The role of oil futures intraday information on predicting US stock market volatility

This study investigates the role of oil futures price information on forecasting the US stock market volatility using the HAR framework. In-sample results indicate that oil futures intraday information is helpful to increase the predictability. Moreover, compared to the benchmark model, the proposed models improve their predictive ability with the help of oil futures realized volatility. In particular, the multivariate HAR model outperforms the univariate model. Accordingly, considering the contemporaneous connection is useful to predict the US stock market volatility. Furthermore, these findings are consistent across a variety of robust checks.     

Multivariate volatility forecasts for stock market indices

Volatility forecasts aim to measure future risk and they are key inputs for financial analysis. In this study, we forecast the realized variance as an observable measure of volatility for several major international stock market indices and accounted for the different predictive information present in jump, continuous, and option-implied variance components. We allowed for volatility spillovers in different stock markets by using a multivariate modeling approach. We used heterogeneous autoregressive (HAR)-type models to obtain the forecasts. Based an out-of-sample forecast study, we show that: (i) including option-implied variances in the HAR model substantially improves the forecast accuracy, (ii) lasso-based lag selection methods do not outperform the parsimonious day-week-month lag structure of the HAR model, and (iii) cross-market spillover effects embedded in the multivariate HAR model have long-term forecasting power.     

Forecasting stock price volatility: New evidence from the GARCH-MIDAS model

This paper introduces a combination of asymmetry and extreme volatility effects in order to build superior extensions of the GARCH-MIDAS model for modeling and forecasting the stock volatility. Our in-sample results clearly verify that extreme shocks have a significant impact on the stock volatility and that the volatility can be influenced more by the asymmetry effect than by the extreme volatility effect in both the long and short term. Out-of-sample results with several robustness checks demonstrate that our proposed models can achieve better performances in forecasting the volatility. Furthermore, the improvement in predictive ability is attributed more strongly to the introduction of asymmetry and extreme volatility effects for the short-term volatility component.     

Deregulation and liberalization of the Chinese stock market and the improvement of market efficiency

This study employs single and multiple variance ratio tests to reexamine the weak-form efficient market hypothesis (EMH) of A- and B-shares on the Shanghai and Shenzhen exchanges in Chinese stock market. The study also examines the influence of the release of investment restriction of B-share markets on market efficiency. For the whole sample period, the weak-form EMH is only supported for Shanghai A-shares, and is not supported for the remaining shares. For the sub-sample period, the Shenzhen A-share and B-shares of both exchanges being rejected for the weak-form EMH in the earlier sample period are supported following the regulatory change. Rolling multiple variance ratio test statistic values provide additional evidence of weak-form EMH. The improvement of market efficiency can be explained by the increased liquidity and maturity accompanying deregulation and liberalization.     

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.     

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.     

货币反替代及其对中国股市的冲击

货币反替代是指在一国的经济发展过程中,居民在本币坚挺且存在升值趋势下,普遍看好本币的币值或在本币货币资产收益率明显高于外国货币资产收益率时,改变原来对外币的偏好,从而抛售外币资产,持有本币资产,使外币过分集中于中央银行的行为和现象。本文在封“热钱”的内涵进行辨析的基础土,分析货币反替代的目的和渠道,并封1990—2007年货币反替代率进行测度,进而实证检睑货币反替代封中国股市的冲击,研究发现：货币反替代规模较大、流动速度加快、反转性强;货币反替代与国内股票价格正相关,即货币反替代会推动国内股价上涨;当货币反替代出现反转时,则会引起国内股价下跌.     

Evolving United States stock market volatility: The role of conventional and unconventional monetary policies

Despite the econometric advances of the last 30 years, the effects of monetary policy stance during the boom and busts of the stock market are not clearly defined. In this paper, we use a structural heterogeneous vector autoregressive (SHVAR) model with identified structural breaks to analyse the impact of both conventional and unconventional monetary policies on U.S. stock market volatility. We find that contractionary monetary policy enhances stock market volatility, but the importance of monetary policy shocks in explaining volatility evolves across different regimes and is relative to supply shocks (and shocks to volatility itself). In comparison to business cycle fluctuations, monetary policy shocks explain a greater fraction of the variance of stock market volatility at shorter horizons, as in medium to longer horizons. Our basic findings of a positive impact of monetary policy on equity market volatility (being relatively stronger during calmer stock market periods) are also corroborated by analyses conducted at the daily frequency based on an augmented heterogeneous autoregressive model of realised volatility (HAR-RV) and a multivariate k-th order nonparametric causality-in-quantiles framework. Our results have important implications both for investors and policymakers.     

