Economic policy uncertainty and the Chinese stock market volatility: Novel evidence

In this study, we investigate the impact of global economic policy uncertainty (GEPU) on Chinese stock market volatility. More importantly, for the first time, we explore the effects of directional GEPU based on the changing directions of GEPU and Chinese economic policy uncertainty (EPU). We make several noteworthy findings. First, the in-sample estimated results show that up and down GEPU can lead to substantially high stock market volatility for China. Second, the out-of-sample estimated results support the contention that the GEPU index is helpful for predicting volatility. Moreover, compared to GEPU alone, directional GEPU can provide more useful information that can increase the forecast accuracy. Third, we empirically find that directional GEPU is more effective in predicting Chinese stock market volatility when GEPU and EPU rise in the same month.     

The source of global stock market risk: A viewpoint of economic policy uncertainty

This study explores the effect of economic policy uncertainty (EPU) in four countries or regions (China, Japan, Europe, and the United States) on the contagion risk of investments in the global stock market. The stock returns of 22 stock markets worldwide are analyzed to determine which region’s EPU exhibits the greatest effect on regional systematic risk in the global stock market and on volatility risk in individual stock markets. First, all of the samples, the markets of different continents and the spillover indices of the developed and emerging markets, are calculated to observe the dynamic correlation among these markets with the aim of quantifying regional systematic risk and further examining the contagion risk effect of EPU. The results indicate the following: EPU in China is the most influential, and its contagion risk spreads to different regional markets, except for Europe; the effect of EPU in the United States is inferior to that in China; EPU in Japan merely influences contagion risk in emerging markets; contagion risk in European markets is not influenced by the four EPU indices; and EPU in Europe is not influenced by contagion risk in the global stock market. However, according to the volatility risk in each market, the EPU in Europe and China respectively influence Asian countries and European countries the most. These results may be attributable to the extremely high trade dependence among these countries because the performance of international enterprises is mainly determined by the economic policies of their trading partners.     

Is economic policy uncertainty important to forecast the realized volatility of crude oil futures?

In this research, we first investigate whether economic policy uncertainty (EPU) index can increase the HAR-RV-type models’ forecast accuracy. In addition, we explore how EPU index can be effectively used to gain larger economic values in the oil futures market. To this end, this research provides a new perspective on setting thresholds for EPU and examines whether these thresholds can help improve both the forecast accuracy and economic values. Empirical results suggest that the HAR-RV-type models including EPU can generate more accurate forecasts and economic values. The HAR-RV-type models including above-threshold EPU can further improve the forecast accuracy and yield higher economic values by setting specific thresholds for a range of horizons. The findings highlight the importance of EPU and effective way of using EPU in risk management and portfolio strategies that is crucial for investors and policymakers.     

Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models

This paper applies the threshold quantile autoregressive model to study stock return autocorrelations and predictability in the Chinese stock market from 2005 to 2014. The results show that the Shanghai A-share stock index has significant negative autocorrelations in the lower regime and has significant positive autocorrelations in the higher regime. It attributes that Chinese investors overreact and underreact in two different states. These results are similar when we employ individual stocks. Besides, we investigate stock return autocorrelations by different stock characteristics, including liquidity, volatility, market to book ratio and investor sentiment. The results show autocorrelations are significantly large in the middle and higher regimes of market to book ratio and volatility. Psychological biases can result into return autocorrelations by using investor sentiment proxy since autocorrelations are significantly larger in the middle and higher regime of investor sentiment. The empirical results show that predictability exists in the Chinese stock market.     

上证180指数的GARCH族模型仿真研究——对上证300指数的间接实证建模分析

本文旨在运用GARCH族模型对即将作为股指期货标的物——上证300指数进行间接实证建模研究。本文使用上证180指数研究上证300指数具有可行性。分析结果表明:上海股市股价波动确实存在显著的GARCH效应和冲击持久效应,并存在较弱的杠杆效应;收益率条件方差序列是平稳的,模型具有可预测性,GARCH-M(1,1)模型可以很好地拟合与预测上证180指数。该仿真模型可以较好地实现点对点的长期高精度预测,克服了传统预测模型只能进行短期预测的缺陷。这不仅对于投资者规避风险,开拓利润空间,而且对于我国资本市场的稳健发展,都具有重要的理论与实践指导意义。     

金融危机后中国股市波动性结构变化测度及其原因分析

以2005年4月至2010年4月我国沪深300指数为研究对象,使用调整后的EGARCH模型,对金融危机前后中国股市的波动性进行研究。结果显示:金融危机发生后中国股市的波动性明显减弱———这与美国股市明显不同,且波动性结构发生了显著性变化,表现为美国股市对中国股市的影响减弱、中国股市波动的持久性增强等。最后,对产生这些变化的原因进行了理论分析,指出金融危机发生后贸易保护主义抬头、刺激性的宏观经济政策出台是中国股市波动性结构变化的可能原因。     

The effects of economic policy uncertainty on China’s economy: evidence from time-varying parameter FAVAR

