Stock Market Correlations Research Articles

Stock market correlations during the financial crisis of 2008–2009: Evidence from 50 equity markets

Using data from 50 equity markets we examine conditional and unconditional correlations around two major banking events during the financial crisis of 2008–09. To measure the value of covariance information on the augmented DCC model used in the study, a portfolio in-sample estimation is performed. We show that by taking into account the change in the level of variance in high volatility periods, the estimates of the conditional covariance are more efficient in capturing the dynamics of the stock markets variance. Furthermore, in a two-asset allocation framework, the model consistently generates relatively low portfolio variances, implying substantial benefits in portfolio diversification.

International diversification during the financial crisis: A blessing for equity investors?

This paper empirically investigates international equity investors' foreign portfolios before and during the financial crisis by estimating a gravity model for 22 source and 42 destination countries during 2001–2009. The results show a significant negative relationship between foreign equity holdings and stock market correlations during the financial crisis, while there is no relationship before the crisis. When distinguishing between active and passive rebalancing, the results clearly indicate a significantly negative relationship between active rebalancing and correlations during the crisis. These findings hold as well at the individual country level when allowing for source country specific coefficients. An analysis from the perspective of each source country's representative investor, who optimizes mean-variance utility, shows that active rebalancing provides sizeable utility gains during the crisis. Finally, there is even a significantly negative relationship between future correlations and active rebalancing since 2007, suggesting that prior to the crisis investors already repositioned their country weights to markets with lower correlation during 2008–2009.

International Diversification During the Financial Crisis: A Blessing for Equity Investors?

This paper empirically investigates international equity investors’ foreign portfolios before and during the financial crisis by estimating a gravity model for 22 source and 42 destination countries. The results show that international stock market diversification provides large gains during the financial crisis. This is remarkable because of large stock market correlations. During the financial crisis investors have larger positions in foreign stock markets which are relatively less correlated with the domestic market. However, this relationship is not present before the crisis. Results at the country level show that aggregate portfolio volatility is lower and returns are higher for investors from low home biased source countries during the financial crisis. This result implies that global equity diversification has an important positive effect on stabilizing a country’s aggregate equity wealth, especially during periods of stock market stress.

Dynamic Analysis of Time-Varying Correlations and Cointegration Relationship between Australia and Frontier Equity Markets

This paper aims to demonstrate to what extent Australian stock market is correlated with those of eighteen frontier markets of five different regions. We also investigate the long-run relationship between these markets. The empirical analysis is carried out on the weekly closing price data of broad market indices of respective stock markets. Empirical results of AGDCC GARCH model reveal that the correlations of Australian stock market with frontier markets are changing over time. Results show that Australian stock market has weak correlations with all the frontier markets. Further, our analysis confirms that the affect of GFC on the correlations of Australia and frontier markets are limited to only few markets where correlations increased to some extent. Results also demonstrate that the GFC has no influence on the correlations of Australia and frontier markets of Asia. The cointegration test results display that there is no evidence of long-run relationship between Australia and frontier markets. Similarly, Granger causality test results show that Australian stock market drives some of frontier markets and no evidence of reverse causality from these markets to Australia. The causality results also show that the only Trinidad & Tobago market influences the Australian stock market. Empirical findings of our study suggest that Australian stock market is weakly correlated with those of frontier markets. Therefore, our study findings suggest that the global investors can diversify their portfolios into these frontier markets for gaining higher risk-adjusted returns. Our study also contributes to the body of knowledge by addressing the issue of stock markets linkage between developed and frontier markets and also the GFC.

