Prediction of the Conditional Distribution of Daily International Stock Returns Volatility: The Role of (Conventional and Unconventional) Monetary Policies

In this paper, we use a k-th order nonparametric causality-in-quantiles test to analyze the effect of both conventional and unconventional monetary policy, captured by a single-metric (shadow rates), on high-frequency, i.e., daily international equity market volatility, while simultaneously accounting for the effect on stock returns too. Using data for the Euro Area, Sweden, the United Kingdom and the United States, we find strong evidence of causal influence over the entire conditional distribution of stock returns and its volatility, with the latter shown to be positively related to the shadow rates across various regimes. Focusing on volatility, the predictability result continues to be robust to alternative estimates of volatility and metrics of conventional and unconventional monetary policies, as well as, when we consider controls capturing high-frequency effects from the real-side of the macroeconomy. Finally, we also depict that the predictive content of monetary policy on stock market volatility based on the shadow rates is stronger than the corresponding official rates, due to the former not hitting an effective lower bound during the episodes of the global financial crisis and the coronavirus pandemic. Our findings have important implications for both investors and policymakers.