US policy uncertainty and stock returns: evidence in the US and its spillovers to the European Union, China and Japan

Abstract

Purpose Recent empirical studies by Antonakakis, Chatziantoniou and Filis (2013), Brogaard and Detzel (2015) and Christou et al. (2017) present evidence, which supports the notion that a rise in economic policy uncertainty (EPU) will lead to a decline in stock prices. The purpose of this paper is to examine US categorical policy uncertainty on stock returns while controlling for implied volatility and downside risk. In addition to the domestic impacts of policy uncertainty, this paper also presents evidence that changes in US policy uncertainty promptly propagates to the global stock markets. Design/methodology/approach This study uses a GED-GARCH (1, 1) model to estimate changes of uncertainties in US monetary, fiscal and trade policies on stock returns for the sample period of January 1990–December 2018. Robustness test is conducted by using different set of data and modeling techniques. Findings This paper contributes to the literature in several aspects. First, testing of US aggregate data while controlling for downside risk and implied volatility, consistently, shows that responses of stock prices to US policy uncertainty changes, not only display a negative effect in the current period but also have at least a one-month time-lag. The evidence supports the uncertainty premium hypothesis. Second, extending the test to global data reveals that US policy uncertainty changes have a negative impact on markets in Europe, China and Japan. Third, testing the data in sectoral stock markets mainly displays statistically significant results with a negative sign. Fourth, the evidence consistently shows that changes in policy uncertainty present an inverse relation to the stock returns, regardless of whether uncertainty is moving upward or downward. Research limitations/implications The current research is limited to the markets in the USA, eurozone, China and Japan. This study can be extended to additional countries, such as emerging markets. Practical implications This paper provides a model that uses categorical policy uncertainty approach to explain stock price changes. The parametric estimates provide insightful information in advising investors for making portfolio decision. Social implications The estimated coefficients of changes in monetary policy uncertainty, fiscal policy uncertainty and trade policy uncertainty are informative in assisting policymakers to formulate effective financial policies. Originality/value This study extends the existing risk premium model in several directions. First, it separates the financial risk factors from the EPU innovations; second, instead of using EPU, this study investigates the effects from monetary policy, fiscal policy and trade policy uncertainties; third, in additional to an examination of the effects of US categorical policy uncertainties on its own markets, this study also investigates the spillover effects to global major markets; fourth, besides the aggregate stock markets, this study estimates the effects of US policy uncertainty innovations on the sectoral stock returns.

Can gold or silver be used as a hedge against policy uncertainty and COVID-19 in the Chinese market?

“…As a point of comparison to approaches taken in the literature, this section conducts a robustness test by replacing the ΔEPU t with the US market implied volatility, ΔVIX US t . In practice, market participants perceive that information of ΔVIX US t appears to be more visible, which is often viewed as a fear index in world financial markets given the dominant role of the US position (Rapach et al, 2013;Chiang, 2019Chiang, , 2020. The estimates estimated by replacing ΔVIX US t in the test equation are reported in Table 8.…”

“…In practice, market participants perceive that information of ΔVIXtUS appears to be more visible, which is often viewed as a fear index in world financial markets given the dominant role of the US position (Rapach et al. , 2013; Chiang, 2019, 2020). The estimates estimated by replacing ΔVIXtUS in the test equation are reported in Table 8.…”

Dividend policy and the downside risk in stock prices: evidence from the MENA region

“…The dependent variable (DOWNR) of this paper measures the downside risk embedded in the stock prices of firms. According to Chiang (2020), it is a risk measure that reflects the notion of uncertainty for stock prices as it indicates information on the most recent extreme shock for a given asset in the stock market. To calculate this risk, we use the maximum drawdown as an indicator of downside risk.…”

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