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Article
Publication date: 24 May 2021

Dejun Xie, Yu Cui and Yujian Liu

The focus of the current research is to examine whether mixed-frequency investor sentiment affects stock volatility in the China A-shares stock market.

Abstract

Purpose

The focus of the current research is to examine whether mixed-frequency investor sentiment affects stock volatility in the China A-shares stock market.

Design/methodology/approach

Mixed-frequency sampling models are employed to find the relationship between stock market volatility and mixed-frequency investor sentiment. Principal analysis and MIDAS-GARCH model are used to calibrate the impact of investor sentiment on the large-horizon components of volatility of Shanghai composite stocks.

Findings

The results show that the volatility in Chinese stock market is positively influenced by BW investor sentiment index, when the sentiment index encompasses weighted mixed frequencies with different horizons. In particular, the impact of mixed-frequency investor sentiment is most significantly on the large-horizon components of volatility. Moreover, it is demonstrated that mixed-frequency sampling model has better explanatory powers than exogenous regression models when accounting for the relationship between investor sentiment and stock volatility.

Practical implications

Given the various unique features of Chinese stock market and its importance as the major representative of world emerging markets, the findings of the current paper are of particularly scholarly and practical significance by shedding lights to the applicableness GARCH-MIDAS in the focused frontiers.

Originality/value

A more accurate and insightful understanding of volatility has always been one of the core scholarly pursuits since the influential structural time series modeling of Engle (1982) and the seminal work of Engle and Rangel (2008) attempting to accommodate macroeconomic factors into volatility models. However, the studies in this regard are so far relatively scarce with mixed conclusions. The current study fills such gaps with improved MIDAS-GARCH approach and new evidence from Shanghai A-share market.

Details

China Finance Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1398

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Article
Publication date: 15 June 2012

Ritab Al‐Khouri and Abdulkhader Abdallah

The purpose of this paper is to examine whether stock market liberalization creates excess stock return volatility in the Qatar Exchange (QSC).

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643

Abstract

Purpose

The purpose of this paper is to examine whether stock market liberalization creates excess stock return volatility in the Qatar Exchange (QSC).

Design/methodology/approach

The study utilizes two methods, simple analysis of variance and the EGARCH model with dummy variables.

Findings

Results reveal no change in market volatility following the partial removal of the restrictions on foreign participation. Results suggest, however, that the degree of persistence in volatility is high, which implies that once volatility increases it remains high over a long run. In addition, conditional volatility tends to rise when the absolute value of the standardized residuals was large. While, contrary to what has been found in the literature, the return volatility seems to be symmetric.

Research limitations/implications

The finding of volatility persistence and clustering might imply an inefficient stock market. Therefore, policy makers should emphasize and direct their attention toward increasing the efficiency of the stock market.

Practical implications

Being able to make predictions about financial market volatility is of special importance to investors and policy makers since it makes available to them a measure of risk exposure in their investments and decisions.

Originality/value

This paper provides a contribution to the empirical literature on stock market volatility. It is the only study, to the authors' knowledge, that investigates the issue of QSC liberalization and volatility. The authors believe that QSC has its own unique characteristics, and the results of the study depend mainly on the market's specific conditions, the quality of its financial institutions and the extent of financial liberalization obtained.

Details

International Journal of Islamic and Middle Eastern Finance and Management, vol. 5 no. 2
Type: Research Article
ISSN: 1753-8394

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Article
Publication date: 22 November 2019

Jitendra Kumar Dixit and Vivek Agrawal

Volatility is a permanent behavior of the stock market around the globe. The presence of the volatility in the stock price makes it possible to earn abnormal profits by…

Abstract

Purpose

Volatility is a permanent behavior of the stock market around the globe. The presence of the volatility in the stock price makes it possible to earn abnormal profits by risk seeking investors and creates hesitancy among risk averse investors as high volatility means high return with high risk. Investors always consider market volatility before making any investment decisions. Random fluctuations are termed as volatility of stock market. Volatility in financial markets is reflected because of uncertainty in the price and return, unexpected events and non-constant variance that can be measured through the generalized autoregressive conditional heteroscedasticity family models and that will give an insight for investment decision-making.

Design/methodology/approach

Daily data of the closing value of Bombay Stock Exchange (BSE) (Sensex) and National Stock Exchange (NSE) (Nifty) from April 1, 2011 to March 31, 2017 is collected through the web-portal of BSE (www.bseindia.com) and NSE (www.nseindia.com) for the analysis purpose.

Findings

The outcome of the study suggested that P-GARCH model is most suitable to predict and forecast the stock market volatility for both the markets.

