The stochastic volatility in mean model and automation: Evidence from TSE

This paper investigates the behavior of volatility in Canadian equity markets before and after automation. We employ a stochastic volatility in mean (SVM) model that incorporates the unobserved volatility as an explanatory variable in the mean equation. The volatility persistent estimates all increase post-automation, with the scaling parameter increasing as well. The parameter estimates which measure both the ex ante relationship between returns and volatility and the volatility feedback effect are found to be negative for all series, and to increase post-automation. Our results fall in line with those of (French, K.R., Schwert, G.W., & Stanbaugh, R.F. (1987). Expected stock returns and volatility. Journal of Financial Economics, 19, 3–29) who find similar relationship between unexpected volatility dynamics and returns and confirm the hypothesis that rational risk-averse investors require higher expected returns when unanticipated increase in future volatility are highly persistent. Finally, our findings are consistent since higher values of persistence are combined with larger negative values for the in-mean parameter.