Asymmetric volatility spillover between oil-importing and oil-exporting countries' economic policy uncertainty and China's energy sector

While the relationship between economic policy uncertainty(EPU) and energy market is of great interest to economist, previous research dose not differentiate the effect from oil-importing countries to oil-exporting countries' EPU on the a country's energy sector. In this paper, we address this issue by testing the effect of importer and exporter's EPU on the largest oil-importing country, China, as oil-importing affected greatly by the economic policy. TVP-FAVAR model is applied to obtain the factors and time-varying coefficients of 21 countries' EPU monthly indexes and energy stock realized volatility. We find that the Chinese energy sector's stock volatility is positively related to EPU shocks and that bad volatility has a stronger impact than good volatility. Second, the volatility spillover from oil-exporting countries' EPU on the Chinese energy sector is stronger than that from oil-importing countries' EPU, with a stronger effect for bad volatility than for good volatility. Finally, The bad volatility spillover and spillover asymmetry is stronger during the crisis periods, such as the debt crisis, energy contention, oil price turbulence, or limited production agreement, both symmetric and asymmetric spillovers increase. Our findings have potentially important implications for the regulators and investors on Chinese oil market with different types of countries' EPU.     

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.     

Examining the relationship between policy uncertainty and market uncertainty across the G7

Economic policy uncertainty (EPU) relates to ambiguity surrounding possible changes in government policy and their associate impact on firm performance. This uncertainty places additional stress on economic agents and has implications for the global economy via delays in firm investment and hiring, and postponement of household consumption. We utilise the EPU measure of Baker et al. (2016) to investigate whether financial market uncertainty is related to policy uncertainty across the G7 economies. Our empirical results show that financial market uncertainty (implied volatility) increases as economic policy uncertainty increases (and the economy weakens). This relationship holds even after controlling for macroeconomic state variables and country/time fixed effects, and is consistent for monthly and daily data frequency. The correlation of political uncertainty among countries varies over time, increasing in tranquil times with low EPU, and sharply decreasing during times of crisis. We also show that US and Japanese policy uncertainty has an economic and statistically significant relationship with global financial market uncertainty, a spill-over effect that is consistent with the size of their economies, and the important role that US policy decisions play in the global economy.     

Economic policy uncertainty,investor attention and post-earnings announcement drift

How the market incorporates information into stock price is a core issue in finance. This study focuses on the impact of economic policy uncertainty (EPU) on the stock prices information efficiency of China's A-share market and underlying role of investors' attention allocation mechanism. This study analyzes the information efficiency of stock prices using the sensitivity of stock cumulative abnormal return to earnings information across different windows following earnings announcement. Based on the earnings announcement events of listed companies in China's A-share market, this study presents an empirical study of the aforementioned issues using event study and regression analysis methods. The following results are seen: (1) EPU aggravates the underreaction of stock price earnings information and the post-earnings announcement drift in the A-share market. (2) Under highly uncertain economic policies, investors show a limited attention allocation pattern of devoting increasing attention to macroeconomic policies and decreasing attention to earnings information, which leads to a decrease in the information efficiency of stock price. This study also analyzes the heterogeneity of the influence of EPU on stock price information efficiency using the institutional shareholding ratio. The results show that increasing institutional shareholding does not reduce the adverse effects of EPU on the information efficiency of stock prices. This study not only provides empirical evidence for Brunnermeier, Sockin, and Xiong (2022) and rational inattention theory, but also reveals that institutional investors show similar behavioral characteristics to retail investors in China's stock market. The results of this study have policy significance for improving the information efficiency of stock market.     

Dynamic and frequency-domain spillover among economic policy uncertainty,stock and housing markets in China

This study examines the dynamic characteristics of information spillover effect among economic policy uncertainty (EPU), stock and housing markets in China's first-, second- and third-tier cities. To measure return and volatility spillovers over time and across frequencies simultaneously, the researchers utilize the time-frequency connectedness network approach developed by Baruník and Křehlík (2018). The empirical findings suggest that return and volatility spillovers are stronger in the longer period (more than 3 months) than in the shorter period (1 to 3 months). In the short term, second and third-tier cities are net transmitters of information spillovers, while in the long term, first-tier cities, EPU, and stock markets are the net information transmitters. Furthermore, the long-term information from the EPU and stock market affect most of the real estate markets for different tier cities. Additionally, market segmentation reveals the city-specific characteristics of China's real estate market, especially the close connections between first-tier cities and the stock market. These results have important empirical implications for real estate policymakers and investors when they make related short or long-term decisions.     

