Is U.S. economic policy uncertainty priced in China's A-shares market? Evidence from market,industry, and individual stocks

This paper is motivated by Bali, Brown, and Tang (2017) who find U.S. economic policy uncertainty (EPU) is priced in the cross-section of U.S. stock returns, and uses weekly data from March 2006 to April 2016 to study whether shocks in U.S. EPU also influence prices of China's A-shares from a market, industry, and individual stock perspective. Our methodology relies on an ARMA (1,1) model to extract shocks in the U.S. EPU series and a GARCH (1,1) model to examine how returns of China's A-shares respond to these shocks after controlling for business conditions proxied by term and credit spread in China. Generally, we find that shocks in U.S. EPU significantly and negatively explain returns of Chinese A-shares with a lag of one week. In addition, the market index containing small and growth stocks is more sensitive to shocks in U.S. EPU than the index containing big and value stocks. Furthermore, we find that firms in manufacturing, information technology, and media industries in China are more sensitive to shocks in U.S. EPU, while firms in agriculture and real estate industries respond less to shocks in U.S. EPU. Finally, China's A-shares which decline more in response to shocks in U.S. EPU have higher returns, smaller market capitalization, weaker operating profitability, higher asset growth, and better past year's cumulative returns. Overall, our findings show that investors in the Chinese A-shares market require a premium to hold stocks that are sensitive to shocks in U.S. economic policy uncertainty.     

Impact of speculation and economic uncertainty on commodity markets

We examine the interactions between commodity futures returns and five driving factors (financial speculation, exchange rate, stock market dynamics, implied volatility for the US equity market, and economic policy uncertainty). Nonlinear causality tests are implemented after controlling for cointegration and conditional heteroscedasticity in the data over the period May 1990 – April 2014. Our results show strong evidence of unidirectional linear causality from commodity returns to excess speculation for the majority of the considered commodities, in particular for agriculture commodities. This evidence casts doubt on the claim that speculation is driving food prices. We also find unidirectional linear causality from energy futures markets to exchange rates and strong evidence of nonlinear causal dependence between commodity futures returns, on the one hand, and stock market returns and implied volatility, on the other hand. Overall, the new evidence found in this paper can be utilized for policy and investment decision-making.     

Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures

Using daily data from August 9, 2015, to July 7, 2020, this study examines the effects of economic policy uncertainty (EPU) on the returns of four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Ripple. To this end, two new measures of EPU (Twitter-based economic uncertainty and Twitter-based market uncertainty) are considered. A Granger causality test using the recursive evolving window approach shows a significant causality between the Twitter-based EPU measures and the BTC/USD exchange rate from October 2016 to July 2017. Moreover, a significant causality was noted from the EPU measures to the ETH/USD exchange rate from June 2019 to February 2020 and from the EPU measures to the XRP/USD exchange rate from January 2020 to February 2020. The Twitter-based EPU measures primarily positively affect the returns of the related cryptocurrencies during these periods. These results are robust to different measures of Twitter-based EPU and different econometric techniques. Potential implications, including the COVID-19 era, are also discussed.     

The dynamic interaction between volatility and returns in the US stock market using leveraged bootstrap simulations

One of the most important stylized facts in finance is that stock index returns are inversely related to volatility. The theoretical rationale behind the proposition is still controversial. The causal relationship between returns and volatility is investigated in the US stock market over the period 2004-2009 using daily data. We apply a bootstrap test with leveraged adjustments that is robust to non-normality and ARCH. We find that the volatility causes returns negatively and returns cause volatility positively. The policy implications of our findings are discussed in the main text.     

Empirical investigation of changes in policy uncertainty on stock returns—Evidence from China’s market

This study finds evidence that a rise in economic policy uncertainty (EPU) leads to a decline in stock returns in Chinese market; however, a positive coefficient was observed in the lagged EPU as stock prices rebound. This phenomenon also holds true for a rise in uncertainty innovations in fiscal policy, monetary policy, trade policy and global policy. The evidence leads to conclude that policy uncertainty premiums should be priced into China’s stock prices. An escalation of U.S. policy uncertainty has a significantly harmful effect on Chinese stocks regardless of whether firms are stated own or listed on U.S. market.     

