Volatility and information flows in emerging equity market: A case of the Korean Stock Exchange

Applying the generalized autoregressive conditional heteroskedasticity (GARCH) model to the Korean Stock Exchange, this study examines: (1) the statistical property of time-varying volatility in returns and trading volume data found in an emerging capital market, and (2) the property of the conditional variances of returns in predicting the flow patterns of information across the firms of different sizes. The results find that current trading volume as a proxy of information arrival dramatically reduces the persistence of the conditional variance, meaning that the arrival of information is a source of the ARCH effect in the emerging market just as it is in the U.S. The results also show that just as the volatility of larger firms can be predicted by shocks to smaller firms, the volatility of smaller firms can be predicted by shocks to larger firms. However, the volatility spillover effect from larger to smaller firms is more significant than that from smaller to larger firms.     

Macroeconomic Factors and the Asymmetric Predictability of Conditional Variances

This paper investigates the predictability of the volatilities of large versus small firms. Using AR-GARCH models we show that there is symmetry in the ability of firms of different market values to predict conditional variances. Specifically, we show that volatility surprises of small (large) firms are important in predicting the conditional variance of large (small) firms. These results are different than those previously reported which indicate that there is an asymmetry in the predictability of the volatilities of large versus small firms. This predictive ability is still present when the equation of conditional variance includes state variables such as the default premium, dividend yield and the term premium. Finally, our results indicate that the pattern of symmetric predictability is present in both pre- and post-war sample periods.     

Market capitalisation,cross-correlations,the lead/lag structure and microstructure effects in the Indian stock market

The lead/lag relationship between portfolios comprising large and small cap firms is analytically derived in terms of their speeds of adjustment and degrees of thin trading. Using a number of Indian equity index series that differ in their market capitalization characteristics, large cap indices are found to lead small cap indices and to have higher speeds of adjustment towards intrinsic values. However, pure thin trading effects and an interaction effect between thin trading and speeds of adjustment are found to make significant contributions to the lead/lag effect. An empirical analysis of the underlying intrinsic value process using a reduced form model developed in the paper indicates that a small degree of overreaction is present in intrinsic values series.     

Dynamic relations of uncertainty expectations: a conditional assessment of implied volatility indices

This study examines the spillover effects in international financial markets with respect to implied volatility indices. The use of the latter as the basis of integration analysis means that we test market participants’ expectations and not the actual price fluctuations. The empirical analysis, which includes all publicly available implied volatility indices, employs the dynamic conditional correlation model of Engle (2002) and its findings suggest that there is significant integration of investors’ expectations about future uncertainty. Furthermore, by accounting for the dynamic volatility of implied volatility inter-dependencies, we are able to reveal possible shifts in conditional correlations of market expectations over time. More specifically, our findings show a slight increase in the conditional correlations for all the volatility indices under review over the years and prove that in periods of turbulence in the financial markets the conditional correlations across implied volatility indices increase.     

Quarterly earnings announcements and intra-industry information transfer from the Pacific to the Atlantic

In this study, we explore intra-industry information transfer of quarterly earnings announcements for six major developed markets including the United States. Using an event study methodology, we find that the average cumulative abnormal returns (CARs) of peer firms exhibit a positive and significant relationship with the CARs of announcing firms in the same country and industry over the three-day window surrounding quarterly earnings announcements. During periods of high past market volatility, earnings announcements demonstrate magnified information spillover effects on peer firms. Also, our results suggest that announcing firms with larger market capitalization generate greater intra-industry information transfer.     

Capital Asset Pricing Model and Stochastic Volatility: A Case Study of India

The existing literature demonstrates that under a general equilibrium model, the performance of the Capital Asset Pricing Model (CAPM) can be improved significantly by using conditional consumption and market return volatilities as factors. This article tests the validity of these factors explaining stock return differences using a less developed country (India) as a case study. While the earlier studies used panel data to test CAPM, we use portfolios sorted by size and book-to-market equity (BE/ME) ratio. We found that conditional volatility has a limited effect on firms with large capitalization but a significant impact on small-growth and small-value firms.     

