外汇期权信息含量与在岸离岸市场效率

央行在“8·11”汇改后放松了汇率中间价的管理,采用更为市场化的方式形成中间价,这种变化对于人民币汇率衍生品市场的影响尚属未知。为此,本文从人民币期权组合的Black-Scholes隐含波动率历史报价数据中提取出在岸、离岸市场人民币期权的无模型隐含波动率和风险中性偏度,在将样本划分为汇改前后三个不同的阶段的基础上,检验了期权隐含指标对未来汇率分布的预测能力。实证结果表明,在“8·11”汇改之后,随着人民币中间价形成机制变得更加市场化,期权价格中包含了越来越多关于未来汇率分布的信息,在岸和离岸期权市场的信息效率都有显著提高,意味着人民币中间价形成机制的市场化能显著提升我国金融市场效率。因此,在兼顾金融安全的角度上,稳步促进人民币中间价形成机制市场化进程将有利于我国金融市场效率的提高。     

基于多元随机波动模型方法的股指期货与现货关系研究——以亚洲五地金融市场为例

本文以多元随机波动模型检视亚洲五个主要金融市场股指期货与现货的报酬关系与波动溢出效应。实证发现,五地金融市场股指期货与现货之间皆存在双向的波动溢出效应。股指现货动态相关系数和波动持续系数均高,显示现货市场具有聚类的现象。此外,本研究进一步探讨股指期货与现货的联动和共同波动因子的关系,实证发现,股指期货与现货的波动关系是同时受到共同信息发布的影响。     

“好”的不确定性、“坏”的不确定性与股票市场定价——基于中国股市高频数据分析

不确定性并不是都是“坏”的,“好”的不确定性也同样存在。本文采用Barndorff-Nielsen et al.(2010)提出的已实现半方差作为股票市场“好”的不确定性和“坏”的不确定性的代理指标,并在此基础上构建了相对符号变差(RSV),分析RSV对中国股市定价的影响。基于2007-2017年中国A股5分钟高频数据的实证研究发现:(1)与理论解释相一致,RSV与股票收益之间呈现负相关关系。无论是基于单变量分组、双变量分组还是公司层面的截面回归,这种影响在经济上和统计上都显著。(2)RSV是独立于已实现偏度的一个重要定价因子,且RSV对股票的定价能力强于已实现偏度的定价能力。(3)RSV对中国股市的影响是状态依存的,相对于经济景气程度高的状态,在经济景气程度低的状态下RSV定价影响更大。(4)基于RSV构建的投资组合的表现明显优于市场超额收益率组合、SMB组合和HML组合的表现。     

Intertemporal risk-return trade-off in foreign exchange rates

We investigate the intertemporal risk-return trade-off of foreign exchange (FX) rates for ten currencies quoted against the USD. For each currency, we use three risk measures simultaneously that pertain to that currency; its realized volatility, its realized skewness, and its value-at-risk. We apply monthly FX excess returns and risk measures calculated from daily observations. We find that there is a significant contemporaneous risk-return trade-off for the currencies under investigation. There is no evidence of noncontemporaneous risk-return trade-off. We pay special attention to the risk-return trade-off during the recent financial crisis.     

基于贝叶斯MSSV-ST金融波动模型的股市特征及机制转移性研究

针对有偏厚尾金融随机波动模型难以刻画参数的动态时变性及结构突变的问题,设置偏态参数服从 Markov 转换过程,采用贝叶斯方法,构建带机制转移的有偏厚尾金融随机波动模型,考量股市不同波动状态间的机制转移性,捕捉股市间多重波动特性。通过设置先验分布,实现模型的贝叶斯推断,设计相应的马尔科夫链蒙特卡洛算法进行估计,并利用上证指数进行实证。结果表明：模型不仅刻画了股市的尖峰厚尾、杠杆效应等特性,发现收益率条件分布的偏度参数具有动态时变性,股市波动呈现出显著的机制转移特性,而且证实了若模型考虑波动的不同阶段性状态后,将降低持续性参数向上偏倚幅度的结论。     

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.     

Is volatility clustering of asset returns asymmetric?