The bivariate GARCH approach to investigating the relation between stock returns,trading volume,and return volatility

We use a bivariate GJR-GARCH model to investigate simultaneously the contemporaneous and causal relations between trading volume and stock returns and the causal relation between trading volume and return volatility in a one-step estimation procedure, which leads to the more efficient estimates and is more consistent with finance theory. We apply our approach to ten Asian stock markets: Hong Kong, Japan, Korea, Singapore, Taiwan, China, Indonesia, Malaysia, the Philippines, and Thailand. Our major findings are as follows. First, the contemporaneous relation between stock returns and trading volume and the causal relation from stock returns and trading volume are significant and robust across all sample stock markets. Second, there is a positive bi-directional causality between stock returns and trading volume in Taiwan and China and that between trading volume and return volatility in Japan, Korea, Singapore, and Taiwan. Third, there exists a positive contemporaneous relation between trading volume and return volatility in Hong Kong, Korea, Singapore, China, Indonesia, and Thailand, but a negative one in Japan and Taiwan. Fourth, we find a significant asymmetric effect on return and volume volatilities in all sample countries and in Korea and Thailand, respectively.     

Can Insurance Activity Act as a Stimulus of Economic Growth? Evidence from Time-Varying Causality in China

This article investigates the nexus between insurance and economic growth in China with a dynamic interactive mechanism to study different time periods. Using quarterly data from 1999 to 2015, the rolling-window causality test provides evidence of bidirectional causality between insurance activity and economic growth. However, the “supply-leading” pattern tends to dominate the “demand-following” pattern, which implies that in China insurance acts as a stimulus of economic growth during most of the period. Property insurance is more effective than life insurance in stimulating economic growth. Some temporary negative impacts from the development of the insurance sector show that China is in the midst of a transition from a closed economy to a more open economy and policy interventions by the government to liberalize the insurance sector. These findings offer several useful insights for policy makers in transition economies and developing countries.     

A comparative analysis of cryptocurrency returns and economic policy uncertainty pre- and post-Covid-19

This study analyzes the impact of economic policy uncertainty (EPU) on cryptocurrency returns for a sample of 100 highly capitalized cryptocurrencies from January 2016 to May 2021. The results of the panel data analysis and quantile regression show that increases in global EPU have a positive impact on cryptocurrency returns for lower cryptocurrency returns quantiles and an adverse impact for upper quantiles. In line with the existing literature, the Covid-19 pandemic resulted in higher returns for cryptocurrencies. Inclusion of a Covid-19 dummy in the models strengthened the impact of EPU on cryptocurrency returns. Furthermore, the relationship between the change in EPU and cryptocurrency returns was direct in the pre-Covid-19 period but inverse in the post-Covid-19 period. These results imply that cryptocurrencies act more like traditional financial assets in the post-Covid-19 era.     

Policy uncertainty and peer effects: Evidence from corporate investment in China

This study investigates whether economic policy uncertainty (EPU) magnifies peer effects in corporate investment in China and the economic mechanisms through which EPU may act upon this property. We examine this relationship by analysing a large sample of publicly listed companies in China for the period of 2009–2019, adopting the peer-firm-average idiosyncratic stock return to capture exogenous variations in peer firms’ investment activities. We demonstrate that peer effects are stronger when EPU is increasing in intensity. We also find that high EPU magnifies peer effects by decreasing the accuracy of firms’ signals regarding their investment opportunities, asymmetrically impacting their capacity to acquire information and exacerbating managers’ career concerns. We further show that increased EPU magnifies peer effects only for underinvesting firms, causing underinvestment to persist and retarding recovery from an economic downturn. Our investigation provides original evidence of how EPU influences corporate investment decisions through peer effects, contributing to the continuing debate on the role of EPU and corporate investment efficiency by establishing that the adoption of consistent and transparent economic policies optimize returns on a company’s investments, especially during an economic downturn.     

A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns

This study uses economic policy uncertainty (EPU) indices for ten developed countries, three diffusion models, and five combination methods to forecast excess returns in the U.S. stock market. It shows empirically that, over the period January 1997 to January 2022, non-U.S. EPU indices have better predictive power for U.S. equity market excess returns than the U.S. EPU index itself. This illustrates how economic information from international markets can affect the U.S. stock market. This finding challenges the extensively recognized view that the U.S. is where important market signals are initially transmitted to other markets, suggesting that this belief is incomplete. Our outcomes are robust to a battery of tests covering model selection, model specification, forecast horizons, and the pandemic period, and their economic values are assessed. The findings are essential for the financial field to confront future fierce situations and crises.     