Research limitations/implications

Future research can be extended to other stock market segments and sectoral indices to explore and forecast the volatility to establish a trade-off between risk and return.

Originality/value

The results of previous studies available are not conducive to this research, and very limited scholarly work is available in the Indian context, so required to be re-explored to identify the appropriate model to predict market volatility.

Details

foresight, vol. 22 no. 1
Type: Research Article
ISSN: 1463-6689

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Article
Publication date: 18 April 2017

Bhaskar Bagchi

The purpose of this paper is to examine the dynamic relationship between crude oil price volatility and stock markets in the emerging economies like BRIC (Brazil, Russia…

Abstract

Purpose

The purpose of this paper is to examine the dynamic relationship between crude oil price volatility and stock markets in the emerging economies like BRIC (Brazil, Russia, India and China) countries in the context of sharp continuous fall in the crude oil price in recent times.

Design/methodology/approach

The stock price volatility is partly explained by volatility in crude oil price. The author adopt an Asymmetric Power ARCH (APARCH) model which takes into account long memory behavior, speed of market information, asymmetries and leverage effects.

Findings

For Bovespa, MICEX, BSE Sensex and crude oil there is an asymmetric response of volatilities to positive and negative shocks and negative correlation exists between returns and volatility indicating that negative information will create greater volatility. However, for Shanghai Composite positive information has greater effect on stock price volatility in comparison to negative information. The study results also suggest the presence long memory behavior and persistent volatility clustering phenomenon amongst crude oil price and stock markets of the BRIC countries.

Originality/value

The present study makes a number of contributions to the existing literature in the following ways. First, the author have considered crude oil prices up to January 31, 2016, so that the study can reflect the impact of declining trend of crude oil prices on the stock indices which is also regarded as “new oil price shock” to measure the volatility between crude oil price and stock market indices of BRIC countries. Second, the volatility is captured by APARCH model which takes into account long memory behavior, speed of market information, asymmetries and leverage effects.

Details

International Journal of Emerging Markets, vol. 12 no. 2
Type: Research Article
ISSN: 1746-8809

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Article
Publication date: 1 March 2004

Nidal Rashid Sabri

This paper explored the new features of emerging stock markets, in order to point out the most associated indicators of increasing stock return volatility, which may lead…

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1297

Abstract

This paper explored the new features of emerging stock markets, in order to point out the most associated indicators of increasing stock return volatility, which may lead to instability of emerging markets. The study covers a sample of five geographical areas of emerging economies, including Mexico, Korea, South Africa, Turkey, and Malaysia. It used the backward multiple‐regression technique to examine the relationship between monthly changes of stock price indices as dependent variable and the associated predicting local as well as international variables, which represent possible causes of increasing price volatility and initiating crises in emerging stock markets. The study covered monthly data for a period of forty‐eight months from January 1997 to December 2000. The study revealed that stock trading volume and currency exchange rate respectively represent the highest positive correlation to the emerging stock price changes; thus represent the most predicting variables of increasing price volatility. International stock price index, deposit interest rate, and bond trading volume were moderate predicting variables for emerging stock price volatility. While changes in inflation rate showed the least positive correlation to stock price volatility, thus represents the least predicting variable.

Details

Review of Accounting and Finance, vol. 3 no. 3
Type: Research Article
ISSN: 1475-7702

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Article
Publication date: 31 October 2008

Duc Khuong Nguyen and Mondher Bellalah

This paper aims to empirically reexamine the dynamic changes in emerging market volatility around stock market liberalization.

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1539

Abstract

Purpose

This paper aims to empirically reexamine the dynamic changes in emerging market volatility around stock market liberalization.

Design/methodology/approach

First, a bivariate GARCH‐M model which counts for partial market integration is developed for modeling stock market volatility in emerging market countries. Second, the Bai and Perron stability test in a linear framework and a pooled time‐series cross‐section model were employed to examine the empirical relationship between stock market liberalization and volatility.

Findings

Structural breaks detected in emerging market volatility series did not take place at the time of official liberalization dates, but they rather coincide with alternative events of liberalization process. The effects of official liberalization on return volatility are on average insignificant. The stock return volatility is however lowered when the participation of the US investors becomes effective and important on emerging markets, and when emerging markets increase in size.

Research limitations/implications

The study assumes a static degree of market integration. Future research should extend our model by using a time‐varying measure of market integration.