Volatility clustering is a well-known stylized feature of financial asset returns. This paper investigates asymmetric pattern in volatility clustering by employing a univariate copula approach of Chen and Fan (2006). Using daily realized kernel volatilities constructed from high frequency data from stock and foreign exchange markets, we find evidence that volatility clustering is highly nonlinear and strongly asymmetric in that clusters of high volatility occur more often than clusters of low volatility. To the best of our knowledge, this paper is the first one to address and uncover this phenomenon. In particular, the asymmetry in volatility clustering is found to be more pronounced in the stock markets than in the foreign exchange markets. Further, the volatility clusters are shown to remain persistent for over a month and asymmetric across different time periods. Our findings have important implications for risk management. A simulation study indicates that models which accommodate asymmetric volatility clustering can significantly improve the out-of-sample forecasts of Value-at-Risk.     

Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility

This paper develops a two-step estimation methodology that allows us to apply catastrophe theory to stock market returns with time-varying volatility and to model stock market crashes. In the first step, we utilize high-frequency data to estimate daily realized volatility from returns. Then, we use stochastic cusp catastrophe theory on data normalized by the estimated volatility in the second step to study possible discontinuities in the markets. We support our methodology through simulations in which we discuss the importance of stochastic noise and volatility in a deterministic cusp catastrophe model. The methodology is empirically tested on nearly 27 years of US stock market returns covering several important recessions and crisis periods. While we find that the stock markets showed signs of bifurcation in the first half of the period, catastrophe theory was not able to confirm this behaviour in the second half. Translating the results, we find that the US stock market’s downturns were more likely to be driven by the endogenous market forces during the first half of the studied period, while during the second half of the period, exogenous forces seem to be driving the market’s instability. The results suggest that the proposed methodology provides an important shift in the application of catastrophe theory to stock markets.     

Spreading the fear: The central role of CBOE VIX in global stock market uncertainty

Construction of efficient portfolios is reliant on understanding the correlation between assets. If correlations change markedly during times of economic turmoil then investors are exposed to greater risk at the most inopportune time. We examine the linkages between global stock markets using measures of market uncertainty (implied volatility). Using a sample of daily changes in G7 and BRIC implied volatility measures, over a 20-year sample period, we demonstrate that uncertainty in U.S. markets plays a pivotal role in global stock market uncertainty. “Fear is spread” across markets, as heightened uncertainty in U.S. markets is transmitted across global markets. Conversely, changes in global market uncertainty do not explain changes in U.S. market uncertainty. While there is a clear increase in connectedness during crisis periods, we observe a disparity in the way that inter-dependencies change during the two major economic crises in our sample period; the GFC (2007–2009) and COVID-pandemic (2020). The additional importance of US news largely drives our results during the GFC, while the effect is spread among several countries (particularly within European markets) during COVID.     

Volatility transmission patterns and terrorist attacks

The objective of this study is to analyse volatility transmission between the US and Eurozone stock markets considering the financial market responses to the September 11, March 11 and July 7 terrorist attacks. In order to do this, we use a multivariate GARCH model and take into account the asymmetric volatility phenomenon, the non-synchronous trading problem and the turmoil periods themselves. Moreover, a graphical analysis of the Asymmetric Volatility Impulse-Response Functions (AVIRF) is introduced, which takes into consideration the financial market responses to the terrorist attacks. Results suggest that there is bidirectional and asymmetric volatility transmission and show the different impacts that terrorist attacks had on both markets.     

市场摩擦对特质风险溢价的影响效应——基于A股主板市场的实证分析

与国外发达市场相比,我国A股主板市场的市场摩擦因素对市场微观结构和资产定价的影响更大。在防范和化解系统性风险的过程中,进一步分析市场摩擦如何作用于特质风险定价效应的问题具有重要的理论和现实意义。本文通过采用多维市场摩擦指标来代理信息不对称、交易成本、买卖限制、卖空限制、风险对冲和外部冲击,检验中国股市特质风险和预期收益率的关系,并判断出市场摩擦因素间的差异性影响机制。回归发现,市场摩擦和特质风险因子(特质波动率和特质偏度)都具有定价效应。各维度市场摩擦因素降低了股票流动性,进而增强了特质波动率的负向定价效应,部分解释了“特质波动率之谜”,但市场摩擦对特质偏度因子溢价的影响较为微弱。同时,基于特质波动率和特质偏度因子的投资策略能够产生超越CAPM、三因子和五因子模型的绝对收益,并印证了市场摩擦对特质风险因子绝对收益的影响作用。     

