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Stock Return Quantiles and Conditional Asymmetry: An Approach to Portfolio Selection

Fully aware of the importance of effective risk management, we develop a dynamic quantile forecasting model aimed at improving the accuracy of conditional quantile predictions. We place an emphasis on the 1\%, 2.5\%, and 5\% conditional quantiles, since these measures are often cited to manage the downside risks of portfolios. We validate that the model has a strong performance in predicting this quantile when applied to various GARCH-type models. We use conditional asymmetry measures generated from the model conditional quantile predictions to design a portfolio allocation strategy for five market indices. We identify one such strategy that could improve upon the risk-return tradeoff of the default conditional value-at-risk optimal portfolio and the equal-weight portfolio.


18, 20, 0, 0

Other papers

Has the Downside Risk in the Chinese Stock Market Fundamentally Changed? Eric Ghysels

  • Letter writers

  • Eric Ghysels
  • Chuanshu Ji
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