ABSTRACT

This article explores the effects of China’s economic policy uncertainty (EPU) on its fiscal policy, monetary policy and a wide range of macro-economic variables using a time-varying parameter FAVAR model. Based on monthly data from 07/2003 to 08/2017, the time-varying structure of the model allows us to capture the time-varying characteristics of the macro-economic variables and which channel is relevant. Empirical results reveal that the reaction of monetary and fiscal policies to EPU is highly asymmetric across macro-economic circumstances. Loose monetary and fiscal policies are adopted in response to EPU shocks during the financial crisis, while policies are moderately tightened after the crisis. The China Interbank Offered Rate (Chibor) responds more sensitively and severely than M2 to EPU shocks. Additionally, EPU shocks have a significant and negative impact on economic growth, consumption, exchange rates, bonds and the stock market, but showing a positive impact on credit, real estate and fixed asset investment (which might be due to China’s special economic market environment and the high investment return). The results indicate that EPU shocks significantly affect macroeconomic fundamentals through precautionary savings and financial market channels but lose their effectiveness through a ‘real options’ effect.     

Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect

This study investigates the impact of the recently introduced Shanghai-Hong Kong Stock Connect. Using high frequency data and dynamic forecasting techniques, we find that the new Stock Connect does contribute to the increasing importance of the Chinese mainland stock market and economic activity. A weak and unstable cointegration relationship is found after this event. Additionally, the Stock Connect has also increased the conditional variance of both stock markets. We observe a leading role of the Shanghai stock market to the Hong Kong stock market in terms of both mean and volatility spillover effects after the Stock Connect. Our study indicates that the opening up of stock markets in China could enhance the leading power, influence the risk level and improve the market efficiency of the Chinese mainland stock market, since the volatility spillover effect from Shanghai to Hong Kong is strengthened. Besides, our results have important policy implications, especially on how policy makers should deal with the increased market interconnectedness and for portfolio managers in choosing potential hedging instruments. The success of Shanghai-Hong Kong Stock Connect provides valuable operational experience for the forthcoming Shenzhen-Hong Kong Stock Connect which could further improve the market efficiency in China.     

Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market

Based on methods developed by Bollerslev et al. (2016), we explicitly accounted for the heteroskedasticity in the measurement errors and for the high volatility of Chinese stock prices; we proposed a new model, the LogHARQ model, as a way to appropriately forecast the realized volatility of the Chinese stock market. Out-of-sample findings suggest that the LogHARQ model performs better than existing logarithmic and linear forecast models, particularly when the realized quarticity is large. The better performance is also confirmed by the utility based economic value test through volatility timing.     

中国股票市场波动率的高频估计与特性分析

本文旨在应用高频数据估计中国股市的已实现波动率。我们发现股票指数与个股的高频交易数据中的微观摩擦影响正好相反 ,使用极高频的数据会大大增加个股的波动率估计值 ,相反却会大大降低指数的波动率估计值。在计算各种频率的已实现波动率的基础上 ,本文构造了一种较为精确的估计波动率的方法 ,可以更好地平衡测量误差与微观结构误差。基于已实现波动率 ,本文研究了中国股市波动率不对称性和长期记忆特性     

Oil shocks and stock volatility: new evidence via a Bayesian,graph-based VAR approach

ABSTRACT

This article examines the temporal dependence between three oil shocks and realized volatility in the stock markets of G20 countries between 1994 and 2019. By applying a novel, graphical, Bayesian VAR (BGVAR) model, we calculate unidirectional linkages of oil and stock volatility with a full and segmented sample. The results suggest an overall causality from stock volatility to oil shocks. For certain short, specific periods, the causal direction reverses. Depending on the country and the source of an oil shock, the magnitude and type of the effect can vary considerably. Specific oil-market shocks occur most often in our full sample. In a time-varying structure, oil supply shocks’ impact on stock volatility is more prominent, and net oil-importing countries’ responses to these shocks are greater than for oil-exporting countries. In addition, we find that relationship dynamics can capture market information, such as global economic growth during the 2008–2009 financial crisis.     

股权分置改革与股市波动结构——基于EEMD方法的实证研究

笔者利用系综经验模式分解方法(EEMD)考察了股改启动前、股改期间与股改基本完成后上证综指与深证成指的波动结构特征及其变化。实证结果表明:与股改基本完成前相比,股改后我国股市的波动结构发生显著变化,即短期波动成分成为解释股市总体波动的最主要因素。同时,中期波动成分的平均周期大幅延长。股改后限售股大规模且集中解禁与减持对股市的冲击强化了市场的短线投机行为,引发股市短期波动急剧增加。而人民币升值、次贷危机等导致中期波动更具持久性。     

Does international oil volatility have directional predictability for stock returns? Evidence from BRICS countries based on cross-quantilogram analysis

While numerous studies have investigated the relationship between oil volatility and stock returns, it is surprising that little research has examined the quantile dependence and directional predictability from oil volatility to stock returns in BRICS (Brazil, Russia, India, China, and South Africa) countries. We address this issue by using the cross-quantilogram model proposed by Han et al. (2016). The empirical results show that, overall, oil volatility has a directional predictability for the stock returns in BRICS countries. When the oil volatility is in a low quantile (lower than its 0.1 quantiles), it is less likely to show either a large loss or a large gain in the stock market. In contrast, there is an increased likelihood of either large loss or a large gain in the stock market when the oil volatility is in a high quantile (higher than its 0.9 quantiles). The directional predictability from the oil volatility to stock returns depends on the net position of oil imports and exports of these BRICS countries in the oil market. The net oil exporters (Russia and Brazil) are less likely to have large gains and large losses in the stock market than are the net oil importers (India, China, and South Africa) when the oil volatility is in a low quantile. The net oil exporters are more likely to have large gains and large losses than are the net oil importers when the oil volatility is in a high quantile. The results are robust to change in the variable of oil volatility and the sample interval.     