Volatility dependences of stock markets with structural breaks

We develop a Vector Heterogeneous Autoregression model with Continuous Volatility and Jumps (VHARCJ) where residuals follow a flexible dynamic heterogeneous covariance structure. We employ the Bayesian data augmentation approach to match the realised volatility series based on high-frequency data from six stock markets. The structural breaks in the covariance are captured by an exogenous stochastic component that follows a three-state Markov regime-switching process. We find that the stock markets have higher volatility dependence during turmoil periods and that breakdowns in volatility dependence can be attributed to the increase in market volatilities. We also find positive correlations between the Asian stock markets, the European stock market, and the UK stock market. The US stock market has positive correlations with all other markets for most of the sample periods, indicating the leading position of US stock market in the global stock markets. In addition, the proposed three-state VHARCJ model with Dynamic Conditional Correlation (DCC) and break structure under student-t distribution has a superior density forecast performance as compared to the competing models. The forecast models with structural breaks outperform those without structural breaks based on the log predicted likelihood, the log Bayesian factor, and the root mean square loss function.     

Linkages between Indian and US financial markets: impact of global financial crisis and Eurozone debt crisis

This paper examines inter-linkages between Indian and US equity, foreign exchange and money markets using the vector autoregressive-multivariate GARCH-BEKK framework. We investigate the impact of global financial crisis (GFC) and Eurozone debt crisis (EZDC) on the conditional volatility and conditional correlation estimates derived from the multivariate GARCH model for Indian and US financial markets. Our results indicate that there is significant bidirectional causality-in-mean between the Indian stock market returns and the Rs./USD market returns, and significant unidirectional causality-in-mean from the US stock market returns to the Indian stock market returns. As regards volatility spillovers, we find that volatility in the Indian stock market rises in response to domestic as well as US financial market shocks but Indian financial market shocks do not impact the US markets. Further, impact of the recent crisis episodes on the covariance matrix is found to be significant. We find that volatility in the Indian and US financial markets significantly amplified during GFC. The conditional correlations across asset markets were significantly accentuated in the wake of the two crisis episodes. The impact of GFC on cross-market conditional correlations is higher for majority of the asset market pairs in comparison to the EZDC.     

Return and volatility spillovers between currency and bond markets in India

This paper examines the return and volatility spillovers between the foreign exchange and bond markets of India using a bivariate asymmetric BEKK-GARCH (1,1) model for the period 4 April 2005 to 31 March 2017. We find the evidence of bidirectional return and volatility spillovers with asymmetric effects between these two markets. The spillovers are evidenced even during the periods when foreign portfolio investments in the Indian bond markets were relatively low suggests the existence of strong inter-linkages between both the markets.     

Equilibrium moment restrictions on asset returns: normal and crisis periods

Empirically, the covariance between stock returns varies with their volatility. We seek a robust theoretical explanation of this. With minimal assumptions, we model stochastic properties of equilibrium returns which result from the interaction between inter-temporal traders and noisy, price-sensitive short-term traders. The inter-temporal traders can have arbitrary investment rules, preferences and information. In all cases we find a set of restrictions between second moments of equilibrium returns. With two assets there is also a bound on the correlation between asset returns. Estimation with second moments of global stock returns supports our theoretical framework. Higher volatility in at least one market can increase comovement among markets. With globalization, covariances between two stock markets can also affect covariances between two other stock markets. We also find that the changes in trader behavior between normal and crisis periods lead to changes in the moment restrictions between asset returns.     

Volatility spillovers between oil prices and stock sector returns: Implications for portfolio management

In this article we take a recent generalized VAR-GARCH approach to examine the extent of volatility transmission between oil and stock markets in Europe and the United States at the sector-level. The empirical model is advantageous in that it typically allows simultaneous shock transmission in the conditional returns and volatilities. Insofar as volatility transmission across oil and stock sector markets is a crucial element for portfolio designs and risk management, we also analyze the optimal weights and hedge ratios for oil-stock portfolio holdings with respect to the results. Our findings point to the existence of significant volatility spillover between oil and sector stock returns. However, the spillover is usually unidirectional from oil markets to stock markets in Europe, but bidirectional in the United States. Our back-testing procedures, finally, suggest that taking the cross-market volatility spillovers estimated from the VAR-GARCH models often leads to diversification benefits and hedging effectiveness better than those of commonly used multivariate volatility models such as the CCC-GARCH of Bollerslev (1990), the diagonal BEKK-GARCH of Engle and Kroner (1995) and the DCC-GARCH of Engle (2002).     

