Dar-Hsin Chen

Downside risk measures and equity returns in the NYSE

Although investors are concerned foremost with mean and variance, they are also sensitive to downside risk. In this article we employ several risk variables of traditional and downside risk measures to evaluate the equity returns in the New York Stock Exchange (NYSE) market in order to test their explaining power. The test results show that variance (or SD) is better than beta in the performance. However, those traditional risk measures have almost less explanatory power than total downside risk measures, whether the downside risk measures are relative to zero, the mean return or the market index return when they are used to predict the future risk premium. The results also show that the significance of the downside risk measures in the NYSE market is different between different industry sectors, different periods of time and in different individual equities.

The Downside Risk and Equity Evaluation: Emerging Market Evidence

In this paper we employ several risk measures to evaluate the equity returns in emerging markets. We focus on a downside risk approach, in particular, with shortfall probability, expected shortfall, downside variance and downside deviation. Our results show that return variance is important in explaining the same-period return. When the risk measure is used to predict future risk premium, the relative-to-zero downside variance (deviation) is a better measure than the total variance (deviation). This new risk measure is not only aligned with peoples normal risk sense, but also consistent with the available information in portfolio management.

VaR and the Cross-Section of Expected Stock Returns: An Emerging Market Evidence

In this paper we investigate the explanatory power of the market beta, firm size, and the book-to-market ratio, as well as Value-at-Risk regarding the cross-sectional expected stock returns in a less developed stock market - Taiwans stock market. The main purpose is to examine whether the Value-at-Risk factor has marginal explanatory power related to the Fama-French three-factor model. The empirical results show that Value-at-Risk can account for the average stock returns at both 1% and 5% significance levels based on cross-sectional regression analysis. Moreover, from the perspective of the time series regression, the Value-at-Risk factor can also demonstrate the variation of the stock market, especially for the larger companies in the Taiwan stock market.