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Modeling asset returns under time-varying semi-nonparametric distributions

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  • León, Ángel
  • Ñíguez, Trino-Manuel

Abstract

We extend the semi-nonparametric (SNP) density of León et al. (2009) to time-varying higher-order moments for daily asset return innovations of stock indexes and foreign-exchange rates. We estimate robust tail-indexes for testing the existence of the unconditional higher-order moments. We obtain closed-form expressions of partial moments and expected shortfall under the time-varying SNP density with the GJR-GARCH for modeling returns. A comparative study between SNP and Hansen’s skewed-t, based on skewness-kurtosis frontiers, in-sample and backtesting analyses, is also implemented. Finally, we conduct an out-of-sample portfolio selection exercise for the stocks of the S&P 100 index through an equity screening method based on our parametric one-sided reward/risk performance measures and compare with the Sharpe ratio portfolio.

Suggested Citation

  • León, Ángel & Ñíguez, Trino-Manuel, 2020. "Modeling asset returns under time-varying semi-nonparametric distributions," Journal of Banking & Finance, Elsevier, vol. 118(C).
    • Handle: RePEc:eee:jbfina:v:118:y:2020:i:c:s0378426620301369
    DOI: 10.1016/j.jbankfin.2020.105870
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    More about this item

    Keywords

    Backtesting; Equity screening; Expected shortfall; Conditional higher-order moments; Tail-index;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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