中国沪深股市收益率和波动性的实证分析

沪市和深市股票收益率和波动性之闻具有相互作用和相互影响,存在股价变化和走势之间的互动作用和示范效应,我们发现两市收益率序列之间具有长期协整关系,这说明它们存在类似的长期趋势成分;它们的短期误差修正系数存在一定的差异,这说明它们具有相异的短期波动模式;我们利用 GARCH 模型等非对称性方法发现两市之间存在显著的波动"溢出效应"和"杠杆效应",这说明两市资金的流动性约束较低,投资主体的相关性较强,两市收益率和波动性之间具有一定程度的整合性。     

Does the currency board matter? US news and Argentine financial market reaction

Using a Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, we study the effects of the US monetary policy and macroeconomic announcements on Argentine money, stock and foreign exchange markets over the period January 1998 to July 2007. We show, first, that both types of news have a significant impact on all markets. Second, there are noticeable differences in reaction for different subsamples: Argentine money markets were more dependent on US news under the currency board than after it was abandoned as the floating exchange rate partly absorbs spillover effects from the US. Finally, we find that the US-dollar-denominated assets react less to US news than peso-denominated assets, which suggests that the currency board was not completely credible during its final years.     

Asymmetric spillover effects between the Shanghai and Hong Kong stock markets: evidence from quantile lagged regression

This article surveys the asymmetric spillover effects between the mainland China-based Shanghai Composite Index (SCI) and the Hong Kong based Hang Seng Index (HSI) using a quantile lagged regression model. Compared to previous studies, this article, based on data before and after the 2008 global financial crisis, presents a more detailed analysis, as we investigate the spillovers in terms of returns, volatilities and exchange rates between the renminbi (RMB) and the Hong Kong dollar (HKD) throughout the entire conditional return distribution, including the central quantiles, which are closely related to the normal circumstances, and the extreme quantiles, which correspond to the bear and bull markets. First, we find that the return spillovers from its lagged returns or from the other index not only vary across time but also depend on stock state. Second, while return volatility may boost the stock market in a bull market, it accelerates the decline in a bear market. Third, the depreciation of the RMB relative to the HKD does not significantly affect current returns for the HSI, while it negatively affects current returns for the SCI in a bad state after the crisis. The findings presented in this article will facilitate investors’ understanding of the two stock markets.     

Examining the relationship between stock return volatility and trading volume: new evidence from an emerging economy

Using daily stock return data for individual stocks from an emerging economy, this article examines the relationship between return volatility and trading volume under the theoretical postulate of the mixture of distributions hypothesis. The results suggest that the contemporaneous trading volume as a proxy for latent information arrival to the market did not contribute to the removal of significant ARCH or Generalized Autoregressive Conditional Heteroscedasticity effects that are found in stocks at the first stage of the investigation. The same holds for the lagged volume except for one case. This, perhaps, suggests that the trading volume (contemporaneous or lagged) is not adequately conveying information to induce traders’ views of the desirability of trade and, therefore, points to the need for searching for other micro and macro variables to be used as potential proxy for information arrival to the stock market of the emerging economy.     

Trading asymmetric trend and volatility by leverage trend GARCH in Taiwan stock index

This article develops a leverage trend Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model by incorporating asymmetric trend of returns of the exponential autoregressive and asymmetric volatility of GARCH models to study the asymmetric effects. Using in-sample daily data of Taiex over the period 4 January 1980 to 25 August 1997 and postsample daily data over the period 26 August 1997 to 10 September 2007, the evidence reveals that a curvaceous risk–return relationship and both asymmetric volatility and asymmetric trend of returns are significant in Taiex. The episode of asymmetric trend of returns is that the positive information creates a higher return trend than the negative information of the same amount, while similarly to most studies, the evidence of asymmetric volatility appears that the negative information makes a higher volatility than the positive information of the same size. Most remarkably, we evidence that the volatility asymmetry effect is a conservative trading factor and the return trend asymmetry effect is an active trading factor. In comparison of post-sample performance using rolling-window technique, the leverage trend GARCH model indeed outperforms the other three models with single asymmetry adjusted or without asymmetry adjusted, while the asymmetry nonadjusted model performs the worst. It implies that the return trend asymmetry (active trading) and the volatility asymmetry effects (conservative trading) tend to compensate, but not offset each other.     

FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSION

This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997–98 and 2008–09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992–June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time‐varying co‐volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only.     

How are Africa's emerging stock markets related to advanced markets? Evidence from copulas

The finance literature provides ample evidence that diversification benefits hinges on dependence between assets returns. A notable feature of the recent financial crisis is the extent to which assets that had hitherto moved mostly independently suddenly moved together resulting in joint losses in most advanced markets. This provides grounds to uncover the relative potential of African markets to provide diversification benefits by means of their correlation with advanced markets. Therefore, we examine the dependence structure between advanced and emerging African stock markets using copulas. Several findings are documented. First, dependence is time-varying and weak for most African markets, except South Africa. Second, we find evidence of asymmetric dependence, suggesting that stock return comovement varies in bearish and bullish markets. Third, extreme downward stock price movements in the advanced markets do not have significant spillover effects on Africa’s emerging stock markets. Our results, implying that African markets, with the exception of South Africa, are immune to risk spillover from advanced markets, improves the extant literature and have implications for portfolio diversification and risk management.     

