Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In this paper, we analyze conditional threshold effects of stock market volatility on crude oil market volatility. We use Conditional Threshold Autoregression (CoTAR), a novel extension of TAR from a constant threshold to a time-varying threshold. The conditional threshold is specified as an empirical quantile of recent realizations of a threshold variable. This specification is expected to match investors’ relative perception of financial risk. The target variable is monthly realized volatility (RV) measures of the West Texas Intermediate, and the threshold variable is monthly RV measures of the S&P 500 Index. Our rolling window out-of-sample analysis indicates that the predictive ability of CoTAR is at least on par with TAR for all cases considered, and significantly better than TAR for some cases. The superiority of CoTAR is pronounced when the target variable is a downside RV measure. This is a useful finding which helps market participants and policymakers better control downward risks.