Spillover effects of the US stock market and the predictability of returns: international evidence based on daily data

ABSTRACT

This paper investigates the spillover effect of lagged US daily returns on stock return predictability across 17 developed markets from January 1^st, 1972 through August 31^st, 2022. Using daily returns series, we find that lagged US returns is a superior predictor for future returns in international markets while including the lagged domestic returns and considering US negative or extreme returns. The predictive power of lagged US daily returns, nonetheless, substantially weakens during the recent COVID period. Our results imply that the degrees of stock return predictability and spillovers across markets are driven by the evolutionary market conditions, the channels of information transmission, and information leadership.

KEYWORDS:

• Spillover effect
• lagged US returns
• return predictability
• comovements

JEL CLASSIFICATION:

• G10
• G11
• G12
• G15

Acknowledgments

We are grateful to two anonymous Reviewers of the journal for very useful comments and suggestions. However, we are solely responsible for any errors and omissions that may remain in the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

¹ Although some macroeconomic indicators (Rapach, Wohar, and Rangvid 2005) and financial variables (Hjalmarsson 2010) are widely used to predict stock returns, empirical evidence is far from conclusiveness. Because they reflect less dynamic information from the combination of environmental conditions and market participants for highly volatile stock markets (Lo 2004), macroeconomic or financial predictors cannot provide a universal explanation in an international context.

² They elaborate the counter-cyclical pattern of investors’ disagreement which can generate return predictability to concentrate in economic contractions. They illustrate the persistent dynamics of the volatility and risk premium during turbulent economic phases (a recessionary shock). The structural disagreement (the driver of risk premia) and uncertainty (the persistent fluctuations in volatility) particularly with regard to the persistence of fundamentals fits salient points of asset prices and return dynamics.

³ We also use the ARIMAX model, a time-series model, to replace our Model (1). The ARIMAX model is written as: $R_{i,t}^{own}={\alpha }_i+{\beta }_i^{US}{R}_{t-1}^{US}+{\mu }_{i,t}$, where ${\mu }_{i,t}=\rho {\mu }_{i,t-1}+\theta { }_{i,t-1}+{ }_{i,t}$. The results (unreported but available upon request) are very similar with those shown in Table 3 that the lagged US daily returns are positively related to future returns of all the tested markets.

⁴ We also consider the holiday effect by adding an interaction variable with a holiday dummy ($Holiday{s}_{t-1}$), which equals one if day t-1 is a holiday or the next-day immediately after a holiday. The model is written as: $R_{i,t}^{own}={\alpha }_i+{\beta }_i^{US}{R}_{t-1}^{US}+{\beta }_i^{own}{R}_{i,t-1\hspace{0.17em}}^{own}+{\beta }_i^{Holiday}{R}_{t-1}^{US}\times Holiday{s}_{t-1}+{\epsilon }_{i,t}$, where ${\beta }_i^{Holiday}$ denotes the additional predictive power of the lagged US daily returns during holiday periods. We apply this model only on leading developed markets whose holiday data is available, including Japan, Hong Kong, the UK, Canada, and Germany. In an unreported analysis (available upon request), we find that the lagged US daily returns do not show additional predictive power during holiday periods, and therefore, holidays do not significantly influence the spillover effect of the US daily returns shown in Table 4.

⁵ We also test whether the lagged US daily returns will provide additional predictive power when the US returns are negative or are ranked at the bottom 5%. Similar results are obtained, and these are available upon request.

⁶ Similarly, we perform the predictive power when the lagged US returns are ranked at the top 5%. The results are similar and these are available upon request.