Search results

Although stock price co-movement has been examined extensively, its causes are not well understood. Using a decomposition method, we extract three information components from the turnover rate: market information, firm-specific information, and investors' opinion divergence. We find that market information strengthens stock price co-movement, whereas firm-specific information weakens it. Moreover, our analysis shows that divergence of investors' opinion increases stock price variations but weakens price co-movement.

The objective of the present study is to examine how domestic and foreign exchange traded funds (ETFs) tracking Indian equities affect the return correlations of their underlying constituents. Further, this study investigates how these effects vary between periods of turmoil and calmness in the financial markets.

The study is based on quarterly data for stocks comprising the CNX (CRISIL NSE Indices) Nifty 50 Index from 2009Q1 to 2019Q4. The data on holdings of 45 domestic and 196 foreign ETFs in the sample stocks were obtained from Thomson Reuters’ Eikon. The paper employs a panel-regression methodology with stock and time fixed effects and robust standard errors.

This study documents that irrespective of the market conditions, foreign ETFs, particularly those from Asia–Pacific and European regions tend to exacerbate co-movement. Conversely, domestic ETFs lower co-movement in stable markets but during periods of turbulence a jump in return correlations is observed.

The results have important implications for ETF investors as well as market regulators because an increase in co-movement would reduce the diversification benefits of ETFs, thereby nullifying the biggest advantage that ETFs have to offer.

The literature on the economic impact of ETFs is highly skewed with the majority of the studies focusing on developed markets. To the best of the authors’ knowledge, this study is the first one to empirically examine the impact of ETFs on the return co-movement of an emerging market. Furthermore, the study is unique as the authors investigate how the effects of ETFs vary in turbulent and tranquil markets.

This paper aims to investigate empirically the linkages between stock and commodity futures markets.

It involves the application of a flexible copula approach to weekly total returns from the S&P 500 index and from three commodity sub-indices (agriculture, metals and energy) from 1995 to 2017.

Co-movement is by no means frequent and symmetric. It was predominantly zero before the last financial crisis, and since then, it is positive and asymmetric. The pattern of asymmetry is consistent with transmission of shocks under extreme negative shocks only. Recently, total returns of commodity futures are very poor. At the same time, commodity futures markets move in step (out of step) with stock markets when the latter plunge (rise), pointing to limited diversification benefits. These appear to justify the concerns of investors and researchers whether including commodities in a portfolio of assets is still a prudent investment strategy.

It is the only manuscript that combines a flexible copula approach and co-movement measurement along both the positive and negative diagonals. The findings are in sharp contrast with those reported by Delatte and Lopez (2013) and are very important for portfolio management.

This study aims to observe the extent of asset diversification benefits in the Association of Southeast Asian Nations (ASEAN)-5 market by examining the effect of financial integration (FI) and financial development (FD) on domestic stock–bond co-movements, SBcorr.

The dynamic conditional correlation - multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) technique is adopted to construct FI and stock−bond co-movement variables. Then, the study uses static panel data analysis to examine the effect of FI on stock−bond co-movements.

FI does not provide asset diversification benefits due to high country risks in ASEAN-5. However, when FI is moderated by FD, FI × FD, the study shows that FI × FD provides higher asset diversification benefits in ASEAN-5.

This study shows the importance of incorporating the level of FD when assessing the effect of FI on stock–bond co-movements in ASEAN-5. In the presence of FI, a well-diversified investor should always consider the state of FD, which will show a better representation of asset diversification strategy in the emerging markets. Additionally, policymakers of ASEAN-5 countries should prioritise enhancing their financial system to attract more investment into the countries.

The purpose of this paper is to investigate the cross-spectra of stock, real estate and bond of ten selected Asian economies in the pre- and post-global financial crisis periods to detect whether there is greater cyclical co-movement post-financial crisis, and whether any observed increased co-movement measures the outcomes of contagion or integration.

Co-spectral approach is the proper econometric tool to deliver economic insight for this research.

Results indicate that Asian stock markets, and to a lesser degree, bond and real estate markets are more correlated post-financial crisis. Similarly, Asian financial markets have experienced increased co-movements with the US financial markets post-financial crisis. Moreover, these observed increased co-movements measure the outcomes of contagion in some cases of within-asset and cross-asset classes, as well as for some cross-US-Asian asset factor relationships along the high-frequency components of between two and four weeks. The stock markets are the most contagious, followed by the real estate markets and bond markets.

The results provide short-term investors with additional co-movement information at higher frequencies in order to identify short-term fluctuations of different asset classes. The empirical study also underscores the role of Asian real estate in investment portfolios in a mixed real estate, stock and bond context from a frequency domain perspective.

The practical implication of this research is that benefits to investors from international diversification may not be as great during the present time compared to previous periods because financial/asset market movements have become more correlated. However, it does not imply the complete absence of diversification benefits. This is because although cyclical correlations increase in the short run, many of the values are still between low and moderate range, indicating that some diversification benefits may still be realized.

In advancing the body of knowledge in international financial markets, this research is probably the first study to consider a multi-asset class portfolio context that includes stock, real estate and bond across the ten Asian economies and the USA in a single study. The frequency domain analysis conducted in this paper adds to the understanding of real estate, stock and bond market co-movement, integration and contagion dynamics, as well as the Asian cross-asset factor and US-Asian asset factor relationships in global mixed-investing environment.

