Impact of stock market trading on currency market volatility spillovers

This research aims to detect the volatility linkages among various currencies during operating and non-operating hours of three major stock markets (Tokyo, London and New York) by employing bivariate VAR-BEKK-GARCH model in selected currency pairs. In particular, the aim is to analyze whether the major stock markets have a differential impact on volatility linkages in currency markets. The results indicate that volatility linkages in intraday are far stronger then in daily results. One remarkable result is that rather than major currencies, some minor and exotic currencies play a leading role in volatility transmission during trading hours of major stock markets.     

International linkage of the Russian market and the Russian financial crisis: A multivariate GARCH analysis

This study considers the linkage of the Russian equity market to the world market, examining the international transmission of the Russia's 1998 financial crisis utilizing the GARCH–BEKK model proposed by Engle and Kroner [Engle, R.F., Kroner, K.F., 1995. Multivariate simultaneous generalized ARCH. Economet. Theor. 11, 122–150]. We find evidence of direct linkage between the Russian equity market with regards to returns and volatility, while the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market. At the time of the crisis, evidence of contagion is clear.     

The impact of corporate governance,regulatory differences and futures contracts on movements among portfolios of cross-listed equities: The case of Germany

We test the impact of corporate governance effects on the stock price volatility of the DAX100 and find that these variables increase the volatility and decrease the error terms statistically significant. In addition, controlling for contemporaneous and next period's movements, we find that shocks can have a significant impact on the magnitude of stock return co-movements. In particular, our results show that the impact of the German mark/Euro and German bond price index futures shocks have a significant effect on spillovers, on contemporaneous and next period's co-movements related to firms or equities that cross-list on markets with different creditor bankruptcy protection rules. On the other hand, the impact of the German mark/Euro and the German stock price index shocks related to different shareholder protection rules have a smaller impact on both the next period's co-movements and contemporaneous co-movements among or between markets.     

Return and Volatility Spillovers Between Large and Small Stocks in the UK

Abstract:  This paper investigates return and volatility spillover effects between the FTSE 100, FTSE 250 and FTSE Small Cap equity indices using the multivariate GARCH framework. We find that return and volatility transmission mechanisms between large and small stocks in the UK are asymmetric. In particular, there are significant spillover effects in both returns and volatility from the portfolios of larger stocks to the portfolios of smaller stocks. For volatility, there is also evidence of limited feedback from the portfolios of smaller stocks to the portfolios of larger stocks, although sub-period analysis suggests that this is to some extent period-specific. Simulation evidence shows that non-synchronous trading potentially explains some, but not all, of the spillover effects in returns, and that it explains none of the spillover effects in volatility. These results are consistent with a market in which information is first incorporated into the prices of large stocks before being impounded into the prices of small stocks.     

Robust outlier detection for Asia–Pacific stock index returns

Outliers can lead to model misspecifications, poor forecasts and invalid inferences. Their identification and correction is therefore an important objective of financial modeling.This paper introduces a simple method to detect outliers in a financial series. It uses an AR(1)–GARCH(1,1) model to calculate interval forecasts for one-step ahead returns that are then compared to realized returns to determine whether or not we are in the presence of an aberrant observation. The GARCH model, however, is only used as a filter and the identification algorithm remains robust to model misspecifications.The efficiency of this outlier-correction technique is first tested with a simulation study, before being applied to five Asian stock market returns to identify the outlying observations. After an analysis of these extreme fluctuations, the out-of-sample forecasting performance of our outlier-corrected model is then compared to the classical forecasts of a GARCH model in which no account is taken of outliers.     

ARCH and GARCH models vs. martingale volatility of finance market returns

ARCH and GARCH models assume either i.i.d. or ‘white noise’ as is usual in regression analysis, while also assuming memory in a conditional mean square fluctuation with stationary increments. We will show that ARCH/GARCH is inconsistent with uncorrelated increments, violating the i.i.d. and ‘white’ assumptions, and violating finance data and the efficient market hypothesis as well.     

Multivariate Modeling of Daily REIT Volatility

This paper examines volatility in REITs using a multivariate GARCH based model. The Multivariate VAR–GARCH technique documents the return and volatility linkages between REIT sub-sectors and also examines the influence of other US equity series. The motivation is for investors to incorporate time-varyng volatility and correlations in their portfolio selection. The results illustrate the differences in results when higher frequency daily data is tested in comparison to the monthly data that has been commonly used in the existing literature. The linkages both within the REIT sector and between REITs and related sectors such as value stocks are weaker than commonly found in monthly studies. The broad market would appear to be more influential in the daily case.     

