we propose to automate the discretisation of the price returns and the volatility index by using four different approaches, two based on statistical...

According to no-arbitrage, risk-adjusted returns should be unpredictable. Using several prominent factor models and a large cross-section of anomalies, we find that past pricing errors predict future risk-adjusted anomaly returns. We show that past pricing errors can be interpreted as deviations...