Revisiting the asymmetric dynamic dependence of stock returns: Evidence from a quantile autoregression model

The paper provides an overview of the asymmetric dynamic dependency of the conditional return distribution using a quantile autoregression model for three indexes, namely the Shenzhen Component (SZC), the Standard & Poor's 500 (S&P 500) and Stoxx Europe 600 (S&E 600) indexes. Our findings can be summarized as follows. For SZC index, lagged extreme positive returns display more impact on current returns than that of lagged other returns at median and high quantiles; at median and high quantiles lagged positive returns display more impact on current returns than that of lagged negative returns; at lower quantiles lagged positive returns display less impact on current returns than that of lagged negative returns. For S&E 600 index, at low quantiles lagged extreme positive returns display less impact on current returns than that of lagged other returns; at high quantiles lagged extreme positive returns display more impact on current returns than that of lagged other returns; at low quantiles lagged positive returns display less impact on current returns than that of lagged negative returns; at high quantiles lagged positive returns display more impact on current returns than that of lagged negative returns. For S&P 500 index, at low quantiles lagged extreme positive returns display less impact on current returns than that of lagged other returns; at high quantiles lagged extreme positive returns display more impact on current returns than that of lagged other returns; at low quantiles lagged positive returns display less impact on current returns than that of lagged negative returns; and at high quantiles lagged positive returns display more impact on current returns than that of lagged negative returns. We find insignificant asymmetric dynamic dependency of middle returns for the three indexes. The sensitivity of our results is evaluated by a robustness check. The findings of this paper should help investors make appropriate decisions to maintain control of stock returns.