Is VIX an investor fear gauge in BRIC equity markets?

This study examines the intertemporal relationships between CBOE market volatility index (VIX) and stock market returns in Brazil, Russia, India, and China (BRIC), and between VIX and U.S. stock market returns, to uncover if VIX serves as an investor fear gauge in BRIC and U.S. markets. We conduct the VIX-returns analysis for the 1993–2007 period.Our results suggest a strong negative contemporaneous relation between daily changes (innovations) in VIX and U.S. stock market returns. This relation is stronger when VIX is higher and more volatile. A significant negative contemporaneous relation between VIX and equity returns also exists for China and Brazil during 1993–2007 and for India during 1993–1997. Similar to the U.S. market, the immediate negative relation between the Brazilian stock returns and VIX changes is much stronger when VIX is both high and more volatile. Our results also indicate a strong asymmetric relation between innovations in VIX and daily stock market returns in U.S., Brazil, and China, suggesting that VIX is more of a gauge of investor fear than investor positive sentiment. However, the asymmetric relationship between stock market returns and VIX is much weaker when VIX is large and more volatile. These results have potential implications for portfolio diversification and for stock market and option trading timing in the equity markets of Brazil, India, and China. Overall, our results indicate that VIX is not only an investor fear gauge for the U.S. stock market but also for the equity markets of China, Brazil, and India.     

Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China

This study explores the spillovers between economic policy uncertainty (EPU) and stock market realized volatility (RV). The monthly index of Chinese and US EPU and RV are used to analyze the pairwise directional spillovers. We find that RV is a net receiver that is more vulnerable to shocks from U.S. EPU than to shocks from Chinese EPU. We further decompose the RV into good and bad volatility to test the asymmetric spillover effect between the stock market and EPU. The results suggest that EPU has a bigger effect on bad volatility in the stock market throughout most of the sample period. However, we find that good volatility spillovers become larger during periods of stimulated reform, whereas bad volatility spillovers become larger during periods of international disputes. We show that Chinese stock market volatility is sensitive to both U.S. and Chinese EPU and that the spillover is asymmetric in different periods.     

Category-specific EPU indices,macroeconomic variables and stock market return predictability

This paper mainly investigates whether the category-specific EPU indices have predictability for stock market returns. Empirical results show that the content of category-specific EPU can significantly predict the stock market return, no matter the individual category-specific EPU index or the principal component of category-specific EPU indices. In addition, the information of category-specific EPU indices can also have higher economic gains than traditional macroeconomic variables, even considering the trading cost and different investor risk aversion coefficients. During different forecasting windows, multi-period forecast horizons and the COVID-19 pandemic, we find the information contained in category-specific EPU indices can have better performances than that of the macroeconomic variables. Our paper tries to provide new evidence for stock market returns based on category-specific EPU indices.     

Economic policy uncertainty exposure and stock price bubbles: Evidence from China

We explore the impact of economic policy uncertainty exposure (hereafter, EPU exposure) on stock price bubbles. We find that there exists a significantly positive relationship between EPU exposure and stock price bubbles. This result is still significant after a series of robustness checks. Moreover, the relationship between EPU exposure and bubbles is due to retail investors' speculative trading behavior. In addition, optimistic aggregate states and firms with higher information uncertainty characteristics strengthen the EPU exposure effects. Overall, we provide unique evidence regarding the impact of uncertainty on stock prices.     

Main driving factors of the interest rate-stock market Granger causality

This paper investigates the causal relationship between changes in the 10-year Treasury bond yield and the S&P 500 stock return in the United Sates with emphasis on time variation, stress factors and smooth regime transition. First, the time-varying Granger causality test proposed by Lu et al. (2014) is applied. Then a two-regime multifactor smooth transition regression model with a single transition variable representing a wide range of macroeconomic and financial variables is estimated in order to identify the key explanatory factors governing the causal relationship. The results show a significant bidirectional causal relationship over most of the study period, mainly due to the strong simultaneous interactions between the bond interest rate and the stock returns, and the causal link has strengthened since the beginning of the U.S. sub-prime crisis in the summer of 2007. Moreover, the U.S. financial stress indices seem to play a key role in explaining the dynamics of the causal relationship between the long-term interest rates and the stock returns, especially during the recent global financial crisis.     

