Time-Varying Semi-Nonparametric Distribution and Portfolio Performance

In this paper, we extend the semi-nonparametric (SNP) densities of León, Mencía and Sentana (2009) through time-varying (TV) volatility, skewness and kurtosis. We derive some parametric properties, the conditional expected shortfall, quantiles and partial moments. We obtain closed-form expressions of reward-to-risk measures under the TV-SNP density. An empirical study of portfolio selection based on equity screening under alternative performance measures for stocks from the S&P 100 index is carried out. We show that the Rachev ratio and skewness-kurtosis ratio both yield portfolios that dominate those obtained under the Sharpe ratio. These results are more significant for weekly rebalancing than for lower rebalancing frequency. We also find that portfolio performance is significantly sensitive to alternative weighting schemes. Besides, a study of tail dependence through copulas is implemented to provide robustness to our results. Finally, a comparative analysis with respect to the historical simulation approach is also provided