2016/08/25 by Heejoon Han, Han, Heejoon
Economics, Econometrics and Finance · Mathematics · #Applications (stat.AP) #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Economics and business #Financial Risk and Volatility Modeling #Market Dynamics and Volatility #Statistical Finance (q-fin.ST) #q-fin.ST #stat.AP
paper · pdf · doi:10.48550/arxiv.1608.07193
arxiv created 2016/08/25 · openalex publication_date 2016/08/25 · arxiv updated 2016/08/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper examines quantile dependence between international stock markets and evaluates its use for improving volatility forecasting. First, we analyze quantile dependence and directional predictability between the US stock market and stock markets in the UK, Germany, France and Japan. We use the cross-quantilogram, which is a correlation statistic of quantile hit processes. The detailed dependence between stock markets depends on specific quantile ranges and this dependence is generally asymmetric; the negative spillover effect is stronger than the positive spillover effect and there exists strong directional predictability from the US market to the UK, Germany, France and Japan markets. Second, we consider a simple quantile-augmented volatility model that accommodates the quantile dependence and directional predictability between the US market and these other markets. The quantile-augmented volatility model provides superior in-sample and out-of-sample volatility forecasts.