[We argue that changes in average idiosyncratic volatility provide a proxy for changes in the investment opportunity set and that this proxy is closely related to the book-to-market factor. We test this idea in two ways using G7 countries' data. First, we show that idiosyncratic volatility has statistically significant predictive power for aggregate stock market returns over time. Second, we show that idiosyncratic volatility performs just as well as the book- to-market factor in explaining the cross section of stock returns. Our results suggest that the hedge against changes in investment opportunities is an important determinant of asset prices.]

We describe four channels through which breakups can potentially increase idiosyncratic volatility for parent firms. These are: loss of diversification (portfolio effect), change in growth opportunities, change in operational efficiency, and the flow and assimilation of information (information effect). The relevance of each channel depends on the mode of a breakup. We explain conceptually and show empirically, using a sample of 530 breakups (259 spinoffs and 271 equity carveouts), that the portfolio effect is dominant for spinoff parents, while the information effect gains importance for carveout parents. Our novel insight is that the magnitude of the information effect depends on the pre-announcement information set held by investors; we provide a simple state-space model and empirical evidence to support this intuition. We also find a relation between the change in operational efficiency and the change in idiosyncratic volatility for spinoff parents.

To sign option trades as buys and sells, researchers often employ stock trade classification rules including the quote, the Lee and Ready (1991), the Ellis, Michaely, and O'Hara (2000), and the tick methods. Using a proprietary CBOE dataset that reports trade direction, we find that these four rules sign correctly 83%, 80%, 77%, and 59% of all classifiable trades, respectively. These rates are based on separate classifiable samples because each of the four rules fails to classify some trades (e.g., the quote rulecannot classify midspread trades). Outside-quote and reversed-quote trades are highly misclassified by all four rules. The probability of such trades is related to trading frequency, trade size, moneyness, and maturity. Underlying asset price changes around the time of the trade improve classification precision. We find that the components of index option complex trades not executed on the Retail Automated Execution System are misclassified almost 50% of the time by any method. The elimination of these trades (15% of the sample) results in a success rate of over 87% for the quote rule.

We argue that changes in average idiosyncratic volatility provide a proxy for changes in the investment opportunity set and that this proxy is closely related to the book-to-market factor. We test this idea in two ways using G7 countries' data. First, we show that idiosyncratic volatility has statistically significant predictive power for aggregate stock market returns over time. Second, we show that idiosyncratic volatility performs just as well as the book-to-market factor in explaining the cross section of stock returns. Our results suggest that the hedge against changes in investment opportunities is an important determinant of asset prices. The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected], Oxford University Press.

Consistent with the post-1962 US evidence by Ang et al. [Ang, A., Hodrick, R., Xing Y., Zhang, X., 2006. The cross-section of volatility and expected returns. Journal of Finance 51, 259–299], we find that stocks with high idiosyncratic variance (IV) have low CAPM-adjusted expected returns in both pre-1962 US and modern G7 data. We also test in three ways the conjecture that IV is a proxy of systematic risk. First, the return difference between low and high IV stocks – that we dub as IVF – is a priced factor in the cross-section of stock returns. Second, loadings on lagged market variance and lagged average IV account for a significant portion of variation in average returns on portfolios sorted by IV. Third, the variance of IVF correlates closely with average IV, and the two variables have similar explanatory power for the time-series and cross-sectional stock returns.

Average idiosyncratic stock volatility forecasts the bilateral exchange rates of the US dollar against major foreign currencies in and out of sample. The US dollar tends to appreciate after an increase in US idiosyncratic volatility. Similarly, ceteris paribus, German and Japanese idiosyncratic volatilities positively and significantly correlate with future US dollar prices of the Deutsche mark and the Japanese yen, respectively. Our results suggest that exchange rates are predictable.

We uncover a positive stock market risk-return tradeoff after controlling for the covariance of market returns with the value premium. Fama and French (1996) conjecture that the value premium proxies for investment opportunities; therefore, by ignoring it, early specifications suffer from an omitted variable problem that causes a downward bias in the risk-return tradeoff estimation. We also document a positive relation between the value premium and its conditional variance, and the estimated conditional value premium is strongly countercyclical. The latter evidence supports the view that value is riskier than growth in bad times, when the price of risk is high.