Horse race of weekly idiosyncratic momentum strategies with respect to various risk metrics: Evidence from the Chinese stock market

This paper focuses on the horse race of weekly idiosyncratic momentum (IMOM) with respect to various idiosyncratic risk metrics. Using the A-share individual stocks in the Chinese market from January 1997 to December 2017, we first evaluate the performance of the weekly momentum based on raw returns and idiosyncratic returns, respectively. After that the univariate portfolio analysis is conducted to investigate the return predictability with respect to various idiosyncratic risk metrics. Further, we perform a comparative study on the performance of the IMOM portfolios with respect to various risk metrics. At last, we explore the possible explanations to IMOM as well as risk-based IMOM portfolios. We find that 1) there are prevailing contrarian effect and IMOM effect for the whole sample; 2) the negative relations exist between most of the idiosyncratic risk metrics and the cross-sectional stock returns, and better performance is linked to idiosyncratic volatility (IVol) and maximum drawdowns (IMDs); 3) additionally, the IVol-based and IMD-based IMOM portfolios exhibit better explanatory power to the IMOM portfolios with respect to other risk metrics; 4) finally, higher profitability of IMOM as well as IVol-based and IMD-based IMOM portfolios is found to be related to upside market states, high levels of liquidity and high levels of investor sentiment.     

Efficient predictability of stock return volatility: The role of stock market implied volatility

This study examines the predictability of stock market implied volatility on stock volatility in five developed economies (the US, Japan, Germany, France, and the UK) using monthly volatility data for the period 2000 to 2017. We utilize a simple linear autoregressive model to capture predictive relationships between stock market implied volatility and stock volatility. Our in-sample results show there exists very significant Granger causality from stock market implied volatility to stock volatility. The out-of-sample results also indicate that stock market implied volatility is significantly more powerful for stock volatility than the oil price volatility in five developed economies.     

The dynamic impact of oil price shocks on the stock market and the USD/RMB exchange rate: Evidence from implied volatility indices

Using daily data from March 16, 2011, to September 9, 2019, we explore the dynamic impact of the oil implied volatility index (OVX) changes on the Chinese stock implied volatility index (VXFXI) changes and on the USD/RMB exchange rate implied volatility index (USDCNYV1M) changes. Through a TVP-VAR model, we analyse the time-varying uncertainty transmission effects across the three markets, measured by the changes in implied volatility indices. The empirical results show that the OVX changes are the dominant factor, which has a positive impact on the USDCNYV1M changes and the VXFXI changes during periods of important political and economic events. Moreover, USDCNYV1M changes are the key factor affecting the impact of OVX changes on VXFXI changes. When the oil crisis, exchange rate reform, and stock market crash occurred during 2014–2016, the positive effects of uncertainty transmission among the oil market, the Chinese stock market, and the bilateral exchange rate are significantly strengthened. Finally, we find that the positive effects are significant in the short term but diminish over time.     

Economic policy uncertainty,oil price volatility and stock market returns: Evidence from a nonlinear model

This paper investigates the nonlinear relationship between economic policy uncertainty, oil price volatility and stock market returns for 25 countries by applying the panel smooth transition regression model. We find that oil price volatility has a negative effect on stock returns, and this effect increases with economic policy uncertainty. Furthermore, there is pronounced heterogeneity in responses. First, oil-exporting countries whose economies depend more on oil prices respond more strongly to oil price volatility than oil-importing countries. Second, stock returns of developing countries are more susceptible to oil price volatility than that of developed countries. Third, crisis plays a crucial role in the relation between oil price volatility and stock returns.     

COVID-19 and asymmetric volatility spillovers across global stock markets

In this study, I improve the assessment of asymmetry in volatility spillovers, and define six asymmetric spillover indexes. Employing Diebold-Yilmaz spillover index, network analysis, and my developed asymmetric spillover index, this study investigates the time-varying volatility spillovers and asymmetry in spillovers across stock markets of the U.S., Japan, Germany, the U.K., France, Italy, Canada, China, India, and Brazil based on high-frequency data from June 1, 2009, to August 28, 2020. I find that the global markets are well connected, and volatility spillovers across global stock markets are time-varying, crisis-sensitive, and asymmetric. Developed markets are the main risk transmitters, and emerging markets are the main risk receivers. Downside risk dominates financial contagion effects, and a great deal of downside risk spilled over from stock markets of risk transmitters into the global markets. Moreover, during the coronavirus recession, the total degree of volatility spillover is staying at an extremely high level, and emerging markets are the main risk receivers in the 2020 stock markets crash.     