Practical implications

Policymakers in frontier markets should open up local stock markets to attract foreign investments and to allow local firms to benefit from international risk sharing. Also, the gradual embankment of market‐liberalization is necessary to gain investors' confidence and to prevent the harmful effects of foreign capital flows.

Originality/value

The consideration of alternative events of liberalization process and the use of a powerful stability test to examine the time‐series properties of conditional volatilities.

Details

Review of Accounting and Finance, vol. 7 no. 4
Type: Research Article
ISSN: 1475-7702

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Article
Publication date: 29 May 2019

Feng Zhan

The purpose of this paper is to examine the impact of national culture on herding behavior across international financial markets.

Abstract

Purpose

The purpose of this paper is to examine the impact of national culture on herding behavior across international financial markets.

Design/methodology/approach

The relation between national culture and investor behavior, and how it impacts overall market volatility is studied by examining synchronized stock price movements and stock market volatility in 47 countries around the world over the period of January 2003–May 2012.

Findings

The author finds that nations with lower values of individualistic culture are more likely to have a higher number of synchronized stock price movements. Further, the correlation between stock price movements apparently increases stock market volatility. Nations with high individualistic culture have a lower number of synchronized stock price movements and, thus, have lower levels of stock market volatility. The positive relationship between synchronized stock price movements and stock market volatility is stronger for emerging markets during the financial crisis from June 2007 to December 2008.

Originality/value

The empirical results in this paper indicate that a portion of the difference in market level volatility is attributed to the investor bias of different cultures. Investor behavior bias creates excess volatility that drives stock prices away from fundamentals. This impact is strong in nations with lower individualistic culture. The result from this research could also have a wide implication in the investment industry.

Details

International Journal of Managerial Finance, vol. 15 no. 3
Type: Research Article
ISSN: 1743-9132

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Article
Publication date: 1 October 1995

Francis E. Laatsch and Shane A. Johnson

We investigate the causal relationships between volatility implied in Major Market Index (MMI) options and its component stocks' options from January, 1987 to October…

Abstract

We investigate the causal relationships between volatility implied in Major Market Index (MMI) options and its component stocks' options from January, 1987 to October, 1989. We find that MMI implied volatility Granger causes component stock implied volatility for all twenty component stocks, which is consistent with the hypothesis that changes in volatility in index options markets leads volatility in underlying component (cash) markets. When we further analyze the sample by subperiod, we find that the causal relationships are insignificant in the period after the October 1987 crash, which is consistent with the hypothesis that exchange and regulatory actions taken after the crash weakened the influence of index options markets on cash markets. Trading strategies and programs involving stock index options and futures have been blamed for increasing volatility of the stock market. Indeed, trading in index futures and options markets has been blamed for much of the drop in stock prices in the crash of October 1987. After the crash, regulators took several actions to reduce the influence of futures and options market volatility on cash market volatility. If regulators' fears were legitimate and their efforts were successful, the volatility linkage between index options markets and their underlying cash markets should have been weakened. This paper provides two important contributions to our understanding of the volatility implications of index options markets. First, we examine the causality relationships between index and component stock implied volatility to assess whether or not changes in volatility in the index option market lead changes in volatility in the underlying component stock markets. Second, we test whether the causal relationships differ before and after the October 1987 crash to assess whether or not regulatory actions after the crash caused a change in these relationships. We measure volatility using implied standard deviations (ISDs) from options on the Major Market Index (MMI) and its component stocks. We form time series of ISDs for both the MMI and its component stocks, and then apply Granger causality tests to the series. For the full sample period of January 1987 to October 1989, we find that changes in index ISDs do Granger cause changes in component stock ISDs for all twenty component stocks, evidence consistent with the notion that volatility in index option market leads volatility in the component (cash) market. When we analyze the sample by subperiod, however, we find that the significant Granger causality holds only in the period before the October 1987 crash. Post‐crash subperiods show insignificant causality relationships, which suggests that efforts taken by exchange officials and regulators to reduce the influence of volatility in the index options and futures markets on cash market volatility were successful. The remainder of the paper is structured as follows. In Section I we discuss the potential for causal relationships between index option markets and their component markets and review related literature. Section II contains a discussion of our methodology and a description of our data. Section III contains a discussion of our results and Section IV concludes.

Details

Managerial Finance, vol. 21 no. 10
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 8 May 2018

Khalil Jebran

This paper aims to examine the volatility spillover dynamics between stock and foreign exchange market of China considering subprime 2007 financial crisis period.

Abstract

Purpose

This paper aims to examine the volatility spillover dynamics between stock and foreign exchange market of China considering subprime 2007 financial crisis period.