A股与H股市场的差异与互动

本文选择了28家既在香港发行H股,又在内地发行A股的上市公司作为样本,研究分割市场之间的差异性和互动关系.通过对比相同上市公司在两个市场上的收益性和波动性差异,本文发现:两个市场在年报公告、中报公告、季报公告以及预告事件下获得的超额收益具有显著差异,而在分红通过公告事件下未产生显著差异;同时,除了分红通过公告(旧信息)事件未引起市场产生明显的波动以外,其余事件都对两个市场产生了显著的波动性影响.另外,我们也发现"H股引起A股变化"的可能性要大于"A股引起H股变化"的可能性.     

基于CDM机制的国际碳排放权贸易价格波动性研究

运用规范分析和基于GARCH模型族的实证分析发现:清洁发展机制(CDM)下国际碳排放权核证减排单位(CERs)市场的价格波动是政治博弈、国际经济形势等多重因素共同冲击的结果。其价格波动呈现时变性、聚集性和持续性特征,市场"杠杆效应"明显。我国作为全球CDM项目的最大供给方,为了掌握定价权,必须寻求CERs市场价格波动规律、积极参与国际气候环境条款的谈判、选择恰当贸易时机和建立CDM项目风险管理体系。     

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.     

Volatility spillovers and hedging effectiveness between the oil market and Eurozone sectors: A tale of two crises

This paper aims to analyze the mean and volatility spillovers between oil prices and the Eurozone supersector returns. It uses daily data of the Brent prices and 19 Eurozone supersector indices for the period from August 2004 to August 2015. This area experienced two important instabilities in that period, the global financial crisis (GFC) and the Euro debt crisis (EDC). Because financial turbulences are suspected to induce changes in the volatility dynamics, the full sample is divided into three sub-samples. Empirically, this study employs a bivariate VAR-BEKK-GARCH model that allows for transmission in volatility. The obtained volatilities and covariances are used to compute the optimal weights and hedge ratios for oil–stock portfolio holdings. The findings show that both mean and volatility spillovers between the oil market and the different Eurozone sectors are time-varying and heterogeneous. In the GFC sub-period, there is evidence of contagion effects because there is an intensification of volatility spillovers. The EDC does not seem to have induced any particular change in the spillover effects. The optimal weights, hedge ratios, and correlation analysis results allow an accurate understanding of the time series relationship between the two markets and are useful for financial market participants and policymakers.     

Empirical analysis of dynamic correlations of stock returns: evidence from Chinese A-share and B-share markets

This paper examines the dynamic correlation structure between A-share and B-share stock returns based on three different measures of correlation coefficients. Testing the models by employing daily stock-return data for the period from 1996 through 2003, we reach the following empirical conclusions. First, the correlation coefficients between A-share and B-share stock returns are time varying. Second, the dynamic path of the correlation coefficients indicates that the correlation coefficients are significantly correlated with the trend factor. Third, there is a substantial spillover effect from the Asian crisis to Chinese stock-return dynamic correlations. Fourth, the evidence suggests that the time-varying correlations are significantly associated with excessive trading activity as measured by excessive trading volumes and high–low price differentials. Fifth, the correlation between A-share and B-share markets has increased since the relaxation of the restriction on B-share market investments by domestic investors.     

基于波动效应与价格发现的期指仿真交易研究

沪深300股指期货仿真交易的推出,对我国现货市场的影响如何以及这种影响是否有利于现货效率的改进。首次采用修正的GARCH模型和向量误差修正模型（VEC）将股指期货推出后现货市场波动性的变化和股指期货与现货市场的价格发现功能结合起来进行对比研究。结果表明,期指仿真交易的推出对于现货市场效率的改进确实存在正面的影响。其引入在短期内加大了现货市场的波动,但这一波动正是市场信息流动加速的反映,因而提高了市场信息的传递效率。同时期货价格领先于现货价格,存在由期货市场到现货市场长期的单向因果关系,说明期货价格具有引导现货价格向均衡方向调整的功能,从而在经验上支持了股指期货市场的开放政策。     

An investigation of return and volatility linkages among equity markets: A study of selected European and emerging countries