On the globalization of stock markets: An application of Vector Error Correction Model, Mutual Information and Singular Spectrum Analysis to the G7 countries

This paper analyzes stock market relationships among the G7 countries between 1973 and 2009 using three different approaches: (i) a linear approach based on cointegration, Vector Error Correction (VECM) and Granger Causality; (ii) a nonlinear approach based on Mutual Information and the Global Correlation Coefficient; and (iii) a nonlinear approach based on Singular Spectrum Analysis (SSA). While the cointegration tests are based on regression models and capture linearities in the data, Mutual Information and Singular Spectrum Analysis capture nonlinear relationships in a non-parametric way. The framework of this paper is based on the notion of market integration and uses stock market correlations and linkages both in price levels and returns. The main results show that significant co-movements occur among most of the G7 countries over the period analyzed and that Mutual Information and the Global Correlation Coefficient actually seem to provide more information about the market relationships than the Vector Error Correction Model and Granger Causality. However, unlike the latter, the direction of causality is difficult to distinguish in Mutual Information and the Global Correlation Coefficient. In this respect, the nonlinear Singular Spectrum Analysis technique displays several advantages, since it enabled us to capture nonlinear causality in both directions, while Granger Causality only captures causality in a linear way. The results also show that stock markets are closely linked both in terms of price levels and returns (as well as lagged returns) over the 36 years analyzed.

Multi‐scale relation analysis of power law distribution and correlation in the Chinese stock market

PurposeThe purpose of this paper is to reveal the multi‐scale relation between power law distribution and correlation of stock returns and to figure out the determinants underlying capital markets.Design/methodology/approachThe multi‐scale relation between power law distribution and correlation is investigated by comparing the original series with the special series. The eliminating intraday trend series approach developed by Liuet al.is utilized to analyze the effects of power law decay change on correlation properties, and shuffling series originated by Viswanathanet al.for the impacts of special type of correlation on power‐law distribution.FindingsIt is found that the accelerating decay of power law has an insignificant effect on correlation properties of returns and the empirical results indicate that time scale may also be an important factor maintaining power law property of returns besides correlation. When time scale is under critical point, the effects of correlation are crucial, and the correlation of nonlinear long‐range presents the strongest influence. However, for time scale beyond critical point, the impact of correlation begins to diminish or even finally disappear and then the power law property shows complete dependence on time scale.Research limitations/implicationsThe 5‐min high frequency data of the Shanghai market as the empirical benchmark is insufficient to depict the relation over the entire time scale in the Chinese stock market.Practical implicationsThe paper identifies the determinants of market dynamics to apply them to risk management through analysis of multi‐scale relations, and supports endeavors to introduce time parameter into further risk measures and control.Originality/valueThe paper provides the empirical evidence that time scale is one of the key determinants of market dynamics by analyzing the multi‐scale relation between power law distribution and correlation.

A Dynamic Analysis of the Integration of the Australian Stock Market with Those of Its Trading Partners

This paper aims to investigate does foreign trade matter for the stock markets integration by segmenting Australian trade partners into three groups based on bilateral trade relations. We further explore time-varying correlations of pairwise stock market returns by employing asymmetric generalized DCC-GARCH models. Study uses weekly price index data from September 3rd, 1999 to May 4th, 2012. Empirical findings from cointegration tests show the presence of long-run relationship between Australia and its major trading partners in the pre-crisis and post-crisis (includes crisis-period). We also found the long-run relationship between Australia and its medium trading partners only in the post-crisis period. Granger non-causality test show the presence of bidirectional relationship between Australia and Singapore. Study also finds unidirectional relationship from Australia to China, Korea and the Philippines and from the USA, the UK and South Africa to Australia. Results from AGDCC-GARCH evidence that correlations are time-varying and increase significantly during the crisis period and revert close to their initial levels after the crisis. Further, we identified that the time-varying correlations of Australia with the USA, Korea and the Philippines are more volatile. Our findings confirm that foreign trade intensity matters for the stock market integration. The absence of stable long-run relationship may provide incentive for investors to include these markets into their portfolio selection process to exploit potential diversification benefits.

Asymmetric dynamics in stock market correlations: Evidence from Japan and Singapore

This paper uses the asymmetric dynamic conditional correlation model developed by Cappiello et al. (2006) to analyze the correlation between the Japanese and Singaporean stock markets and makes two principal findings. First, it finds that financial integration has advanced because of the Japan–Singapore Economic Partnership Agreement, thereby strengthening the bidirectional relationship between Japan and Singapore. Second, it demonstrates empirically that the weight of Asian stocks in portfolios within the Asian region has increased since the global financial crisis, again strengthening the relationships among Asian region economies.