Using daily returns from 1980‐2006, we find a significant contemporaneous association between all European Union (EU) equity markets and Germany. There is, however, no significant indication that the German stock market leads or lags the movements in the other EU stock markets. A higher share of imports by Germany from other EU countries, as well as fluctuations and increased volatility in the exchange rate, have negative effects on stock market co‐movements. Conversely, the difference in equity market capitalization with Germany, the greater the foreign direct investment by Germany, and the fact of belonging to the eurozone all contribute to greater stock market co‐movement.

This paper aims to attempt to capture the co-movement of the Indian equity market with some of the major economic giants such as the USA, Europe, Japan and China after the occurrence of global financial crisis in a multivariate framework. Apart from these cross-country co-movements, the study also captures an intertemporal risk-return relationship in the Indian equity market, considering the covariance of the Indian equity market with the other countries as well.

To account for dynamic correlation coefficients and risk-return dynamics, vector autoregressive (1) dynamic conditional correlation–asymmetric generalized autoregressive conditional heteroskedastic model in a multivariate framework and exponential generalized autoregressive conditional heteroskedastic model in mean with covariances as explanatory variables are used. For an in-depth analysis, Markov regime switching model and optimal hedging ratios and weights are also computed. The span of data ranges from August 10, 2010 to August 7, 2015, especially after the global financial crisis.

The Indian equity market is not completely decoupled from mature markets as well as emerging market (China), but the time-varying correlation coefficients are on a downward spree after the global financial crisis, except for the US market. The Indian and Chinese equity markets witness a highest level of correlation with each other, followed by the European, US and Japanese markets. Both the optimal portfolio hedge ratios and portfolio weights with two asset classes point out toward portfolio risk minimization through the combination of the Indian and US equity market stocks from a US investor viewpoint. A negative co-movement between the Indian and US market increases the conditional expected returns in the Indian equity market. There is an insignificant but a negative relationship between the expected risk and returns.

The study provides an insight to the international as well as domestic investors and supports the construction of cross-country portfolios and risk management especially after the occurrence of global financial crisis.

The present study contributes to the literature in three senses. First, the period relates to the events after the global financial crisis (2007-2009). Second, the study examines the co-movement of the Indian equity market with four major economic giants such as the USA, Europe, Japan and China in a multivariate framework. These economic giants are excessively following the easy money policies aftermath the financial crisis so as to wriggle out of deflationary phases. Finally, the study captures risk-return relationship in the Indian equity market, considering its covariance with the international markets.

The aim of this paper is threefold: (1) to develop a new measure of investor sentiment rational (ISR) of developing countries by applying principal component analysis (PCA), (2) to investigate co-movements between the ten developing stock markets, the sentiment investor's, exchange rates and geopolitical risk (GPR) during Russian invasion of Ukraine in 2022, (3) to explore the key factors that might affect exchange market and capital market before and mainly during Russia–Ukraine war period.

The wavelet approach and the multivariate wavelet coherence (MWC) are applied to detect the co-movements on daily data from August 2019 to December 2022. Value-at-risk (VaR) and conditional value-at-risk (CVaR) are used to assess the systemic risks of exchange rate market and stock market return in the developing market.

Results of this study reveal (1) strong interdependence between GPR, investor sentiment rational (ISR), stock market index and exchange rate in short- and long-terms in most countries, as inferred from (WTC) analysis. (2) There is evidence of strong short-term co-movements between ISR and exchange rates, with ISR leading. (3) Multivariate coherency shows strong contributions of ISR and GPR index to stock market index and exchange rate returns. The findings signal the attractiveness of the Vietnamese dong, Malaysian ringgits and Tunisian dinar as a hedge for currency portfolios against GPR. The authors detect a positive connectedness in the short term between all pairs of the variables analyzed in most countries. (4) Both foreign exchange and equity markets are exposed to higher levels of systemic risk in the period of the Russian invasion of Ukraine.

This study provides information that supports investors, regulators and executive managers in developing countries. The impact of sentiment investor with GPR intensified the co-movements of stocks market and exchange market during 2021–2022, which overlaps with period of the Russian invasion of Ukraine.

The purpose of this paper is to empirically investigate the volatility spillover between the Chinese stock market, investor’s sentiment and oil market, specifically during the 2014‒2016 turmoil period.

This study used the daily and monthly China market price index, oil-price index and composite index of Chinese investor’s sentiment. The authors first use the DCC GARCH model in order to study the correlation between variables. Second, the authors use a continuous wavelet decomposition technique so as to capture both time- and frequency-varying features of co-movement variables. Finally, the authors examine the spillover effects by estimating the BEKK GARCH model.

The wavelet coherency results indicate a substantial co-movement between oil and Chinese stock markets in the periods of high volatility. BEKK GARCH model outcomes confirm this relation and report the noteworthy bidirectional transmission of volatility between oil market shocks and the Chinese investor’s sentiment, chiefly in the crisis period. These results support the behavioral theory of contagion and highlight that the Chinese investor’s sentiment is a channel through which shocks are transmitted between the oil and Chinese equity markets. Thus, these results are important for Chinese authorities that should monitor the investor’s sentiment to better control the interaction between financial and real markets.

This study makes three major contributions to the existing literature. First, it pays attention to the recent 2015 Chinese stock market bumble. Second, it has gone some way toward enhancing our understanding of the volatility spillover between the investor’s sentiment, investor’s sentiment variation, oil prices and stock market returns (variables of interest) during oil and stock market crises. Third, it uses the continuous wavelet decomposition technique since it reveals the linkage between variables of interest at different time horizons.

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.

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.

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.

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.

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.