Mutual Funds and Stock and Bond Market Stability

The unprecedented growth of mutual funds has raised questions about the impact of mutual fund flows on stock and bond prices. Many believe that the equity bull market of the 1990s is attributable to the huge flows of funds into equity mutual funds during this period and that a withdrawal of those funds could send stock prices plummeting. This article investigates the relationship between aggregate monthly mutual fund flows (sales, redemptions, and net sales) and stock and bond monthly returns during a 30-year period beginning January 1961 utilizing Granger causality and instrumental variables analysis. With one exception, flows into stock and bond funds have not affected either stock and bond returns. The exception is 1971–1981, when widespread redemptions from equity mutual funds significantly depressed stock returns. In contrast, the magnitude of flows into both stock and bond funds are affected significantly by stock and bond returns.     

A VARMA Analysis of the Causal Relations Among Stock Returns,Real Output,and Nominal Interest Rates

Previous research has documented a negative relation between common stock returns and inflation. Recently, Fama 3 and Geske and Roll 6 have argued that this relation results from a more fundamental one between real activity and expected inflation. Stock returns, they argue, signal changes in real activity, which in turn affect expected inflation. However, unlike Fama, Geske and Roll argue that changes in real activity result in changes in money supply growth, which in turn affect expected inflation. Empirical tests have analyzed separately each link in the proposed causal chain. In this article, we investigate simultaneously the relations among stock returns, real activity, inflation, and money supply changes using a vector autoregressive moving average (VARMA) model. Our empirical results strongly support Geske and Roll's reversed causality model.     

Who drives whom ‐ sukuk or bond? A new evidence from granger causality and wavelet approach

Sukuk is a highly appealing alternative instrument of conventional bond in the financial market over the last two decades. To a certain extent, the market players assume sukuk as the same as bond. However, sukuk has its own fundamental asset backed principles, whereas bond is backed by debt. The objective of the study is to examine the Granger‐causality and lead–lag relationship between sukuk and bond by using the data of the Malaysian Government securities return for both conventional and Islamic instruments. The data for every working day of 7 years covering the period from January 31, 2007 to December 31, 2013 were collected from Bloomberg database. The yield returns of both securities have been plotted for each six months of a year. This study applied both Granger‐causality and dynamic co‐movement techniques such as, continuous wavelet transforms (CWT) coherence for analyzing the temporal evolution of the frequency content of both securities by decomposing each period into different time scales. The empirical findings of the paper reveal that with a bit of exception, there is a causal relationship between sukuk securities and conventional bonds for a given period of time. For robustness, this study applied the wavelet coherence approach and found that bond is led by sukuk in the long term investment horizon rather than in the short term. Our findings relating to the lead‐lag relationship between sukuk and bonds have important implications in terms of policy regulations and investment management. Future research and market practices could reinvestigate the differences between these two securities across different markets and types.     

A High‐Frequency Investigation of the Interaction between Volatility and DAX Returns

One of the most noticeable stylised facts in finance is that stock index returns are negatively correlated with changes in volatility. The economic rationale for the effect is still controversial. The competing explanations have different implications for the origin of the relationship: Are volatility changes induced by index movements, or inversely, does volatility drive index returns? To differentiate between the alternative hypotheses, we analyse the lead‐lag relationship of option implied volatility and index return in Germany based on Granger causality tests and impulse‐response functions. Our dataset consists of all transactions in DAX options and futures over the time period from 1995 to 2005. Analyzing returns over 5‐minute intervals, we find that the relationship is return‐driven in the sense that index returns Granger cause volatility changes. This causal relationship is statistically and economically significant and can be clearly separated from the contemporaneous correlation. The largest part of the implied volatility response occurs immediately, but we also observe a smaller retarded reaction for up to one hour. A volatility feedback effect is not discernible. If it exists, the stock market appears to correctly anticipate its importance for index returns.     

Economic policy uncertainty and environmental governance company volatility: Evidence from China

This study primarily investigates whether China’s economic policy uncertainty (EPU) can predict the environmental governance index volatility, which selects companies regarding environmental protection such as sewage treatment, solid waste treatment, air treatment, and energy saving. Empirical results reveal that China’s EPU index can predict the environmental governance index volatility. Furthermore, even during periods of fluctuating volatility and the COVID-19 pandemic, China’s EPU index can reliably forecast the environmental governance index volatility. This paper tries to provide new evidence regarding the connection between EPU and environmental governance companies’ stock volatility.