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

Toyoshima, Yuki; Hamori, Shigeyuki

doi:10.1016/j.asieco.2012.08.001

Cited by 19 publications

(5 citation statements)

References 19 publications

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“…The study uses the co-integration test and finds that the Indian stock market is not integrated with other Asian markets. Further, Toyoshima and Hamori (2013) employ the asymmetric dynamic conditional correlation model to analyze the correlation between the stock markets of Japan and Singapore in the context of trade relations. They find that financial integration has advanced due to Japan-Singapore Economic Partnership Agreement.…”

Section: Linkages Between Stock Marketsmentioning

confidence: 99%

Does trade interdependency lead linkages between stock markets? A case of South Asian countries

Kumar

2019

IJOEM

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Purpose The purpose of this paper is to test the dynamic linkages among the stock markets of four South Asian countries (India, Pakistan, Bangladesh and Sri Lanka) in the backdrop of trade interdependency. Design/methodology/approach Listed indices are used to serve the proxy of stock markets of four countries for the period: January 2000–December 2018. The study uses the autoregressive distributed lag model and Granger causality techniques in multivariate frameworks while focusing on intraregional trade as an exogenous factor for testing the long- and short-run causality in the given data set, hence raising the quality of statistical inference. Findings The results highlight that India and Pakistan are net exporters to the South Asian region, while Bangladesh and Sri Lanka are net importers from the region. While testing the stock markets linkages, the expanded intraregional trade volumes (exports plus imports) have occurred with the significant cointegration of stock markets of India and Pakistan with the other stock markets in the long run. In the short run, the stock markets of India, Pakistan and Sri Lanka report bidirectional causality without having significant spillovers of intraregional trade on the stock prices. Research limitations/implications The study relies on the multivariate techniques with stock prices and regional trade share as the exogenous variables. Further the regulatory, political and economic conditions of sample countries are fundamentally different which in turn affect their degree of trade interdependency and integration between the stock markets. Practical implications Nonsignificant cointegration of the stock markets of Sri Lanka and Bangladesh highlights the possibility of portfolio diversification in the long run, while the significant bidirectional causalities between the stock markets highlight the lesser degree of portfolio diversifications in the short run. Originality/value Pioneer efforts are made to examine the dynamic linkages between the South Asian stock markets while focusing on regional trade interdependency. The results provide new insight in the dynamics of stock returns of South Asian stock markets in the backdrop of intraregional trade.

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Section: Linkages Between Stock Marketsmentioning

confidence: 99%

Does trade interdependency lead linkages between stock markets? A case of South Asian countries

Kumar

2019

IJOEM

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“…This approach generalizes the DCC model of Engle (2002) by introducing two modifications: asset-specific correlation evolution parameters and conditional asymmetries in correlation dynamics. In this paper, we adopt the following three step approach (see also Kenourgios et al (2011), Toyoshima et al (2012, Samitas and Tsakalos (2013) and Toyoshima and Hamori (2013)). In the first step, we estimate the conditional variances of gold and financial market returns using an autoregressive-asymmetric exponential generalized autoregressive conditional heteroscedasticity (AR(m) − EGARCH(p, q)) model 1 .…”

Section: Econometric Methodologymentioning

confidence: 99%

On the co-movements among gold and other financial markets: a multivariate time-varying asymmetric approach

Abed¹,

Zardoub

2019

Int Econ Econ Policy

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The analysis of time varying correlation between gold price and financial market in the context of international investments has been well researched in the literature in last few years. In this paper we study the interdependence of three financial markets and the gold price. We adopt a multivariate asymmetric dynamic conditional correlation EGARCH framework, during the period spanning from January 5, 1995 until May 30, 2017. The empirical results suggest asymmetric responses in correlations among gold market and financial market. We find that asymmetric dynamic correlations exhibit substantial time variation even in similar market tensions for same pairs of assets. Our findings imply that investors and fund managers should take into account the asymmetric dependence structure, which depends on the upside or downside of the market.

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“…This phenomenon is called asymmetric correlations between returns and has attracted lots of attention since discovered. Besides, the evidence for asymmetric correlations also comes from international markets, as shown in Longin and Solnik (1995, 2001), Ang and Bekaert (2002), Campbell et al (2002), Okimoto (2008), and Toyoshima and Hamori (2013). They found that correlations between market returns in different countries were higher during bear market periods.…”

Section: Introductionmentioning

confidence: 94%

Asymmetric Correlations in Predicting Portfolio Returns*

et al. 2019

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Rigorous statistical tests have been designed to detect the existence of asymmetric correlations. However, these tests can hardly further facilitate future investment or risk management because asymmetric correlations are time‐varying and difficult to predict. In this paper, we construct a unified state‐space model, which not only measures in‐sample asymmetric correlations, but also exploit out‐of‐sample asymmetric correlations in the context of predicting portfolio returns. First, we regard time‐varying correlation between market returns and portfolio returns as a state variable and model it as an AR(1) process. Then, we measure future asymmetric correlations based on correlation coefficients between two unpredictable components in market returns and correlation, respectively. Third, we clarify the intuition, calculate asymmetric correlations for two portfolio sets and estimate the economic value of applying our model in asset allocation. Finally, we try to search for potential variables that can explain future asymmetric correlations. The results show that market‐wide liquidity, variance, earning price ratio, and investor sentiment can partially explain the asymmetry correlation phenomenon.

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

Cited by 19 publications

References 19 publications

Does trade interdependency lead linkages between stock markets? A case of South Asian countries

Does trade interdependency lead linkages between stock markets? A case of South Asian countries

On the co-movements among gold and other financial markets: a multivariate time-varying asymmetric approach

Asymmetric Correlations in Predicting Portfolio Returns*

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