Return and Volatility Spillovers and Cojump Behavior Between the U.S. and Korean Stock Markets

ABSTRACT

In this study, we examine return spillover, volatility transmission, and cojump behavior between the U.S. and Korean stock markets. In particular, we focus on cojump behavior between the two markets in order to explain the transmission of unexpected shocks. We find that the U.S. stock market causes return spillover effects in the Korean stock market, and there is significant volatility transmission between the two markets. Importantly, we find a stronger association in size, as compared with intensity, of cojumps between the U.S. and Korean stock markets, particularly during the recent financial crisis.     

Risk contagion among international stock markets

We develop a stochastic volatility model with jumps in returns and volatility to analyze the risk spillover from the U.S. market and the regional market to a number of European countries’ equity markets. The key advantage of this approach compared to the earlier approaches is that it enables us to identify jumps and investigate spillover of extreme events across borders. We find that a large part of the jumps in the local markets are due to the U.S. market and the regional market. The U.S. contribution to the variances is in general below the contribution from the regional market. In general, we observe an increasing integration during the last two decades, which, to some extent, can be related to the advancement of the European Union. Furthermore, we show that the identification of the jumps can be used as a useful signal for portfolio reallocation.     

SDR货币篮子中人民币的国际化定位——汇率市场波动传染与波动聚类的实时甄别

随着人民币国际化进程的逐步推进,SDR货币篮子中人民币的国际化定位引人瞩目。本文基于非线性MSBIARCH模型,实时甄别人民币市场与美元市场、英镑市场、日元市场、欧元市场之间的波动传染关系,以及波动传染作用下汇率市场的波动聚类态势,进而识别SDR货币篮子中人民币的国际化定位,旨在为及时防范并规避人民币市场的波动风险提供参考。研究发现,汇率市场经由“经济基本面”“市场情绪”以及“市场预期”对外发挥波动传染作用,人民币市场与美元市场之间存在双向波动传染关系,与英镑市场、欧元市场以及日元市场之间存在单向波动传染关系。不同汇率市场之间的波动传染关系表现出时间区制转移特征,汇率市场的波动聚类态势也呈现时变特征。汇率市场发挥波动传染作用的时间与汇率市场呈现波动聚类态势的时间相匹配,均集中在极端经济事件期、不规则事件期以及政策颁布事件期。国际汇率市场的波动传染作用导致了人民币市场的波动聚类态势,而人民币市场的波动传染作用仅强化了国际汇率市场的波动聚类态势,SDR货币篮子中人民币的国际化程度有待进一步提高。     

Financial and Economic Integration's Impact on Asian Equity Markets’ Sensitivity to External Shocks

This paper investigates the spillover effects from U.S. and regional stock markets on local stock markets in the Pacific Basin region and China. We also analyze if the spillover depends on countries’ financial and economic integration. We apply a stochastic volatility model with jumps in order to separate the spillover of extreme shocks from those of normal shocks. We find that the spillovers of both normal and extreme shocks are significant for almost all Asian countries except China. We also find that the time‐variation in stock market interdependence can largely be associated with economic integration.     

Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks

Oil markets are subject to extreme shocks (e.g. Iraq’s invasion of Kuwait), causing the oil market price exhibits extreme movements, called jumps (or spikes). These jumps pose challenges on oil market volatility forecasting using conventional volatility dynamic models (e.g. GARCH model) This paper characterizes dynamics of jumps in oil market price using high frequency data from three perspectives: the probability (or intensity) of jump occurrence, the sign (e.g. positive or negative) of jumps, and the concurrence with stock market jumps. And then, the paper exploits predictive ability of these jump-related information for oil market volatility forecasting under the mixed data sampling (MIDAS) modeling framework. Our empirical results show that augmenting standard MIDAS model using the three jump-related information significantly improves the accuracy of oil market volatility forecasting. The jump intensity and negative jump size are particularly useful for predicting future oil volatility. These results are widely consistent across a variety of robustness tests. This work provides new insights on how to forecast oil market volatility in the presence of extreme shocks.     