Design/methodology/approach

This study considered daily data from January 2, 2002, to December 31, 2013. The sample period has been further divided into three periods; full sample period (January 2002-December 2013), pre-crisis period (January 2002-October 2007) and post-crisis period (October 2007-December 2013). This study opted Exponential Generalized Autoregressive Heteroskedasticity (EGARCH) model for the purpose of investigating asymmetric volatility spillover.

Findings

The results obtained using the EGARCH model imply that volatility spillover dynamics varies from period to period. In full sample period, the results show evidence of significant unidirectional volatility spillover from foreign exchange market to stock market. In pre-crisis period, the results indicate unidirectional volatility spillover from stock market to foreign exchange market. However, in post-crisis period, the results reveal significant bidirectional volatility spillover between stock and foreign exchange market.

Practical implications

The results of the study are important for policy makers because understanding the behavior of the financial markets, i.e. stock and foreign exchange market, would increase the success of policies implemented in a crisis situation. The results would help investors to formulate efficient portfolios.

Originality/value

This study is an important contribution to the existing literature in terms of analyzing volatility spillover between stock and foreign exchange market in an emerging economy, China. Furthermore, this study explored the volatility spillover dynamics between the two markets by considering the pre and post subprime Asian crisis period.

Details

Journal of Asia Business Studies, vol. 12 no. 2
Type: Research Article
ISSN: 1558-7894

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Article
Publication date: 28 October 2021

Kim Hiang Liow and Jeongseop Song

With growing interdependence between financial markets, the goal of this paper is to examine the dynamic interdependence between corporate equity and public real estate…

Abstract

Purpose

With growing interdependence between financial markets, the goal of this paper is to examine the dynamic interdependence between corporate equity and public real estate markets for the USA and a select group of seven European developed economies under a cross-country framework in crisis and boom market conditions. Dynamic interdependence is related to four measures of market linkages of “correlation, spillover, connectedness and causality”.

Design/methodology/approach

This study adopts a four-step investigation. The authors first estimate “time-varying variance–covariance spillovers and implied correlations” modeled with the bivariate BEKK-MGARCH methods. Second, the methods of Diebold and Yilmaz (2012, 2014) measure the conditional volatility spillover-connectedness effects across the corporate equity and public real estate markets based on a decomposition of the forecast error variance. Third, the authors implement nonlinear bivariate and multivariate causality tests to understand the lead-lag dynamics of the two asset markets' returns, volatilities and net directional volatility connectedness across different sample periods. Finally, the authors conclude the study by providing a portfolio hedging analysis.

Findings

The authors find that corporate equity and public real estate are moderately interdependent to the extent that their diversification benefits increases in the longer term. Moreover, the authors find increased corporate equity-public real estate causal dependence of the market groups of the European and international portfolios during the GFC and INTERCRISIS periods. The nonlinear causality test findings indicate that the joint information of asset markets can be a useful source of prediction for future innovation of market risks. Additionally, policy makers may also be able to employ conditional volatility and volatility connectedness as two other measures to manage market stability in the cross-asset market dependence during highly volatile periods.

Research limitations/implications

One major take away from this academic research is since international portfolio investors are not only concerned the long-term price relationship but also the correlation structure and volatility spillover-connectedness, the conditional BEKK modeling, generalized risk connectedness analysis and nonlinear causal dependence explorations from this multi-country study can shed fresh light on the nature of market interdependence and magnitude of volatility connectedness effects in a multi-portfolio framework.

Practical implications

The hedging performance analysis for portfolio diversification and risk management indicates that industrial stocks (“pure” equities) are valuable assets that can improve the hedging performance of a well-diversified corporate equity-public real estate portfolio during crisis periods. For policymakers, the findings provide important information about the nature of causal links and predictability during the crisis and asset-market boom periods. They can then equip with this information to manage and coordinate market stability in cross corporate equity-real estate relationships effectively.

Originality/value

Although traditional research has in general reported at least a moderate degree of relationship between the two asset markets, investors' knowledge of stock-public real estate market linkage is somewhat inadequate and confine mostly to broad stocks (i.e. stocks that are exposed to public real estate influence) in a single-country context. In this paper, the authors examine the interdependence dynamics in a multi-country (multi-portfolio) context. A clear understanding their changing market relationships in a multi-country context is of crucial importance for portfolio investors, financial institutions and policy makers. Moreover, since the authors use an orthogonal stock market index, the authors allow global investors to understand the potential diversification benefits from stock markets that are beyond the public real estate market under different market conditions.

Details

Journal of European Real Estate Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-9269

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