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Article

Tien Foo Sing and Zhuang Yao Tan

Understanding correlations between stock and direct real estate returns, which is the key factor that determines diversification benefits in a portfolio, helps formulate…

Abstract

Purpose

Understanding correlations between stock and direct real estate returns, which is the key factor that determines diversification benefits in a portfolio, helps formulate and implement better investors' asset allocation and risk management strategies. The past studies find that direct real estate returns have a low unconditionally (long‐run) correlation with the returns of equities. However, assuming that such correlation is constant throughout all periods is implausible. The purpose of this study is to test the time‐varying correlations of returns between general stocks and direct real estate.

Design/methodology/approach

This study uses the dynamic conditional correlation (DCC) model, which is a simplified version of the multivariate generalised autoregressive conditional heteroskedasticity (GARCH) model, proposed by Engle to test the time‐varying correlations between stock and direct real estate returns in six markets, which include the USA, the UK, Ireland, Australia, Hong Kong and Singapore.

Findings

The empirical results show significant time‐varying effects in the conditional covariance between stock returns and direct real estate returns. The results vary across different real estate sub‐sectors, and across different countries. It is observed that the conditional covariance increases in the boom markets, but becomes weaker in the post‐crisis periods. The authors observed significant jumps in the conditional covariance between the two asset markets in Singapore and Hong Kong in the post‐1977 Asian Financial crisis periods and in the post‐2007 US Sub‐prime crisis periods.

Originality/value

The past studies find that direct real estate returns have a low unconditionally (long‐run) correlation with the returns of equities. However, assuming that such correlation is constant throughout all periods is implausible. This study fills in the gap by using the dynamic conditional correlation models to allow for time‐varying effects in the correlations between stock and real estate returns.

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Article

Elie I. Bouri and Georges Yahchouchi

This paper aims to examine the dynamic relationship across stock market returns in Morocco, Tunisia, Egypt, Lebanon, Jordan, Kuwait, Bahrain, Qatar, United Arabic Emirates…

Abstract

Purpose

This paper aims to examine the dynamic relationship across stock market returns in Morocco, Tunisia, Egypt, Lebanon, Jordan, Kuwait, Bahrain, Qatar, United Arabic Emirates (UAE), Saudi Arabia, and Oman from June 2005 to January 2012.

Design/methodology/approach

The paper uses a multivariate model with leptokurtic distribution which allows for both return asymmetry and fat tails. The paper also derives from the model the conditional correlation between stock markets and examines the impact of the global financial crisis of 2008 on the conditional variance and correlation.

Findings

The empirical results show that the Middle East and North African (MENA) markets are interconnected by their volatilities and not by their returns. Volatility persists in each market and significant volatility spillovers from small to relatively larger markets. During the crisis, the paper finds that conditional volatilities across markets increase but then during the post-crisis period return to their pre-crisis levels. More importantly, the conditional correlation behaves differently, with a significant evidence of downwards trend in some correlations across the MENA stock markets.

Research limitations/implications

One limitation of the study relates to the relatively short-sample period which drives the empirical results.

Practical implications

The key results imply that there is still a possibility of benefits from portfolio diversification across specific MENA countries during periods of high volatility.

Originality/value

No previous study investigates the transmission of both the first and second moments of the return series across the MENA stock markets allowing for time-varying volatility and correlation and accounts for the 2008 global financial crisis to examine whether the conditional volatilities and correlations have strengthened or weakened during the crisis and afterwards.

Details

Journal of Economic Studies, vol. 41 no. 2
Type: Research Article
ISSN: 0144-3585

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Article

Dilip Kumar and S. Maheswaran

In this paper, the authors aim to investigate the return, volatility and correlation spillover effects between the crude oil market and the various Indian industrial…

Abstract

Purpose

In this paper, the authors aim to investigate the return, volatility and correlation spillover effects between the crude oil market and the various Indian industrial sectors (automobile, financial, service, energy, metal and mining, and commodities sectors) in order to investigate optimal portfolio construction and to estimate risk minimizing hedge ratios.