Lottery mindset,mispricing and idiosyncratic volatility puzzle: Evidence from the Chinese stock market

This study investigates the MAX effect regarding lottery mindset in the Chinese stock market. The MAX effect significantly affects stock returns through quintile portfolio and cross-sectional regression analyses. The most-overpriced stock groups, as categorized by mispricing index, show more support for the MAX effect. However, the idiosyncratic volatility (IVOL) effect continues regardless of consideration for the MAX effect, indicating that the MAX effect is not a source of the IVOL effect. Our results suggest that the MAX effect, which is highly relevant for overpriced stocks, might have information for determining stock price, and appears to be independent from information of the IVOL effect in the Chinese stock market.     

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.     

The benefits of international diversification: Re-examining the effect of market allocation constraints

This paper makes adjustments to the data, methods and perspective as presented in Chiou (2008) to report lower potential benefits from international diversification for U.S. investors during the previously reported 1988–2004 investment period. The extended results for 1988–2014 are also presented. Naive international diversification is not found to provide positive return-to-risk (RR) gains or volatility reducing benefits versus the U.S. market. Portfolios optimized with no short sales and weakened weight constraints on positive market allocations can provide RR gains and volatility reducing benefits. The positive RR benefits from diversification out of the U.S. market portfolio are not found to be statistically significant for both periods measured.     

Similarity of emerging market returns under changing market conditions: Markets in the ASEAN-4, Latin America,Middle East,and BRICs

We studied the risk-return distances of 18 emerging stock markets in the period from January 2000 to December 2013. Distances are linked to volatility and time-varying correlations estimated in standard and asymmetric DCC models. Our results revealed a positive relationship between risk-return distances and volatility, which means that during more volatile periods, the risk-return characteristics in emerging markets exhibit lower similarity to the characteristics found in developed markets. This result seems to be in sharp contrast to most empirical studies using correlations. Within the portfolio framework, our results suggest that diversification into emerging stock markets may still provide desirable benefits to international investors.     

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.     

Forecasting the volatility of asset returns: The informational gains from option prices

A new class of forecasting models is proposed that extends the realized GARCH class of models through the inclusion of option prices to forecast the variance of asset returns. The VIX is used to approximate option prices, resulting in a set of cross-equation restrictions on the model’s parameters. The full model is characterized by a nonlinear system of three equations containing asset returns, the realized variance, and the VIX, with estimation of the parameters based on maximum likelihood methods. The forecasting properties of the new class of forecasting models, as well as a number of special cases, are investigated and applied to forecasting the daily S&P500 index realized variance using intra-day and daily data from September 2001 to November 2017. The forecasting results provide strong support for including the realized variance and the VIX to improve variance forecasts, with linear conditional variance models performing well for short-term one-day-ahead forecasts, whereas log-linear conditional variance models tend to perform better for intermediate five-day-ahead forecasts.     

Probabilistic forecasting of industrial electricity load with regime switching behavior

This paper suggests a novel inhomogeneous Markov switching approach for the probabilistic forecasting of industrial companies’ electricity loads, for which the load switches at random times between production and standby regimes. The model that we propose describes the transitions between the regimes using a hidden Markov chain with time-varying transition probabilities that depend on calendar variables. We model the demand during the production regime using an autoregressive moving-average (ARMA) process with seasonal patterns, whereas we use a much simpler model for the standby regime in order to reduce the complexity. The maximum likelihood estimation of the parameters is implemented using a differential evolution algorithm. Using the continuous ranked probability score (CRPS) to evaluate the goodness-of-fit of our model for probabilistic forecasting, it is shown that this model often outperforms classical additive time series models, as well as homogeneous Markov switching models. We also propose a simple procedure for classifying load profiles into those with and without regime-switching behaviors.     

论另类股票市场的功能

融资渠道是中小高科技创新型企业发展所面临的主要问题,而创业投资又面对出口问题。文章认为另类股票市场能较有效地解决这两个问题。     

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.     

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.