The VIX,the variance premium and stock market volatility

We decompose the squared VIX index, derived from US S&P500 options prices, into the conditional variance of stock returns and the equity variance premium. We evaluate a plethora of state-of-the-art volatility forecasting models to produce an accurate measure of the conditional variance. We then examine the predictive power of the VIX and its two components for stock market returns, economic activity and financial instability. The variance premium predicts stock returns while the conditional stock market variance predicts economic activity and has a relatively higher predictive power for financial instability than does the variance premium.     

Are regulations the answer for emerging stock markets? Evidence from the Czech Republic and Poland

Does the emergence of a stock market require a well-developed legal and/or regulatory system? Although historical work by Neal and Davis [Neal, L., & Davis, L. (2005). The evolution of the rules and regulations of the first emerging markets: The London, New York, and Paris stock exchanges, 1792–1914. Quarterly Review of Economics and Finance, 45, 296–311] and Stringham [Stringham, E. (2003). The extralegal development of securities trading in seventeenth century Amsterdam. Quarterly Review of Economics and Finance, 43, 321–344] suggests that securities markets have successfully developed with little government oversight, numerous authors [including Black, B. (2001). The legal and institutional preconditions for strong securities markets. University of California Law Angeles Law Review, 48, 781–855; Coffee, J. (1999). Privatization and corporate governance: The lessons from securities market failure. Journal of Corporation Law, 25, 1–39; Frye, T. (2000). Brokers and bureaucrats: Building market institutions in Russia. Ann Arbor: University of Michigan Press; Glaeser, E., Johnson, S., & Shleifer, A. (2001). Coase versus the Coasians. Quarterly Journal of Economics, 116, 853–899; Mlčoch, L. (2000). Restructuring of property rights: An institutional view. In L. Mlčoch et al. (Eds.), Economic and Social Changes in Czech Society After 1989. Prague: The Karolinum Press; Pistor, K. (2001). Law as a determinant for equity market development – the experience of transition economies. In Peter Murrell (Ed.), The Value of Law in Transition Economies (pp. 249–287). Ann Arbor: Michigan University Press; Stiglitz, J. (1999). Whither reform. Ten years of the transition. Keynote Address, Annual Bank Conference on Development Economics, Washington, DC, April 28–30, 1999; Zhang, X. (2006). Financial market governance in developing countries: Getting the political underpinnings right. Journal of Developing Societies, 2, 169–196] argue that the Czech Republic and other Eastern European governments need more regulation for their newly created stock markets. They maintain that the Warsaw Stock Exchange, which is seen as more regulated, has outperformed the Prague Stock Exchange which is seen as largely unregulated. Thus increased regulations are a key to increased performance. This article, however, maintains that the evidence from the Czech experience has been misinterpreted. This article provides an in depth case study of the Czech stock market and finds that (a) Czech capital markets have been hindered by government intervention from their beginning, (b) that the evidence on Poland's superior performance is not as strong as suggested, and (c) that Czech regulators seem to be unqualified, lack the proper incentives, and are unlikely to benefit the market. Under these circumstances it appears that Neal and Davis (2005:311) are correct that increased government involvement is unlikely to improve the situation.     

Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching

The purpose of this paper is to investigate the role of regime switching in the prediction of the Chinese stock market volatility with international market volatilities. Our work is based on the heterogeneous autoregressive (HAR) model and we further extend this simple benchmark model by incorporating an individual volatility measure from 27 international stock markets. The in-sample estimation results show that the transition probabilities are significant and the high volatility regime exhibits substantially higher volatility level than the low volatility regime. The out-of-sample forecasting results based on the Diebold-Mariano (DM) test suggest that the regime switching models consistently outperform their original counterparts with respect to not only the HAR and its extended models but also the five used combination approaches. In addition to point accuracy, the regime switching models also exhibit substantially higher directional accuracy. Furthermore, compared to time-varying parameter, Markov regime switching is found to be a more efficient way to process the volatility information in the changing world. Our results are also robust to alternative evaluation methods, various loss functions, alternative volatility estimators, various sample periods, and various settings of Markov regime switching. Finally, we provide an extension of forecasting aggregate market volatility on monthly frequency and observe mixed results.     

The effects of accounting regulations on stock valuation and volatility: Evidence from the banking industry

Banking regulators and market participants learn from price signals in the stock market (e.g., Flannery, Journal of Money, Credit and Banking 30: 273, 1998). Therefore, the system becomes more secure and developed as stock prices become more informative about banks’ financial conditions. Using a sample that includes major banks from 35 countries, this study investigates how accounting regulations affect bank stock valuation and volatility. The evidence suggests that bank stocks have higher valuation and lower volatility in countries that strictly regulate the quality of external audits and financial statement transparency. This study presents a comprehensive picture of the effects of bank accounting regulations on the stock market.     

Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China

This article uses the stock market regional indexes of 31 provinces (include Province-level municipalities and Minority Autonomous Regions) in mainland China as a sample, and constructs an inter-regional volatility spillover network of China’s stock market based on the GARCH-BEKK model. Through network centrality analysis, Diebold and Yilmaz's spillover index method and block model analysis, we comprehensively analyze the risk contagion effect among different regions in China’s stock market. The empirical results show that: (i) The risk contagion intensity (risk reception intensity) in various regions of China’s stock market has a typical “core-periphery” distribution characteristic due to regions’ different levels of economic development. (ii) There are obvious risk spillover effect in China’s stock market, among which the economically developed regions along the southeastern coast of China, such as Beijing, Shanghai, Zhejiang and Jiangsu, are the main risk transmitters, while the economically undeveloped regions in the Midwest of China, such as Xinjiang, Xizang, Gansu, Nei Menggu and Qinghai are the main risk receivers. (iii) Each region is divided into 4 blocks according to their respective roles in the risk spillover process in China’s stock market. Block 1 that is composed of the economically underdeveloped regions in the Midwest is the “main benefit block”, it acts as a “receiver”. Block 2 that is composed of regions with strong economic growth vitality in the Midwest is a “Bilateral spillover block”, it both plays the role of “receiver” and “transmitter”. Block 3 that is composed of developed regions along the southeast coast, it acts as a “transmitter”; Block 4 that is composed of the relatively fast-growing regions in the Southwest is the “brokers block”, it serves as a “bridge”. The results of this article can provide some reference for investors in financial institutions and decision makers in financial regulators.     

Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach

In this study, we investigate the dependence structures between six Chinese stock markets and the international financial market including possible safe haven assets and global economic factors under different market conditions and investment horizons. The research is conducted by combining a quantile regression approach with a wavelet decomposition analysis. Although we find little or insignificant dependence under short investment horizons, we detect the strong asymmetric dependence of oil prices and the US dollar index on the six Chinese stock markets in the medium and long terms. Moreover, not only is crude oil not a safe haven, it may damage Chinese stock markets as it increases over the long term, even in bull markets. Meanwhile, appreciation of the US dollar (depreciation of RMB) damages (boosts) Chinese stock markets during bull (bear) market conditions under long investment horizons. Moreover, we find that VIX (volatility index)-related derivatives may serve as good risk management tools under any market condition, while gold is a safe haven asset only during crisis periods.     

Site visit information content and return predictability: Evidence from China

In this paper, we use frequency of related phrases in site visit summary reports to denote the site visit content, and study whether site visit content reflecting institutional investors’ market concerns can predict Chinese stock market return. We find that site visit content has greater forecasting power in Chinese stock market returns than other economic predictors after comparing out-of-sample R². The predictability is both statistically and economically significant. Additionally, our results also suggest that the particular information content has better forecasting power than general content in site visit summary reports.     

Carbon Financial Instruments, thin trading, and volatility: Evidence from the Chicago Climate Exchange

We provide the first econometric investigation of volatility dynamics for the Carbon Financial Instrument (CFI) traded on the Chicago Climate Exchange (CCX). A CFI is a financial contract with the right to emit 100 metric tons of CO₂ equivalent. In this study, we present evidence of infrequent trading in the CCX, consistent with emerging markets that are inhabited by non-competitive agents trading permits. We explore the relationship between the observed thin trading effects and GARCH model testing and estimation, concluding with some implications for volatility-based Value-at-Risk forecasts. Our results are important for traders of Carbon Financial Instruments and for policy makers seeking to improve the design of the Chicago Climate Exchange.     

The effects of employee stock ownership on stock liquidity: Evidence from the Korean market

This study investigates the relationship between the level of employee stock ownership (ESO) and stock liquidity. Using Korean ESO data, we find that ESO is positively associated with various liquidity measures. Stock-owning employees tend to mitigate information asymmetry to increase their benefits from the transparent market. We also find stronger effects when the firm is not an affiliate of a chaebol family group, and is less monitored by financial analysts, foreign investors, and outside directors. Furthermore, we employ various robustness tests to mitigate potential endogeneity concerns.     