This paper investigates the linkages among equity returns (based on exchange traded funds, ETF) and transmission of volatilities in the following countries: Germany, Austria, Poland, Russia and Turkey. Multivariate Autoregressive Moving Averages (MARMA) and the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) methodologies are utilized. The findings include the existence of significant co-movement of returns among countries in the sample. Also, Turkish and Russian markets were found to be more volatile than Austria, Germany and Poland. However, volatilities in Russia and Turkey do not persist very long. Finally, there is strong evidence of volatility spillovers. All of the countries in the sample, with the exception of Turkey, experience volatility spillovers from other markets. The presence of spillovers among return series and persistence of volatilities are useful to investors interested in diversifying their portfolios and to traders/fund managers who are interested in maximizing returns.     

Price limits in futures markets: effects on the price discovery process and volatility

Price limits are actively employed by many futures exchanges as a regulatory mechanism directed at reducing volatility and improving price discovery process. The aim of this paper is to investigate whether price limits achieve these goals without affecting market liquidity for a number of agricultural futures contracts. We employ models of changing volatility in order to show that price limits do not appear to significantly reduce market volatility. In addition, we find evidence confirming the hypothesis that price limits delay price discovery instead of facilitating it. Our results also suggest that the impact of price limits on volatility and price reversals, found in previous studies, are mainly due to the properties inherent to the futures returns, such as volatility clustering. Finally, although trading decreases significantly due to the price limits, traders do not seem to switch from the contracts affected by price limits to other maturities in order to minimize the impact of circuit breakers.     

A nesting framework for Markov-switching GARCH modelling with an application to the German stock market

In this paper, we establish a generalized two-regime Markov-switching GARCH model which enables us to specify complex (symmetric and asymmetric) GARCH equations that may differ considerably in their functional forms across the two Markov regimes. We show how previously proposed collapsing procedures for the Markov-switching GARCH model can be extended to estimate our general specification by means of classical maximum-likelihood methods. We estimate several variants of the generalized Markov-switching GARCH model using daily excess returns of the German stock market index DAX sampled during the last decade. Our empirical study has two major findings. First, our generalized model outperforms all nested specifications in terms of (a) statistical fit (when model selection is based on likelihood ratio tests) and (b) out-of-sample volatility forecasting performance. Second, we find significant Markov-switching structures in German stock market data, with substantially differing volatility equations across the regimes.     

Impact of macroeconomic news on metal futures

This paper uses intra-day data for the period 2002 through 2008 to examine the intensity, direction, and speed of impact of US macroeconomic news announcements on the return, volatility and trading volume of three important commodities - gold, silver and copper futures. We find that the response of metal futures to economic news surprises is both swift and significant, with the 8:30 am set of announcements - in particular, nonfarm payrolls and durable goods orders - having the largest impact. Furthermore, announcements that reflect an unexpected improvement in the economy tend to have a negative impact on gold and silver prices; however, they tend to have a positive effect on copper prices. In comparison, realized volatility and volume for all three metals are positively influenced by economic news. Finally, there is evidence that several news announcements exert an asymmetric impact on market activity variables.     

Tail risk of coal futures in China's market

This study evaluates the downside tail risk of coal futures contracts (coke, coking coal and thermal coal) traded in the Chinese market between 2011 and 2021, measured by value at risk (VaR). We examine the one-day-ahead VaR forecasting performance with a hybrid econometric and deep learning model (GARCH-LSTM), GARCH family models, extreme value theory models, quantile regression models and two naïve models (historical simulation and exponentially weighted moving average). We use four backtesting techniques and the model confidence set to identify the optimal models. The results suggest that the models focusing on tail risk or utilising long short-term memory generate more effective risk management.     

Discussions on the spurious hyperbolic memory in the conditional variance and a new model

This paper studies the spurious hyperbolic memory in the conditional variance caused by the Markov Regime-Switching GARCH (MRS-GARCH) process. We firstly propose an illustrative cause of this spuriousness and provide simulation evidence. An MRS Hyperbolic GARCH (MRS-HGARCH) model is then developed to successfully address it. Related statistical properties including the stationarity conditions and asymptotic behaviours of the maximum likelihood estimators of the MRS-HGARCH process are also investigated. An empirical study of the S&P 500 and TOPIX indexes returns is then conducted which demonstrates that our MRS-HGARCH model can provide a more reliable estimator of the hyperbolic-memory parameter and outperform both the HGARCH and MRS-GARCH models.