Stock market entry timing and retail investors' disposition effect

This paper explores the long-lasting impact of investors' first impression of participation in the stock market and the disposition effect. Using a unique dataset of account-level transaction records from a large brokerage firm in China, we find strong evidence for the existence of a disposition effect of Chinese retail investors. Our empirical results suggest that investors exhibit a stronger disposition effect if they initially participate in the stock market in periods of lower market returns, lower investor sentiment, higher market volatility, or higher economic policy uncertainty (EPU). The evidence enhances our understanding of the role of investors' early experience in stock market decisions and the determinants of behavioural biases in investment decisions.     

不同的政策不确定性对股市波动影响相同吗?

本文基于多因子混频波动率模型,研究经济政策不确定性对股市行业波动的影响,为预防出现结构性断点,将样本分为经济增长和经济平稳两个时期,分别探讨两个时期内经济政策不确定性对股市波动的影响。研究发现,在全样本时期货币政策不确定性会显著增强行业波动,贸易和外汇政策不确定性会抑制行业波动,而财政政策不确定性的影响存在行业差异性;子样本结果显示,贸易政策不确定性对行业波动的影响存在非对称性,在经济增长期存在助推作用,在经济平稳期存在抑制作用;同时行业波动在经济增长期对贸易政策反应敏感,在经济平稳期对财政政策反应敏感。     

The Causal Relationship Between Economic Policy Uncertainty and Stock Returns in China and India: Evidence from a Bootstrap Rolling Window Approach

This article applies a bootstrap rolling-window causality test to assess the causal relationship between economic policy uncertainty (EPU) and stock returns in China and India. Empirical literature examining causality between two time series may suffer from inaccurate results when the underlying full-sample time series have structural changes. However, the bootstrap rolling-window approach enables us to identify possible time-varying causalities between time series based on sub-sample data. Using a twenty-four-months rolling window over the period 1995:02 to 2013:02 in China and 2003:02–2013:02 in India, we do find that there are bidirectional causal relationships between EPU and stock returns in several sub-periods rather than in the whole sample period. However, the association between EPU and stock returns is, in general, weak for these two emerging countries. Our findings have important implications for policy makers and investors.     

Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?

This study mainly investigates which predictors (VIX or EPU index) are useful to forecast future volatility for 19 equity indices based on HAR framework during coronavirus pandemic. Out-of-sample analysis shows that the HAR-RV-VIX model exhibits superior forecasting performance for 12 stock markets, while EPU index just can improve forecast accuracy for 5 equity indices, implying that VIX index is more useful for most stock markets' future volatility during coronavirus crisis. The results are robust in recursive window method, alternative realized measures and sub-sample analysis; moreover, VIX index still contains the strongest predictive ability by considering kitchen sink model and mean combination forecast. Furthermore, we further discuss the predictive effect of VIX and EPU index before the coronavirus crisis. Our article provides policy makers, researchers and investors with new insights into exploiting the predictive ability of VIX and EPU index for international stock markets during coronavirus pandemic.     

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.     

Global economic uncertainty and the Chinese stock market: Assessing the impacts of global indicators

We comparatively assess the influence of global economic uncertainty measures on Chinese stock market volatility. Using a model based on generalized autoregressive conditional heteroskedasticity and mixed-data sampling, the results show that the global economic policy uncertainty index, the geopolitical risk index, and the global economic condition index all significantly influence the long-term volatility of China’s equity market. We highlight which of these measures has the most explanatory power under differing contexts. As uncertainty measures have wide applicability, investors, policymakers, and academicians will be quite interested in our results.     

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.     

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.     

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.     

