In this new paper, João Nicolau and colleagues introduce a portfolio optimization procedure that minimizes intra-horizon risk.
The authors use a nonparametric method for estimating first hitting time probabilities, and a novel approach to Markov chain order selection. This proposed optimization framework allows for the inclusion of innovative path-dependent measures of risk and return in the asset allocation process.
Additionally, the authors provide an empirical application using S&P 100 companies, a risk-free asset, and stock indices. These empirical results suggest that the proposed framework exhibits more consistency between in-sample and out-of-sample performance than the mean-variance model and an alternative optimization problem that minimizes the MaxVaR measure.