Misvaluation comovement,market efficiency and the cross-section of stock returns: Evidence from China

In this study, we examine the relation between stock misvaluation and expected returns in China's A-share market. We measure individual stocks’ misvaluation based on their pricing deviation from fundamental values, following Rhodes-Kropf et al. (2005. J. Finan. Econ. 77 (3), 561) and Chang et al. (2013. J. Bank. Finance, forthcoming), and find that the measure has strong and robust return predictive power in the Chinese market. We further form a misvaluation factor and find that misvaluation comovement and systematic misvaluation exist in the Chinese market. A comparison of our results with those of Chang et al. (2013. J. Bank. Finance, forthcoming) reveals that the misvaluation effect is much stronger in the Chinese market than in the U.S market. This evidence is consistent with the notion that the Chinese market is much less efficient than the U.S. market. Finally, we show that the return predictive power of misvaluation has weakened since China launched its split-share structure reform in 2005, which could result from the fact that the reform helps to promote market efficiency.     

Modeling dynamic conditional correlations with leverage effects and volatility spillover effects: Evidence from the Chinese and US stock markets affected by the recent trade friction

In this article, we investigate the dynamic conditional correlations (DCCs) with leverage effects and volatility spillover effects that consider time difference and long memory of returns, between the Chinese and US stock markets, in the Sino-US trade friction and previous stable periods. The widespread belief that the developed markets dominate the emerging markets in stock market interactions is challenged by our findings that both the mean and volatility spillovers are bidirectional. We do find that most of the shocks to these DCCs between the two stock markets are symmetric, and all the symmetric shocks to these DCCs are highly persistent between Shanghai’s trading return and S&P 500′s trading or overnight return, however all the shocks to these DCCs are short-lived between S&P 500′s trading return and Shanghai’s trading or overnight return. We also find clear evidence that the DCC between Shanghai’s trading return and S&P 500′s overnight return has a downward trend with a structural break, perhaps due to the “America First” policy, after which it rebounds and fluctuates sharply in the middle and later periods of trade friction. These findings have important implications for investors to pursue profits.     

Economic policy uncertainty and stock market returns: New evidence

This paper investigates the predictive performance of the Chinese economic policy uncertainty (EPU) index constructed by Davis, Liu, and Sheng (2019) in forecasting the returns of China’s stock market. Using the univariate and bivariate predictive regression model, we confirm that the monthly EPU index can significantly and negatively impact the next month’s stock returns, and has better out-of-sample predictability than the existing EPU index and several macroeconomic variables. By comparing the forecasting effect of the EPU index before and during special events with sharply increased uncertainty, we find that the EPU’s forecasting power decline rapidly when an event of sharply increased uncertainty occurs. Finally, our conclusions are consistent through a batch of robustness tests.     

Liquidity and asset pricing: Evidence from the Chinese stock markets

We introduce a novel two-factor model, incorporating market and liquidity factors, which outperforms the CAPM and Fama–French factor models when applied to stock market returns in Shanghai and Shenzhen over 2000–2019. We compute the liquidity factor as the return on a liquidity-mimicking portfolio, which we construct simultaneously using two measures of liquidity (one of them capturing liquidity’s trading-quantity dimension, and the other associated with its price-impact dimension). Unlike the CAPM and Fama–French factor models, the advocated two-factor model is able to account for numerous return anomalies, such as size, book-to-market ratio, earnings-to-price ratio, cash-flow-to-price ratio, return-on-equity, and volatility. The model’s performance is similar when applied separately to the Shanghai and Shenzhen stock markets. Furthermore, it fares similarly over the 1994–2004 and 2005–2019 sub-periods. This result is somewhat surprising, because liquidity seems likely to have been substantially lower over 1994–2004, as the Chinese markets were noticeably smaller, and the critical market reform aimed at eliminating non-tradable shares by the end of 2006 did not occur until 2005.     

从内因与外因的辩证关系看中国股市如何走出困境

影响股市规范化的因素很多,然而什么是其最根本的因素呢?本文从内因与外因的辨证关系的角度,分析了影响我国股市的深层次原因,认为建立一只高素质的投资队伍才是中国股市脱困的根本出路.     

The relationship between oil prices,the stock market and the exchange rate: Evidence from Mexico

This paper analyzes the variables of oil price, exchange rate and stock market index to explain how they interact with each other in the Mexican economy. The examined period includes monthly data from January 1992 to June 2017. A Vector Autoregressive Model (VAR) is implemented that includes oil prices, the nominal exchange rate, the Mexican stock market index, and the consumer price index. Results indicate that the exchange rate has a negative and statistically significant effect on the stock market index; this indicates that an appreciation of the exchange rate is related to an increase in the stock market index. It is also found that the consumer price index has a positive effect on the exchange rate and a negative effect on the stock market index. The results also indicate that oil prices are statistically significant against the exchange rate, concluding that an increase in oil prices creates an appreciation of the exchange rate. In addition, the impulse-response functions show that the effects found tend to disappear over time.