关于中国宏观经济变量与证券市场关联性的实证研究

检验股票市场与经济发展之间的关系是经济增长理论研究中的一个新课题,股票市场作为金融市场重要组成部分与经济增长、宏观经济变量之间的关系,更是当前研究的热点。文章将重点研究我国的宏观经济变量与股票市场之间是否存在关联性。文章选取了能够较为全面代表宏观经济运行情况的相关指标,并将这些宏观经济变量与代表中国股票市场运行的上证综合指数一起建立数据模型进行分析,探讨宏观经济变量与股票市场之间的相互关系,进而对中国股票市场的更好发展提出有效建议。     

后危机时代亚洲地区股票市场风险研究——基于非对称GARCH模型

运用非对称GARCH模型对后危机时代的日本、中国、印度和韩国的股票指数收益率波动性及亚洲各国股票市场的风险进行比较可发现:亚洲地区股票指数收益率的波动呈现出聚集性和持续性,股票市场存在着冲击的非对称性;后危机时代,日本和韩国股市收益与风险不相匹配,反映出发达国家股票市场的波动性显著大于发展中国家,同时,中国股票市场的抗风险能力正在逐步加强,股票市场的信息冲击也趋于平缓。     

中美股市杠杆效应与波动溢出效应——基于GARCH模型的实证分析

本文基于极大似然函数值准则和赤池信息准则,从众多非对称GARCH模型中选择最优模型来研究中美股市杠杆效应和波动溢出效应。结果表明:沪市和深市都表现出显著的杠杆效应,与美国股市相比沪市和深市杠杆效应较弱;沪市和深市之间存在显著的双向波动溢出效应,且沪市对深市的波动溢出效应更显著;美国股市与中国股市之间不存在显著的波动溢出效应。     

股指期货限制交易对定价效率影响研究*——基于跨市场信息传递视角的实证

从跨国金融市场信息传递的视角对中国2015年股灾中股指期货限制交易政策实施前后的中美市场实证分析表明：股指期货的限制交易政策极大地增强了美国市场对中国市场的影响，尤其是在下跌行情中的影响更大。分位数回归显示美国市场的交易活动对中国市场开盘价的影响呈“V”型特征，美国市场的微小波动都会引起中国市场的巨大波动，限制交易措施实施后，在下跌行情中来自美国市场的负冲击对中国市场的影响变得更大。这一实证研究的政策含义在于：为了增强股指期货市场的定价效率，金融监管层在市场稳定后应放开股指期货的限制交易，并通过降低准入门槛和合约大小等措施提高市场的开放程度。此外，监管层和国内投资者不能忽视美国股指期货对国内市场的影响。     

The Behaviour of Banking Stocks During the Financial Crisis and Recessions. Evidence from Changes‐in‐Changes Panel Data Estimations

This paper examines the impact of the financial crisis and economic recessions on bank shares compared to the overall stock market index for 18 OECD countries from 1993 to 2015. The empirical methodology utilizes the changes‐in‐changes approach. We compare and contrast the returns of the banking stock price index (treatment group) in each country with their general stock price index (control group), which experiences smaller changes. Our results suggest that bank returns on average perform significantly worse than that of the general stock price index during recessions. In addition, we also find significantly greater volatility in bank share returns.     

Spillovers of volatility index: evidence from U.S., European,and Asian stock markets

We investigated the cross-market relations of volatility indexes with U.S. and non-U.S. stock market returns. We found that the pervasive VIX influence at both U.S. and non-U.S. stock markets. The VSTOXX and VKOSPI capture the major shocks to the global economy and show movements similar to the VIX. The empirical findings indicate that volatility index changes are important in explaining stock returns. We also examined spillover effects across volatility indexes. The VIX is a main transmitter, and the VKOSPI the main receiver, of these spillovers. The results point to a leading role for the VIX in the international market.     

Investor sentiment,variance risk premium and delta-hedged gains

Delta-hedged gains are supposed to be negative and represent a volatility risk premium. Using a sample of Standard & Poor 500 index options from 2006 to 2009, this study documents two anomalies that cannot be explained by the volatility risk premium. First, delta-hedged gains are more negative for out-of-money options than for at-the-money options. Second, delta-hedged gains are significantly positive during financial crisis period. We propose a behavioural explanation in which both option prices and stock prices are affected by investor’s sentiment, but pessimistic sentiment has a greater impact on stock market than option market. This asymmetric response to pessimistic mood in turn affects the relative expensiveness of option prices.