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。     

The Political Economy of Volatility Dynamics in the Hong Kong Stock Market

Despite its obvious importance, little empirical research has examined the impact of political risk on stock market volatility. This paper uses data on the Hong Kong stock market over a long sample period to investigate whether political risk has induced regime shifts in stock market volatility. Regime shifts are modelled via a Markov switching EGARCH model that allows for regime-dependent volatility asymmetry. We find strong evidence of regime shifts in conditional volatility as well as significant volatility asymmetry in high volatility periods. Major political uncertainties were reflected in a switch to the high-volatility regime. However, contrary to popular perceptions, we find no evidence that the Hong Kong stock market has become persistently more volatile since the start of Sino-British political negotiations in 1982.     

Small caps in international equity portfolios: the effects of variance risk

We show that predictable covariances between means and variances of stock returns may have a first order effect on portfolio composition. In an international asset menu that includes both European and North American small capitalization equity indices, we find that a three-state, heteroskedastic regime switching VAR model is required to provide a good fit to weekly return data and to accurately predict the dynamics in the joint density of returns. As a result of the non-linear dynamic features revealed by the data, small cap portfolios become riskier in bear markets, i.e., display negative co-skewness with other stock indices. Because of this property, a power utility investor ought to hold a well-diversified portfolio, despite the high risk premium and Sharpe ratios offered by small capitalization stocks. On the contrary, small caps command large optimal weights when the investor ignores variance risk, by incorrectly assuming joint normality of returns.      

Cross-border transmission of stock price volatility: evidence from the overlapping trading hours

Using high-frequency (5-minute returns) data, the transmission pattern of intraday volatility among three international stock markets (i.e., the United States, the United Kingdom, and Canada) during their overlapping trading hours (9:30–11:30 a.m. New York time). The major findings are as follows. First, the conditional variance of a domestic market is affected not only by the volatility surprises of its own market, but also by those of foreign markets. This finding holds for the United States as well as for Canada and the United Kingdom, implying that the information contained in the volatility surprises of each national market is clearly transmitted to other national markets. The volatility spillover is not unidirectional. Second, the magnitude of volatility spillover does not decrease monotonically as the lag length increases, indicating that the effect of a foreign volatility shock on the conditional variance of the domestic market tends to persist.     

Trading volume,time-varying conditional volatility,and asymmetric volatility spillover in the Saudi stock market

Despite the well known importance of volatility–volume relationship, there is a paucity of research on this topic in emerging markets. We attempt to partially fill this gap by investigating volatility–volume relationship in the most important exchange market in the Middle East. We test the effect of trading volume on the persistence of the time-varying conditional volatility of returns in the Saudi stock market. Overall our results support the mixture of distribution hypothesis at the firm level. We also use two different proxies for information arrival, intra-day volatility, and overnight indicators. We find that these are good proxies for information and are important as contemporaneous volume in explaining conditional volatility. We also test for the volatility spillover direction between large- and small-cap portfolios. Our results show that the spillover effect is larger and statistically significant from large to small companies.     

The effect of exchange rate variability on US shareholder wealth

We examine the relationship between financial crisis exchange rate variability and equity return volatility for US multinationals. Empirical analysis of the major financial crises of the last decades reveals that stock return variability increases significantly in the aftermath of a crisis, even relative to the increase in stock return volatility for other firms belonging to the same industry and market capitalization class. In conjunction with this increase in total volatility, there is also an increase in stock market risk (β) for multinational firms. Moreover, trade and service oriented industries appear to be particularly sensitive to these changing exchange rate conditions.     

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。     

Price discovery for cross-listed firms with foreign IPOs

We investigate the inter-market return and volatility linkages for an atypical case of firms with foreign IPOs that subsequently cross-listed in their domestic market. In particular, our data set consists of a unique sample of 29 Israeli firms that went public in the US (host market) and then cross-listed in the Israeli market (home market). To estimate the spillover effects, we employ bivariate GARCH models, assuming both constant and dynamic conditional correlation specifications. At the aggregate market level, we find unidirectional mean and volatility spillovers from the US to the Israeli market. For the portfolios of Israeli cross-listed stocks, we report significant spillovers, at both the mean and volatility levels, from the underlying stocks in the Israeli market to their American Depository Receipts (ADRs) but not vice versa. Thus, the home market dominates the host market in the price discovery process in this atypical international cross-listing case, providing new evidence in support of the home bias hypothesis. We also find that external shocks originating from the Middle East peace process have no impact on the conditional correlation between the two markets but external shocks originating from the world and regional markets impact the conditional correlation positively.     