The quality of market volatility forecasts implied by S&P 100 index option prices

This study examines the performance of the S&P 100 implied volatility as a forecast of future stock market volatility. The results indicate that the implied volatility is an upward biased forecast, but also that it contains relevant information regarding future volatility. The implied volatility dominates the historical volatility rate in terms of ex ante forecasting power, and its forecast error is orthogonal to parameters frequently linked to conditional volatility, including those employed in various ARCH specifications. These findings suggest that a linear model which corrects for the implied volatility's bias can provide a useful market-based estimator of conditional volatility.     

金融危机对证券市场波动溢出的影响研究

不同证券市场之间的波动存在时变、非对称、非线性相关的特性,尤其是在极端事件影响下,证券市场之间往往会表现出尾部相关的特性。以次贷危机为背景,利用时变Copula模型研究了证券市场间的波动溢出。结果发现无论是金融安全时期还是金融危机时期,均存在美国证券市场对中国证券市场的波动溢出,并且在金融危机期间这种波动溢出效应有增强的趋势。     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.     

Computing the market price of volatility risk in the energy commodity markets

In this paper, we demonstrate the need for a negative market price of volatility risk to recover the difference between Black–Scholes [Black, F., Scholes, M., 1973. The pricing of options and corporate liabilities. Journal of Political Economy 81, 637–654]/Black [Black, F., 1976. Studies of stock price volatility changes. In: Proceedings of the 1976 Meetings of the Business and Economics Statistics Section, American Statistical Association, pp. 177–181] implied volatility and realized-term volatility. Initially, using quasi-Monte Carlo simulation, we demonstrate numerically that a negative market price of volatility risk is the key risk premium in explaining the disparity between risk-neutral and statistical volatility in both equity and commodity-energy markets. This is robust to multiple specifications that also incorporate jumps. Next, using futures and options data from natural gas, heating oil and crude oil contracts over a 10 year period, we estimate the volatility risk premium and demonstrate that the premium is negative and significant for all three commodities. Additionally, there appear distinct seasonality patterns for natural gas and heating oil, where winter/withdrawal months have higher volatility risk premiums. Computing such a negative market price of volatility risk highlights the importance of volatility risk in understanding priced volatility in these financial markets.     

Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method

This paper analyzes dynamic volatility spillovers between four major energy commodities (i.e., crude oil, gasoline, heating oil and natural gas) in the oil-natural gas future markets. We construct a time-varying spillover method by combining the TVP-VAR-SV model and the spillover method of Diebold and Yilmaz (2009, 2012, 2014). We use the spillover method to obtain time-varying total, directional and pairwise volatility spillover indices. Our results summarize as follows: (1) The volatility spillover indices present peaks and troughs during some periods, such as shale gas revolution, financial crisis, and oil price crash; (2) After the U.S. shale gas revolution, the size of volatility spillover from natural gas future market has reduced sharply, but volatility doesn't decouple from the other three oil future markets; (3) The directional spillover is asymmetric. The crude oil and heating oil futures market are main net transmitter of volatility risk information, while the gasoline and natural gas futures markets are the net receiver; (4) For natural gas future market, the pairwise volatility spillover from crude oil future market has the most significant influence.     

Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets

We examine the spillover dynamics between the U.S. and BRICS stock markets using the multivariate DECO-GJR-GARCH model and spillover index method. We identify time variations in volatility equicorrelation and significant dynamic spillovers between these stock markets, as well as an increased impact of uncertainty on spillovers. Spillovers between markets intensify after the inception of the global financial crisis and subsequent European sovereign debt crisis. We also find, following the commencement of the crisis periods, that the U.S., Brazilian, and Chinese markets are net volatility transmitters, whereas the Russian, Indian, and South African markets are net recipients. These results shed new light on the information transmission channels between the U.S. and BRICS stock markets.     