Do sovereign credit ratings influence regional stock and bond market interdependencies in emerging countries?

We investigate the permanent and transitory effects of sovereign credit ratings on time-varying stock and bond market correlations with their respective regional markets for a sample of up to nineteen emerging countries over the period from 1 January 1994 to 1 July 2007. We find that stock and bond market co-movements within a region respond heterogeneously to sovereign ratings information. Sovereign ratings and outlooks tend to be positively related to regional stock market co-movements suggesting that there are positive rating spillover effects whereby upgrades provide common benefits for neighboring countries in the region, however downgrades would lead to investors shifting funds from the downgraded market into the surrounding region. In contrast, sovereign rating and outlooks tend to be negatively related to regional bond market co-movements suggesting the existence of contagion during periods of ratings and outlook downgrades (negative rating spillover effects). We find the negative influence is concentrated in the countries that have higher foreign currency debt ratings than the regional average.

Dynamics of Intraday Serial Correlation in China's Stock Market

In this article, we implement the Variance Ratio test to study on the intraday serial correlation of Shenzhen component index return series. The empirical research indicates significant positive serial correlation in China's stock market. For a better understanding of the dynamics of intraday serial correlation in China's stock market, we first investigate the presence of autocorrelation mode of serial correlation. Then, we construct the VR-HAR-RV and VR-HAR-RV-CJ models to explore the links between serial correlation and volatility. We find both the VR-HAR-RV and VR-HAR-RV-CJ models can partially explain the links between serial correlation and volatility, but the VR-HAR-RV-CJ model is more powerful than the VR-HAR-RV model.

The roles of news and volatility in stock market correlations during the global financial crisis

The global financial crisis has again brought the interdependencies of international financial markets to the fore, particularly during times of financial crises. This paper explores the relative roles of news and volatility in explaining the changes in correlations between national stock markets during the global financial crisis. Our results show that the majority of the correlations are more strongly explained by volatility rather than news. However as the global financial crisis evolves the relative role of news grows in importance.

A gravity analysis of international stock market linkages

The last decade has witnessed a marked improvement in information technology. Such an improvement has reduced the information cost for market participants. Thus, whether the influence of geographic factors on international financial linkage is still significant nowadays is an important question yet to be addressed. This article develops a gravity model of international financial linkages. Using the panel data of bilateral cross-country stock market correlations of 23 countries, it is found that the correlations are negatively associated with the Great Circular Distance (GCD) between the financial centres of these countries and positively associated with the duration of overlapping trading hours among stock exchanges and the colonial links between countries. However, whether the countries share a common border or language does not affect the stock market correlations.

Micro Architecture of the Financial Market Based on the Scale-Free Network View

Traditional finance emphasizes particularly on the equilibrium of the whole markets, while ignoring the action of individuals, especially the interaction between the individual and environment. The 2007-2010 financial crisis highlights the importance of the systemic risk and relative micro architecture research for financial market.This article is mainly focused on the micro architecture analysis of the financial market based on complex network view, we will use the stock market correlation coefficient matrix build the financial network, then demonstrate it's a scale-free network and check the financial network characteristics and the dynamic evolution path. By calculation the Cluster Coefficient and the eigenvalues of the Laplacian matrix, we demonstrate a method to forecast the market trends change.Then we will based on the financial network characteristics to build automatic trading strategy and also give some control strategy for public finance.

Stock market correlations between China and its emerging market neighbors

We examine interlinkages of stock return behavior for China and three emerging market neighbors from the Asia Pacific region from November 1993 to July 2008. Results are based on a VAR model. Impulse responses and vector decomposition of VAR are also utilized. Evidence suggests that the aggregate markets are mostly not interrelated. However, we observe relations between China and the other markets when foreign investor returns are specifically accounted for. In addition, a shock originating in China is significantly felt in the other equity markets. Stock market characteristics and macroeconomic conditions of these countries may help explain the observed relations.