Design/methodology/approach

The authors compare bivariate generalized autoregressive conditional heteroskedasticity models (diagonal, constant conditional correlation and dynamic conditional correlation) with the vector autoregressive model as a conditional mean equation and the vector autoregressive moving average generalized autoregressive conditional heteroskedasticity model as a conditional variance equation with the error terms following the Student's t distribution so as to identify the model that would be appropriate for optimal portfolio construction and to estimate risk minimizing hedge ratios.

Findings

The authors’ results indicate that the dynamic conditional correlation bivariate generalized autoregressive conditional heteroskedasticity model is better able to capture time‐dynamics in comparison to other models, based on which the authors find evidence of return and volatility spillover effects from the crude oil market to the Indian industrial sectors. In addition, the authors find that the conditional correlations between the crude oil market and the Indian industrial sectors change dynamically over time and that they reach their highest values during the period of the global financial crisis (2008‐2009). The authors also estimate risk minimizing hedge ratios and oil‐stock optimal portfolio holdings.

Originality/value

This paper has empirical originality in investigating the return, volatility and correlation spillover effects from the crude oil market to the various Indian industrial sectors using BVGARCH models with the error terms assumed to follow the Student's t distribution.

Details

South Asian Journal of Global Business Research, vol. 2 no. 2
Type: Research Article
ISSN: 2045-4457

Keywords

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Article

Shrabani Saha, Anindya Sen, Christine Smith-Han and Dennis Wesselbaum

This paper aims to examine the impact of the Brexit referendum on the risk structure of financial asset prices. Co-movements are analysed using daily price returns of…

Abstract

Purpose

This paper aims to examine the impact of the Brexit referendum on the risk structure of financial asset prices. Co-movements are analysed using daily price returns of major stock and bond indices as well as commodities and exchange rates from June 2014 to June 2018. The authors used a multivariate GARCH model to study the dynamics of the conditional correlation matrix of asset returns. It was found that the conditional variances and correlations of assets spike on and after the Brexit referendum and then quickly revert to normal levels, suggesting that the effect of the referendum was transient rather than structural. The findings are of interest to investors as co-movements of financial assets can significantly impact financial portfolios and hedging strategies.

Design/methodology/approach

The authors used a multivariate GARCH model to study the dynamics of the conditional correlation matrix of asset returns.

Findings

It was found that the conditional variances and correlations of assets spike on and after the Brexit referendum and then quickly revert to normal levels, suggesting that the effect of the referendum was transient rather than structural.

Research limitations/implications

The findings are of interest to investors as co-movements of financial assets can significantly impact financial portfolios and hedging strategies.

Originality/value

To the best of the authors’ knowledge, research studying the underlying asset co-movements around Brexit does not exist.

Details

Journal of Financial Economic Policy, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1757-6385

Keywords

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Article

Antonios Antoniou, Gioia M. Pescetto and Ibrahim Stevens

The paper seeks to investigate conditional correlations and conditional volatility spillovers across international stock markets and industrial sectors from the…

Abstract

Purpose

The paper seeks to investigate conditional correlations and conditional volatility spillovers across international stock markets and industrial sectors from the perspective of the UK investor.

Design/methodology/approach

Utilizing the DCC model, the paper extracts the time‐varying conditional correlations between the UK, US and European stock markets and industrial sectors. It also uses the multivariate generalized autoregressive conditional heteroscedasticity (MVGARCH) to assess the transmission of volatility from the US and European stock markets to the UK.

Findings

The findings suggest that the UK equity market is more integrated with Europe, in terms of both aggregate stock markets and sectors. Correlations are higher during bear markets and tend to fall during periods of recovery. The sectoral analysis also provides interesting insights into the dynamics of volatility transmission across sectors.

Research limitations/implications

The results suggest that the search for a better understanding of the dynamics of correlations between markets and sectors must continue.

Practical implications

The investigation raises interesting questions for investors and regulators, as well as theoretical finance. For example, the finding that correlations increase in bear markets suggests that hedging strategies need to be revisited. The existence of sectoral idiosyncratic volatility offers further evidence that arbitrage may at times become more risky and thus limited.

Originality/value

The findings from analysing both market‐wide and sectoral integration raises the overarching question of whether studies of market integration and portfolio diversification, as well as the authorities overseeing financial stability, should be focusing on sectoral rather than market‐wide analysis.