Inflation volatility and stock prices: Evidence from ARCH effects

This paper examines the impact of inflation uncertainty on stock prices in developed as well as in emerging capital markets over the period 1980:1–93:12 via an Autoregressive Conditional Heteroskedasticity (ARCH) model for inflation. The results seem to support the presence of a negative association between inflation uncertainty and stock prices.The authors would like to thank, without implicating, Gikas Hardouvelis, Costas Karfakis, and especially the discussant of the conference session held in Williasmsburg, Robert C. Winder, for helpful comments and suggestions.     

The linkages,persistence, asymmetry in the volatility,the price discovery and efficiency,and the effect of the US subprime mortgage financial crisis on the spot and the futures market’s returns: the case of India

This article examines the effects of persistence, asymmetry and the US subprime mortgage crisis on the volatility of the returns and also the price discovery, efficiency and the linkages and causality between the spot and futures volatility by using various classes of the ARCH and GARCH models, and through the Granger’s causality. We have used two indices: one for spot and the other for futures, for the daily data from 12 June 2000 to 30 September 2013 from Nifty stock indices. We have then tested for ARCH effects, and subsequently employed various models of the ARCH and GARCH conditional volatility. The GARCH(1,1) model is found to be significant, and it implies that the returns are not autocorrelated and have ‘short memory’. It supports the hypothesis of the efficiency of the markets. The negative ‘news’ has more significant effect on volatility, corroborating the ‘leverage impact’ in finance on market volatility. We have also tested the volatility spillover effects. The two methods we employed support the spillover effects and the causality is bidirectional. We also have used the dummy variable for the US subprime mortgage financial crisis and found that they are statistically significant. Indian stock market is thus integrated to the world stock markets.     

Time-varying correlations in oil,gas and CO2 prices: an application using BEKK,CCC and DCC-MGARCH models

Previous literature has identified oil and gas prices as being the main drivers of CO₂ prices in a univariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) econometric framework (Alberola et al., 2008; Oberndorfer, 2009). By contrast, we argue in this article that the interrelationships between energy and emissions markets shall be modelled in a Vector Autoregressive (VAR) and Multivariate GARCH (MGARCH) framework, so as to reflect the dynamics of the correlations between the oil, gas and CO₂ variables overtime. Using the Baba–Engle–Kraft–Kroner (BEKK), Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation MGARCH (DCC-MGARCH) models on daily data from April 2005 to December 2008, we highlight significant own-volatility, cross-volatility spillovers, and own persistent volatility effects for nearly all markets, indicating the presence of strong Autoregressive Conditional Heteroscedasticity (ARCH) and GARCH effects. Besides, we provide strong empirical evidence of time-varying correlations in the range of [?0.3;?0.3] between oil and gas, [?0.05;?0.05] between oil and CO₂, and [?0.2;?0.2] between gas and CO₂, that have not been considered by previous studies. These findings are of interest for traders and utilities in the energy sector, but also for a broader applied economics audience.     

Do sovereign rating announcements affect emerging market exchange rate correlations? A multivariate DCC-GARCH approach

This article investigates the effects of sovereign credit rating announcements on time-varying exchange rate return correlations for a sample of 11 emerging market countries over the period 2002–2015. The data set covers daily exchange rates and long-term foreign currency sovereign ratings, outlooks and watch list. The pairwise time-varying correlations are derived by corrected Dynamic Conditional Correlation (cDCC) modelling which is a member of multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models family. Furthermore, to capture the global factor effect, a dynamic-weighted index is created by using dynamic principal component (DPC) analysis. Findings suggest that some of the emerging market exchange rate co-movements are affected by rating announcements. Upgrades of Moody’s and downgrades of Fitch lead to spillovers. Main source of these spillovers are sovereign credit rating changes of European countries, especially Czech Republic and Turkey. Countries with high amount of external debt, large current account deficit and speculative grade are more prone to be influenced by announcements on a foreign country’s long-term sovereign rating.     

Spillover effects of the 2008 financial crisis on NIE stock markets

This article estimates dynamic conditional correlations of stock returns across countries by using DCC–GARCH model and analyse spillover effects of the 2008 financial crisis on the NIE’s stock markets. The results show that there is no regime shift in mean equation of the correlation coefficient during the financial crisis. It may imply there are no mean spillover effects of the US financial crisis on the NIE’s stock markets. However, there are volatility spillover effects of the financial crisis sparked in 2008 from the US to the NIE’s markets.     

