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ABSTRACT This paper investigates the causal links between the overnight returns (volatility) and the intraday returns (volatility) series of the S&P 500, DAX and SSE by using a new multiscale nonlinear Granger causality analysis framework. We discover a bidirectional and nonlinear Granger causality between the two series, indicating that robust predictive information can be derived from the other series. To explore the driving force behind nonlinear causality, the original returns (volatility) series are analysed through multiscale decomposition with ensemble empirical mode decomposition (EEMD), fine‐to‐coarse reconstruction and nonlinear Granger causality testing. By counterfactual inference in the time‐frequency domain, we find that statistical causality is driven by specific time‐frequency component(s) of the original series. We also find trading volume serves as an important transmission channel for nonlinear Granger causality. These observations suggest both short‐ and long‐term investment implications, providing meaningful insights for equity market investors in terms of yield and risk management.
Zhao et al. (Wed,) studied this question.