Sector Analysis And Portfolio Optimisation: The Indian Experience

With changing global financial environment and emergence of new economic powers in recent decades, diversification of investment portfolios at country and sector levels assumed additional significance. Optimum portfolio selection within a capital market is primarily based on the best risk-return trade-off among the industry sectors. Literature suggests that much of market volatility can be attributed to substantial increase in sector specific and sub-sector specific risks. This research has estimated the dynamics of correlations of stock market returns between industry sectors in India using Asymmetric DCC GARCH model and tested efficient portfolios that generates returns above the market average. Analysis of daily and monthly market data for the period April 1997 to April 2007 on a sample of 10 industry sectors selected randomly indicates that investors can substantially improve their reward to risk as compared with the market returns. Major contributions of this research are two fold. It used a computationally efficient model for estimating correlations that can incorporate the changes in correlations over time and it applied the model for the Indian market where research is extremely inadequate.

A Sentiment-Based Explanation of the Forward Premium Puzzle

This paper presents a sentiment-based explanation of the forward premium puzzle. Agents over- or underestimate the growth rate of the economy. All else equal, when perceived domestic growth is higher than perceived foreign growth, the domestic interest rate is higher than the foreign interest rate. At the same time, an econometrician would expect an increase in the home currency value. Together, the model with investor misperception can account for the forward premium puzzle.> ; In addition, it helps explain the low correlation of consumption growth differentials and exchange rate growth and the high stock market correlation across countries, despite a low correlation of fundamentals. Finally, this paper provides direct empirical evidence supporting the mechanism in the sentiment-based explanation.

Measuring the effects of geographical distance on stock market correlation

Recent studies suggest that the correlation of stock returns increases with decreasing geographical distance. However, there is some debate on the appropriate methodology for measuring the effects of distance on correlation. We modify a regression approach suggested in the literature and complement it with an approach from spatial statistics, the mark correlation function. For the stocks contained in the S&P 500 that we examine, both approaches lead to similar results. Contrary to previous studies we find that beyond 50 miles geographical proximity is irrelevant for stock return correlations. For distances below 50 miles, we can show that the magnitude of local correlations varies with investor sentiment.

Free Flows, Limited Diversification: Openness and the Fall and Rise of Stock Market Correlations, 1890–2001

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The Index cohesive effect on stock market correlations

We present empirical examination and reassessment of the functional role of the market Index, using datasets of stock returns for eight years, by analyzing and comparing the results for two very different markets: 1) the New York Stock Exchange (NYSE), representing a large, mature market, and 2) the Tel Aviv Stock Exchange (TASE), representing a small, young market. Our method includes special collective (holographic) analysis of stock-Index correlations, of nested stock correlations (including the Index as an additional ghost stock) and of bare stock correlations (after subtraction of the Index return from the stocks returns). Our findings verify and strongly substantiate the assumed functional role of the index in the financial system as a cohesive force between stocks, i.e., the correlations between stocks are largely due to the strong correlation between each stock and the Index (the adhesive effect), rather than inter-stock dependencies. The Index adhesive and cohesive effects on the market correlations in the two markets are presented and compared in a reduced 3-D principal component space of the correlation matrices (holographic presentation). The results provide new insights into the interplay between an index and its constituent stocks in TASE-like versus NYSE-like markets.

STOCK MARKET INTEGRATION FOR THE TRANSITION ECONOMIES: TIME‐VARYING CONDITIONAL CORRELATION APPROACH

In this paper, we investigate the extent to which the three emerging Central Eastern European stock markets have become integrated with the aggregate eurozone market over the sample period from 1994 to 2006 by utilizing the dynamic conditional correlation. We find a higher level of the stock market correlation during the period after the Asian and Russian crises and also during the post‐entry period to the European Union. It is found that financial market integration seems to be a largely self‐fuelling process, depending on existing levels of financial sector development for the Czech Republic and Hungary.