Conditional risk and performance evaluation: Volatility timing, overconditioning, and new estimates of momentum alphas

Unconditional alphas are biased when conditional beta covaries with the market risk premium (market timing) or volatility (volatility timing). We demonstrate an additional bias (overconditioning) that can occur any time an empiricist estimates risk using information, such as a realized beta, that is not available to investors ex ante. Calibrating to U.S. equity returns, volatility timing and overconditioning can plausibly impact alphas more than market timing, which has been the focus of prior literature. To correct market- and volatility-timing biases without overconditioning, we show that incorporating realized betas into instrumental variables estimators is effective. Empirically, instrumentation reduces momentum alphas by 20-40%. Overconditioned alphas overstate performance by up to 2.5 times. We explain the sources of both the volatility-timing and overconditioning biases in momentum portfolios.     

How asymmetric is U.S. stock market volatility?

This paper explores differences in the impact of equally large positive and negative surprise return shocks in the aggregate U.S. stock market on: (1) the volatility predictions of asymmetric time-series models, (2) implied volatility, and (3) realized volatility. Following large negative surprise return shocks, both asymmetric time-series models (such as the EGARCH and GJR models) and implied volatility predict an increase in volatility and, consistent with this, ex post realized volatility normally rises as predicted. Following large positive return shocks, asymmetric time-series models predict an increase in volatility (albeit a much smaller increase than following a negative shock of the same magnitude), but both implied and realized volatilities generally fall sharply. While asymmetric time-series models predict a decline in volatility following near-zero returns, both implied and realized volatility are normally little changed from levels observed prior to the stable market. The reasons for the differences are explored.     

波动溢出网络视角的金融风险传染研究

当前各类经济风险交叉关联,金融系统的风险溢出效应备受关注,为刻画我国金融系统性风险传染的路径特征,本文从波动溢出网络的视角分析金融系统内部的风险传染机制。首先使用广义动态因子模型对收益波动的共同波动率成分和特质性波动率成分进行区分。然后,根据货币市场、资本市场、大宗商品交易市场、外汇市场、房地产市场和黄金市场之间的特质性波动溢出效应,利用基于TVP-VAR模型的方差分解溢出指数分析金融系统波动溢出的动态联动性和风险传递机制。在分析方向性波动溢出效应的基础上,采用方差分解网络方法构建起信息溢出复杂网络,从网络视角分析金融系统内部的风险传染特征。实证研究发现,房地产市场和外汇市场的净溢出效应绝对值相较于其他市场更大,其受其他市场风险冲击的影响强于对外风险溢出效应,而股票市场的单向对外风险溢出效应强度最大。在波动溢出的基础上,进一步考虑股市波动率指数与其他市场波动率指数进行投资组合的资产配置权重,计算了波动率指数投资组合的最优组合权重和对冲策略。研究结论有助于更好地理解我国金融系统的风险传染机制,对监管机构加强宏观审慎监管、投资者规避投资风险具有重要意义。     

国内外黄金市场价格间的联动关系稳定吗?——基于外部冲击视角的分析

在全球金融市场不断开放和融合的大背景下,黄金市场不但与外部市场频繁互动,其系统内部的联动关系也变得极为多元和复杂,黄金市场间的价格联动反映了信息和风险在不同市场间的传递过程。黄金价格通常会受到外部因素干扰而产生波动,但市场间的联动关系是否会因此而改变是值得重点关注的问题,黄金市场功能的有效性及稳固的市场关系是投资者利用全球黄金市场进行对冲和避险的先决条件,同时也关系到整个金融市场的稳定性。本文将研究重点聚焦于黄金市场内部,在研究中外各主要黄金市场间动态相关性和波动溢出效应的同时引入外部冲击以检验不同因素对黄金期货、现货市场间联动关系的影响从而探讨国内外黄金市场间价格联动的稳定性问题。结果表明:中国与全球主要黄金期货、现货市场间整体上保持了正相关关系,同时与各主要黄金市场间均存在显著的波动溢出效应。在一般市场条件下,外部冲击并没有显著改变中国与全球主要黄金期货、现货市场间的联动关系,表明黄金市场内部的价格联动具有较强的稳定性。     

