[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 5 [Year:] 2012 [Issue:] 1 [Pages:] 20-58
This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four major stock indexes in the US market and finds some evidence in favor of a positive relation between the mean of the excess returns and expected risk. However, by using quantile regressions, we find that the risk-return relation moves from negative to positive as the returns' quantile increases. A positive risk-return relation is valid only in the upper quantiles. The evidence also suggests that intraday skewness plays a dominant role in explaining the variations of excess returns.
Risk-return tradeoff Volatility Intraday skewness Quantile Regression High-frequency data