The high returns to low volatility stocks are actually a premium on high quality firms

Recent empirical research shows that low volatility stocks outperform high volatility stocks around the world. This study documents that the volatility effect is associated with the quality of the firm using a large sample of international stocks. First, adding a quality factor to the Fama–French model contributes to the explanation of the volatility effect. Furthermore, the negative volatility–return relation is shown to be stronger and significant only among high quality firms which are profitable and have stable cash flows. Second, a fundamental investment strategy that goes long high quality firms and short low quality firms performs like a volatility strategy and cannot be explained by common asset pricing models. However, a low–high volatility factor adds to the explanation of the return difference between high and low quality stocks as volatility and quality strategies have a common component.     

Value versus growth: Australian evidence

The value‐growth effect is one of the most pervasive patterns in stock prices. In this study, the ability of four proxies for value‐growth, book‐to‐market, sales‐to‐price, earnings‐to‐price and cash‐flow‐to‐price to explain equity returns is analysed. The findings show that in aggregate, book‐to‐market best explains cross‐sectional variation in Australian equity returns, which in isolation suggests that it is the superior proxy for value‐growth. The analysis is taken further and the value‐growth effect is examined separately in positive and negative earnings firms. After segregating firms, it is found that in the negative earnings sample, book‐to‐market is the best value‐growth proxy and in the positive earnings sample, cash‐flow‐to‐price has the highest level of significance and is thus the superior value‐growth proxy. The economic significance of this result is telling, as the firms that report positive earnings are much larger than those that report negative earnings.     

Determinants of Investor Demand for Cross‐Listed Firms

By focusing on the decisions of investors to invest in cross‐listed stocks, this paper presents new evidence on why we observe striking differences in the percentage of trade in foreign markets for cross‐listed stocks. With a large sample of Toronto Stock Exchange (TSX) stocks cross‐listed in the U.S. and Canada, we document the effect of investor recognition and risk characteristics on the distribution of trading volume. Firms that are more visible to American investors are traded more heavily in the U.S. At the same time, firms that offer diverse risk characteristics are attractive to Americans. While investors understand the benefits of international diversification, as they are attracted to stocks that are different (e.g., the stock of small firms with few assets in the U.S.), they also seek stocks that provide them with high returns.     

Investing in gold: Individual asset risk in the long run

This study examines gold’s contribution to portfolio risk over different time scales. The analysis is based on wavelet decompositions of the variances and covariances associated with a portfolio that includes gold, stocks, 10-year government bonds and three-month Treasury bills. The results suggest that gold provides the lowest contribution to portfolio risk only when considered over medium- and long-term investment horizons.     

Have European Stocks become More Volatile? An Empirical Investigation of Idiosyncratic and Market Risk in the Euro Area

We examine the dynamics of idiosyncratic risk, market risk and return correlations in European equity markets using weekly observations from 3515 stocks listed in the 12 euro area stock markets over the period 1974–2004. Similarly to Campbell et al. (2001) , we find a rise in idiosyncratic volatility, implying that it now takes more stocks to diversify away idiosyncratic risk. Contrary to the US, however, market risk is trended upwards in Europe and correlations are not trended downwards. Both the volatility and correlation measures are pro‐cyclical, and they rise during times of low market returns. Market and average idiosyncratic volatility jointly predict market wide returns, and the latter impact upon both market and idiosyncratic volatility. This has asset pricing and risk management implications.