Details

Managerial Finance, vol. 33 no. 3
Type: Research Article
ISSN: 0307-4358

Keywords

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Article

Kim Hiang Liow

The purpose of this paper is to examine weekly dynamic conditional correlations (DCC) and vector autoregressive (VAR)-based volatility spillover effects within the three…

Abstract

Purpose

The purpose of this paper is to examine weekly dynamic conditional correlations (DCC) and vector autoregressive (VAR)-based volatility spillover effects within the three Greater China (GC) public property markets, as well as across the GC property markets, three Asian emerging markets and two developed markets of the USA and Japan over the period from January 1999 through December 2013.

Design/methodology/approach

First, the author employ the DCC methodology proposed by Engle (2002) to examine the time-varying nature in return co-movements among the public property markets. Second, the author appeal to the generalized VAR methodology, variance decomposition and the generalized spillover index of Diebold and Yilmaz (2012) to investigate the volatility spillover effects across the real estate markets. Finally, the spillover framework is able to combine with recent developments in time series econometrics to provide a comprehensive analysis of the dynamic volatility co-movements regionally and globally. The author also examine whether there are volatility spillover regimes, as well as explore the relationship between the volatility spillover cycles and the correlation spillover cycles.

Findings

Results indicate moderate return co-movements and volatility spillover effects within and across the GC region. Cross-market volatility spillovers are bidirectional with the highest spillovers occur during the global financial crisis (GFC) period. Comparatively, the Chinese public property market's volatility is more exogenous and less influenced by other markets. The volatility spillover effects are subject to regime switching with two structural breaks detected for the five sub-groups of markets examined. There is evidence of significant dependence between the volatility spillover cycles across stock and public real estate, due to the presence of unobserved common shocks.

Research limitations/implications

Because international investors incorporate into their portfolio allocation not only the long-term price relationship but also the short-term market volatility interaction and return correlation structure, the results of this study can shed more light on the extent to which investors can benefit from regional and international diversification in the long run and short-term within and across the GC securitized property sector, with Asian emerging market and global developed markets of Japan and USA. Although it is beyond the scope of this paper, it would be interesting to examine how the two co-movement measures (volatility spillovers and correlation spillovers) can be combined in optimal covariance forecasting in global investing that includes stock and public real estate markets.

Originality/value

This is one of very few papers that comprehensively analyze the dynamic return correlations and conditional volatility spillover effects among the three GC public property markets, as well as with their selected emerging and developed partners over the last decade and during the GFC period, which is the main contribution of the study. The specific contribution is to characterize and measure cross-public real estate market volatility transmission in asset pricing through estimates of several conditional “volatility spillover” indices. In this case, a volatility spillover index is defined as share of total return variability in one public real estate market attributable to volatility surprises in another public real estate market.

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Article

Ajaya Kumar Panda and Swagatika Nanda

The purpose of this paper is to capture the pattern of return volatility and information spillover and the extent of conditional correlation among the stock markets of…

Abstract

Purpose

The purpose of this paper is to capture the pattern of return volatility and information spillover and the extent of conditional correlation among the stock markets of leading South American economies. It also examines the connectedness of market returns within the region.

Design/methodology/approach

The time series properties of weekly stock market returns of benchmark indices spanning from the second week of 1995 to the fourth week of December 2015 are analyzed. Using univariate auto-regressive conditional heteroscedastic, generalized auto-regressive conditional heteroscedastic, and dynamic conditional correlation multivariate GARCH model approaches, the study finds evidence of returns and volatility linkages along with the degree of connectedness among the markets.

Findings

The findings of this study are consistent with increasing market connectedness among a group of leading South American economies. Stocks exhibit relatively fewer asymmetries in conditional correlations in addition to conditional volatility; yet, the asymmetry is relatively less apparent in integrated markets. The results demonstrate that co-movements are higher toward the end of the sample period than in the early phase. The stock markets of Argentina, Brazil, Chile, and Peru are closely and strongly connected within the region followed by Colombia, whereas Venezuela is least connected with the group.

Practical implications

The implication is that foreign investors may benefit from the reduction of the risk by adding the stocks to their investment portfolio.