期货价格收益率与波动性的实证研究——以中国上海与英国伦敦为例

采用协整模型、Granger因果关系检验、ECM模型及几种GARCH模型对中国上海与英国伦敦金属期货价格收益率和波动性做了研究.发现两市期货价格之间存在Granger因果关系、协整关系、同向变动关系和长期的共同趋势.采用ECM模型研究了两市的短期波动差异.GARCH类模型研究发现,两市波动性存在非对称性、溢出效应、杠杆效应.上海对伦敦市场的单向溢出效应显著存在.两市存在的利空消息均大于利多消息的作用,伦敦期货市场风险大于上海期货市场风险.     

Nonlinearities in emerging stock markets: evidence from Europe's two largest emerging markets

Recent developments in time series analysis allow proper modelling of nonlinearities in economic and financial variables. A growing body of research was dedicated to investigation of potential nonlinearities in conditional mean of many economic and financial variables, mainly concentrating in developed economies. However, nonlinearities in financial variables in developing economies have not been fully examined yet. In this article we investigate potential nonlinearity and cyclical behaviour of stock returns in Europe's two largest emerging stock markets, mainly in the Greek and Turkish stock markets. Specifically, we use STAR family models, which allow to model nonlinearities in the conditional mean, for modelling monthly returns on stock exchange indices of the Athens Stock Exchange and Istanbul Stock Exchange. Although we find no nonlinearity in conditional variance, we do find strong evidence in favour of nonlinear adjustment of stock returns. It is found that allowing for nonlinearity in conditional mean results in a superior model and provides good out-of-sample forecasts, which contradicts to efficient market hypothesis.     

Nonlinear dynamics: Evidence for a small stock exchange

This paper models the main stock index of the Vienna Stock Exchange with daily data from 1986 to 1992. We find that returns are nonnormal and show linear and nonliner dependence. On that basis we compare the fit of alternative specifications of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) to the Markov-Switching approach. The models are evaluated with diagnostic tests on the standardized residuals. We consider evidence for deterministic structures and for infinite variance. Our main result is that a parsimonious model from the GARCH – class can generate the statistical properties of daily returns. The behavior of the two types of models with respect to temporal aggregation is found to differ significantly. First version received: January 1996/Final version received: December 1997     

Foreign News and Spillovers in Emerging European Stock Markets

We analyze foreign news and spillovers in the emerging EU stock markets (the Czech Republic, Hungary, and Poland). We employ high‐frequency five‐minute intraday data on stock market index returns and four classes of EU and US macroeconomic announcements during 2004–07. We account for the difference of each announcement from its market expectation and we jointly model the volatility of the returns accounting for intraday movements and day‐of‐the‐week effects. Our findings show that intraday interactions on the new EU markets are strongly determined by mature stock markets as well as the macroeconomic news originating thereby. We show that strong contemporaneous links across markets are present even after controlling for macroeconomic announcements. Finally, in terms of specific announcements, we are able to show the exact sources of macro news spillovers from the developed foreign markets to the three new EU markets under research.     

DYNAMIC STOCK RETURN–VOLUME RELATION: EVIDENCE FROM EMERGING ASIAN MARKETS

This paper empirically examines the dynamic stock return–volume relations for six emerging Asian markets: Indonesia, Malaysia, Singapore, South Korea, Taiwan, and Thailand. Evidence is found that trading volume Granger causes stock return in quantiles and the causal effects of volume are heterogeneous across quantiles. This shows that volume carries some information to the return and could be interpreted in light of theoretical models. In addition, we find that there is bi‐directional causality between stock return and trading volume in most of the markets. The finding indicates that those Asian emerging markets with different institutions and information flows than more mature markets have present similar causal effects on the stock return–volume relation. Furthermore, the cross‐country evidence shows that the US market helps to predict the returns of the emerging Asian markets.     

The impact of 11/13 Paris terrorist attacks on stock prices: evidence from the international defence industry

This study explores the effect of the Paris terrorist attacks on the stock returns and the volatility for the most important companies in the global defence industry. To this end, it employs the General Autoregressive Conditional Heteroscedasticity methodology. The findings clearly indicate that this terrorist event has a positive impact on both the returns and the volatility of these stocks.     

非同步交易下股指期货与股票市场开收盘收益率间引导关系的实证研究

运用Granger因果检验、脉冲响应函数分析和方差分解,基于819组5分钟高频数据,对沪深300股指期货及其股票指数的开盘价格、收盘价格之间的引导关系进行检验。结果表明:期货市场与股票市场的开盘收益率相互引导;期货市场收盘收益率引导现货市场的收盘收益率和第二天开盘收益率;期货市场受自身和现货市场新息的冲击;现货市场受自身新息的冲击较大;期货市场对现货市场新息的变动更敏感;期货与现货的开盘收益率变化的总方差主要来自于现货市场,期货与现货的收盘收益率变化的总方差主要来自于期货市场。     

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。