Differences of opinion and stock market volatility: evidence from a nonparametric causality-in-quantiles approach

This paper examines whether the differences of opinion across active money managers relates to stock market volatility via the recently proposed nonparametric causality-in-quantiles test. Using the dispersion in equity market exposures of active managers as a proxy for differences in opinion, we analyze the predictability of (realized) volatility of the S&P500 for the period July, 2006-August, 2016. Unlike the result of no predictability obtained under the misspecified linear set-up, our nonparametric causality-in-quantiles test indicates that dispersion in active managers’ risk exposures to the stock market can predict volatility over the range of quantiles that correspond to moderately high levels of market volatility. Our findings are in line with the previous literature that relates divergent beliefs across investors to subsequent stock returns and suggest that the effect on subsequent returns is likely to be transmitted via the volatility channel. Our results highlight the importance of detecting and modeling nonlinearity when analyzing the information content of divergent beliefs across market participants.