Originality/value

The unique features of the paper include a large sample of national stock returns with updated time series data set that reveals the time series properties and empirical evidence on volatility testing. Unlike other studies, this paper uncovers the relation between the stock markets within the same region facing the same market condition.

Details

International Journal of Managerial Finance, vol. 14 no. 2
Type: Research Article
ISSN: 1743-9132

Keywords

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Book part

Stuart Hyde, Don Bredin and Nghia Nguyen

This chapter investigates the correlation dynamics in the equity markets of 13 Asia-Pacific countries, Europe and the US using the asymmetric dynamic conditional

Abstract

This chapter investigates the correlation dynamics in the equity markets of 13 Asia-Pacific countries, Europe and the US using the asymmetric dynamic conditional correlation GARCH model (AG-DCC-GARCH) introduced by Cappiello, Engle, and Sheppard (2006). We find significant variation in correlation between markets through time. Stocks exhibit asymmetries in conditional correlations in addition to conditional volatility. Yet asymmetry is less apparent in less integrated markets. The Asian crisis acts as a structural break, with correlations increasing markedly between crisis countries during this period though the bear market in the early 2000s is a more significant event for correlations with developed markets. Our findings also provide further evidence consistent with increasing global market integration. The documented asymmetries and correlation dynamics have important implications for international portfolio diversification and asset allocation.

Details

Asia-Pacific Financial Markets: Integration, Innovation and Challenges
Type: Book
ISBN: 978-0-7623-1471-3

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Article

Daniel Perez Liston

The purpose of this paper is to quantify beta for an online gambling portfolio in the UK and investigates whether it is time-varying. It also examines the dynamic…

Abstract

Purpose

The purpose of this paper is to quantify beta for an online gambling portfolio in the UK and investigates whether it is time-varying. It also examines the dynamic correlations of the online gambling portfolio with both the market and socially responsible portfolios. In addition, this paper documents the effect of important UK gambling legislation on the betas and correlations of the online gambling portfolio.

Design/methodology/approach

This study uses static and time-varying models (e.g. rolling regressions, multivariate GARCH models) to estimate betas and correlations for a portfolio of UK online gambling stocks.

Findings

This study finds that beta for the online gambling portfolio is less than 1, indicative of defensiveness toward the market, a result that is consistent with prior literature for sin stocks. In addition, the conditional correlation between the market and online gambling portfolio is small when compared to the correlation of the market and socially responsible portfolios. Findings suggest that the adoption of the Gambling Act 2005 increases the conditional correlation between the market and online gambling portfolio and it also increases the conditional betas for the online gambling portfolio.

Research limitations/implications

This paper serves as a starting point for future research on online gambling stocks. Going forward, studies can focus on the financial performance or accounting performance of online gambling stocks.

Originality/value

This empirical investigation provides insight into the risk characteristics of publicly listed online gambling companies in the UK.

Details

International Journal of Managerial Finance, vol. 13 no. 1
Type: Research Article
ISSN: 1743-9132

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Article

Yang Hou and Steven Li

– This paper aims to investigate the volatility transmission and dynamics in China Securities Index (CSI) 300 index futures market.

Abstract

Purpose

This paper aims to investigate the volatility transmission and dynamics in China Securities Index (CSI) 300 index futures market.

Design/methodology/approach

This paper applies the bivariate Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation (DCC) Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models using high frequency data. Estimates for the bivariate GARCH models are obtained by maximising the log-likelihood of the probability density function of a conditional Student’s t distribution.

Findings

This empirical analysis yields a few interesting results: there is a one-way feedback of volatility transmission from the CSI 300 index futures to spot returns, suggesting index futures market leads the spot market; volatility response to past bad news is asymmetric for both markets; volatility can be intensified by the disequilibrium between spot and futures prices; and trading volume has significant impact on volatility for both markets. These results reveal new evidence on the informational efficiency of the CSI 300 index futures market compared to earlier studies.

Originality/value

This paper shows that the CSI 300 index futures market has improved in terms of price discovery one year after its existence compared to its early days. This is an important finding for market participants and regulators. Further, this study considers the volatility response to news, market disequilibrium and trading volume. The findings are thus useful for financial risk management.

Details

Studies in Economics and Finance, vol. 32 no. 1
Type: Research Article
ISSN: 1086-7376

Keywords

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