An empirical comparison of continuous-time models of implied volatility indices

We explore the ability of alternative popular continuous-time diffusion and jump-diffusion processes to capture the dynamics of implied volatility indices over time. The performance of the various models is assessed under both econometric and financial metrics. To this end, data are employed from major European and American implied volatility indices and the rapidly growing CBOE volatility futures market. We find that the addition of jumps is necessary to capture the evolution of implied volatility indices under both metrics. Mean reversion is of second-order importance though. The results are consistent across the various metrics, markets, and construction methodologies.     

Dispersion trading: Empirical evidence from U.S. options markets

This paper develops empirical evidence on the viability of a form of volatility trading known as “dispersion trading.” The results shed light on the efficiency with which U.S. options markets price volatility.Using end-of-day implied volatilities extracted from equity option prices for the stocks that comprise the S&P 500, the implied volatility of the S&P 500 is computed using a modification of the Markowitz variance equation. This Markowitz-implied volatility is then compared to the implied volatility of the S&P 500 extracted directly from index options on the S&P 500. These contemporaneous measures of implied volatility are then examined for exploitable discrepancies both with and without transaction costs. The study covers the period October 31, 2005 through November 1, 2007.It is shown that, from a trader's perspective, index option implied volatility tended to be more often “rich” and component volatilities tended to be more often “cheap.” Nevertheless, there were times when the opposite was true; suggesting that potential dispersion trades can run in either direction.     

Global financial crisis and emerging stock market contagion: A volatility impulse response function approach

By employing the volatility impulse response (VIRF) approach, this paper presents a general framework for addressing the extent of contagion effects between the BRICSs’ and U.S. stock markets and how the BRICSs’ stock markets have been influenced in the context of the 2007–2009 global financial crisis. Our empirical results show during the period of 2007–2009 global financial crisis, there are significant contagion effects from the U.S. to the BRICSs’ stock markets. Yet, the degree of stock market reactions to such shocks differs from one market to another, depending on the level of integration with the international economy. Besides, the strengthened degree of stock market integration among the U.S. and BRICS has adverse effect such that if the 2007–2009 global financial crisis occurs today it may result in heavier impact on stock market volatility nowadays compared to the crisis-era.     

Extreme downside risk spillover from the United States and Japan to Asia-Pacific stock markets

This paper proposes a binary response model approach to measure and forecast extreme downside risks in Asia-Pacific markets given information on extreme downside risks in the U.S. and Japanese markets. The extreme downside risk of a market is measured as the occurrence of extreme downside movement—market returns falling below left-tail Value at Risk in a Markov switching framework. The empirical findings are consistent with the following notions. First, extreme downside movements of the S&P 500 and Nikkei 225 are significantly predictive for the likelihood of extreme downside movements in all the investigated Asia-Pacific markets. Second, the majority of Asia-Pacific markets become more sensitive to Japan's extreme downside risk when the Japanese market switches into high volatility periods, whereas the U.S. spillover effect is intensified only on Taiwan during high volatility periods in the U.S. Third, mainland China is the least sensitive to extreme downside risk in the U.S. and Japan, Australia is the most sensitive to the U.S., and Singapore is the most sensitive to Japan.     

Information transmission between the Gulf equity markets of Saudi Arabia and Bahrain

This paper examines whether the emerging Gulf markets of Saudi Arabia and Bahrain in conjunction with the US market exhibit cointegrating relationship. Additionally, the transmission of information and volatility spillover between the Gulf markets is explored using a bivariate EGARCH model. We find that although the markets are not cointegrated, the Gulf markets do share information flows. Specifically, we observe an asymmetric spillover of volatility from the smaller though more liberal and accessible Bahraini market to the larger and less accessible Saudi market. The observed difference in information processing may partly be due to a well-developed Bahraini financial sector that encourages wider participation by international investors who play a significant role in assimilating new information.