Does futures trading increase stock market volatility? The case of the Nikkei stock index futures markets

We propose new tests to examine whether stock index futures affect stock market volatility. These tests decompose spot portfolio volatility into the cross-sectional dispersion and the average volatility of returns on the portfolio's constituent securities. Our tests show that for Nikkei stocks spot portfolio volatility increased and cross-sectional dispersion decreased compared with average volatility when Nikkei futures began trading on the Osaka Securities Exchange, but not on the Singapore International Monetary Exchange. For non-Nikkei stocks, no shift occurred when futures trading began on either exchange. These findings are consistent with the hypotheses that futures trading increases spot portfolio volatility but that there is no volatility “spillover” to stocks against which futures are not traded. However, the increase in volatility attributable to futures trading is small compared with volatility shifts induced by changes in broad economic factors.     

Sudden changes in volatility: The case of five central European stock markets

This paper investigates sudden changes in volatility in the stock markets of new European Union (EU) members by utilizing the iterated cumulative sums of squares (ICSS) algorithm. Using weekly data over the sample period 1994–2006, the time period of sudden change in variance of returns and the length of this variance shift are detected. A sudden change in volatility seems to arise from the evolution of emerging stock markets, exchange rate policy changes and financial crises. Evidence also reveals that when sudden shifts are taken into account in the GARCH models, the persistence of volatility is reduced significantly in every series. It suggests that many previous studies may have overestimated the degree of volatility persistence existing in financial time series.     

Term Structure of Interest Rates with Regime Shifts

We develop a term structure model where the short interest rate and the market price of risks are subject to discrete regime shifts. Empirical evidence from efficient method of moments estimation provides considerable support for the regime shifts model. Standard models, which include affine specifications with up to three factors, are sharply rejected in the data. Our diagnostics show that only the regime shifts model can account for the well–documented violations of the expectations hypothesis, the observed conditional volatility, and the conditional correlation across yields. We find that regimes are intimately related to business cycles.     

Periodic Stochastic Volatility and Fat Tails

This article provides a comprehensive analysis of the size andstatistical significance of the day of the week, month of theyear, and holiday effects in daily stock index returns and volatility.We employ data from the Dow Jones Industrial Average (DJIA),the S&P 500, the S&P MidCap 400, and the S&P SmallCap600 in order to test whether the seasonal patterns of mediumand small firms are similar to those of large firms. Using formalhypothesis tests based on bootstrapping, we demonstrate thatthere are more significant calendar effects in volatility thanin expected returns, especially for the two large cap indices.More importantly, we introduce the periodic stochastic volatility(PSV) model for characterizing the observed seasonal patternsof daily financial market volatility. We analyze the interactionbetween seasonal heteroskedasticity and fat tails by comparingthe performance of Gaussian PSV and fat-tailed PSVt specificationsto the plain vanilla SV and SVt benchmarks. Consistent withour model-free results, we find strong evidence of seasonalperiodicity in volatility, which essentially eliminates theneed for a fat-tailed conditional distribution, and is robustto the exclusion of the crash of 1987 outliers.     

Convergence and risk-return linkages across financial service firms

We examine the risk and return linkages across US commercial banks, securities firms, and life insurance companies during the 1991–2001 period. After controlling for changes in the broader stock market, interest rates, and foreign currency values, we find that return and risk interdependencies across these financial firms are significant and size-varying; larger institutions display stronger volatility transmission linkages, while smaller ones exhibit more prominent return-related linkages. The tighter link in risk among large financial institutions (FIs) suggests stronger convergence, employment of common models of risk measurement and risk management, and more intense inter-industry competition, particularly between large banks and large securities firms, compared to smaller institutions. Lack of risk spillover among smaller FIs confirms the intuition that they typically assume more localized and idiosyncratic risk. The co-movement of stock returns among smaller FIs has been helped by the effects of locally based factors, such as economic conditions and state regulations, on all such institutions, and a less diversified product set. Differences in spillover patterns between large and smaller institutions have implications on investment choices and mergers and acquisitions in the industry. Introduction of the Gramm-Leach-Bliley Act (1999) has had dissimilar effects on the riskiness of large versus smaller life insurance and securities firms, and an insignificant effect on commercial banks.     

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。