Economic policy uncertainty and corporate inventory holdings: evidence from China

We investigate the impact of economic policy uncertainty (EPU) on corporate inventory holdings in China over the period 2007–2017. We find that EPU leads firms to significantly reduce inventory holdings and this effect is particularly pronounced among non-state-owned enterprises. The adjustment of inventory holdings enhances firms’ operating and market performance consequently. In addition, firms with greater financial constraints or stronger external governance are more affected by EPU. Further exploration shows that EPU induces high precautionary cash holdings, which crowds out inventories. Our results illustrate that firms reallocate between inventories and cash to cope with uncertainty associated with economic policy changes.     

Macroeconomic attention,economic policy uncertainty,and stock volatility predictability

This study adopts the newly constructed macroeconomic attention indices (MAI) and category-specific economic policy uncertainty (EPU) indices to predict stock volatility. Principal component analysis (PCA), scaled PCA (sPCA), and partial least squares (PLS) are used to extract the principal components from indicators. The results show that the combination of MAI and EPU indices can obtain additional information for predicting stock market volatility. In addition, the comprehensive index containing all indicator information (F_t^All) has the strongest short-term forecasting ability, whereas the MAI show the most substantial forecasting ability in long-term forecasting.     

Comparing the impact of Chinese and U.S. economic policy uncertainty on the volatility of major global stock markets

This study compares the impact of Chinese and U.S. economic policy uncertainty (EPU) (proxied by the EPU index) on the volatility of 11 major stock markets. Unlike previous research that only utilizes monthly EPU for such a comparison, this study uses both daily and monthly data to examine the impact within a month as well as over months. In order to provide a detailed analysis, EPU shocks are investigated from a two-sided viewpoint: one considering the effects of EPU indices as exogenous shocks, and the other examining the spillovers from EPU indices as endogenous variables. Meanwhile, the role of global turmoil, such as the 2007–2008 global financial crisis (GFC) and the COVID-19 pandemic, in influencing the impact of Chinese (or U.S.) EPU is highlighted. The results show that the impact of U.S. EPU is reinforced at both daily and monthly frequencies during the GFC, with a greater effect on the European stock markets. After the GFC, the rising influence of Chinese EPU is observed at a monthly frequency in several markets in Asia and elsewhere. Overall, the dynamic spillovers from the EPU indices to stock volatility suggest the dominant role of U.S. EPU in most markets at a daily frequency, while the extent of the spillovers is driven by turbulent events, including the GFC and the COVID-19 pandemic.     

US presidential elections and implied volatility: The role of political uncertainty

This paper focuses on the effects of political uncertainty and the political process on implied stock market volatility during US presidential election cycles. Using monthly Iowa Electronic Markets data over five elections, we document that stock market uncertainty, as measured by the VIX volatility index, increases along with positive changes in the probability of success of the eventual winner. The association between implied volatility and the election probability of the eventual winner is positive even after controlling for changes in overall election uncertainty. These findings indicate that the presidential election process engenders market anxiety as investors form and revise their expectations regarding future macroeconomic policy.     

Economic policy uncertainty,corporate investment decisions and stock price crash risk: Evidence from China

We examine the relationship between economic policy uncertainty (EPU) and stock price crash risk via the corporate investment in Chinese listed firms. Results show that higher EPU is associated with lower crash risk. Firms increase financial asset holdings and reduce overinvestment when EPU rises, leading to lower future crash risk. State-owned enterprises (SOEs) and firms with lower management incentives tend to reduce overinvestment, whereas non-SOEs tend to increase financial asset holdings. Thus, firms tend to be cautious in their investments when EPU is high, which reduces crash risk. Our study provides new insights into the validity of the Lucas critique in China.     

Less is more? New evidence from stock market volatility predictability

The complex nature of stock market volatility has motivated researchers to apply a variety of predictors to obtain reliable predictive information for precise forecasting. This study seeks to examine the effectiveness of the novel Global Financial Uncertainty (GFU) indices, comprising of only five sub-indices, in predicting stock market volatility using the widely used mixed-data sampling (MIDAS) model. The results demonstrate the remarkable and stable predictive power of GFU, even during crises and global financial uncertainty shocks. Specifically, the financial uncertainty index from Europe plays a significant role in our analysis. Importantly, we find that the GFU index outperforms a large number of other indicators in stock volatility forecasting. The statistical and economic significance of the predictive power of GFU is remarkable. Our study provides significant insights for market participants and policymakers that highlight the need to prioritize global financial uncertainty.