Taming polysemous signals: The role of marketing intensity on the relationship between financial leverage and firm performance

This study traces the degree of integration and volatility spillover effect between the Pakistani and leading foreign stock markets by analyzing the Meteor shower hypothesis. Daily data are used from nine worldly equity markets (KSE 100, NIKKEI 225, HIS, S&P 500, NASDAQ 100, DOW JONES, GADXI, FTSE 350 and DFMGI) for the period of 2005 to 2014. First, we used the whole data set and after that we split data set into two subsets, First subset of data contains the era of global financial crisis of 2008 from 2005 to 2009 and Second subset is after global financial crisis time period from 2010 to 2014 (The global crisis prevailed till end of 2009). By following the Hamao et al. (1990) technique the univariate GARCH type models are employed to explore the dynamic linkages between Pakistani and leading foreign stock markets. The results from whole data set illustrate that there is mixed co‐movements between leading foreign stock markets and Pakistani stock market. The results from both subsets provide an evidence that there is a unidirectional mean and volatility spillover effect from S&P 500, NASDAQ 100, DJI and DFMGI to KSE 100. Also we found bidirectional spillover effect between DFMGI and KSE 100 from both subsets of data. We concluded that there is only one indirect linkage through which may the information transmitted to KSE 100. This linkage is developed due to the co‐movement among KSE 100, DFMGI and NASDAQ 100 in crisis period. This integration between these markets may provide a sign of indirect linkage. It also exhibits the volatility in Pakistan stock market returns is instigated through direct effects as well as indirect effects. Our study brings important conclusions for financial institutions, portfolio managers, market players and academician to diagnose the nature and level of linkages between the financial markets.     

Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models

This paper examines the dynamic relationship between the oil market and stock markets from two perspectives: dependence between the crude oil market (WTI) and stock markets of the US and China, and volatility spillovers between them during 1991–2016. We further analyze structural breaks of market dependences and consider the extent of their influence on such relationships. Our vine-copula results show that the dependences between the three paired markets, WTI-US, WTI-China and US-China, vary dynamically across the six identified structural break periods. In particular, the dependence between WTI-US is stronger and more volatile than that between WTI-China during most of the periods. The dependence between US-China remains at a lower level in the earlier periods, but increases in the final period. Our VAR-BEKK-GARCH results demonstrate distinctive volatility spillovers across these periods, with varying directionality, in response to the structural changes. Overall, our results indicate that the oil market stimulates rapid and continual fluctuations in market dependences, which become manifest most acutely in the aftermath of the Financial Crisis of 2007–08, demonstrating the increasing interdependence between the oil and stock markets. Further, the growing influence of China on the dynamics of these relationships, in the period following the Great Recession, presents evidence that it begins to assume an increasingly important role in global economic recovery.     

Price and volatility spillovers between exchange rates and stock indexes for the pre- and post-euro period

In this paper we explore the nature of the mean, volatility and causality transmission mechanism between stock and foreign exchange markets for the United States and some major European markets for the periods pre- and post-euro. The asymmetric volatility transmission is described by an extended Multivariate Exponential Generalized Autoregressive Conditionally Heteroskedastic (EGARCH) model. The results support the asymmetric and long-range persistence volatility spillover effect and show strong evidence of causality in the mean and variance between foreign exchange rate and stock price for both pre- and post-euro periods. However, the stock price has a more significant effect on foreign exchange rate for the two subsamples. These results are robust to the cross-correlation function test suggested by Cheung and Ng. The implication is particularly important for international portfolio managers when devising hedging and diversification strategies for their portfolios.     

Do Sovereign Re‐Ratings Destabilize Equity Markets during Financial Crises? New Evidence from Higher Return Moments

This study investigates the effects of S&P's sovereign re‐ratings on the higher moments of equity market returns over recent financial crises. Using a set of intraday stock market index prices and sovereign credit ratings for a sample of 36 countries that experienced sovereign rating changes over the period from 1996 to 2013, we find that the higher moments of stock market returns are significantly more responsive to sovereign re‐ratings during financial crises, but the effects on stock markets are not the same across different financial crises. The effects during crises are, however, magnified for large downgrades and those that are associated with a loss of investment grade status. We find that there are asymmetric effects during financial crises in that downgrades are consistently more significant than upgrades in increasing realized volatility and realized kurtosis. Both upgrades and downgrades affect realized skewness in times of crises in the expected direction.