The relationship between stock price index and exchange rate in Asian markets: A quantile regression approach

Tsai, I‐Chun

doi:10.1016/j.intfin.2012.04.005

Cited by 195 publications

(117 citation statements)

References 22 publications

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“…They concluded that exchange market volatility reduces stock market returns. In Tsai's (2012) paper, six Asian countries were analysed via quantile regression approach in order to observe the various relationships between stock and foreign exchange markets. The results indicated a negative relation between stock and foreign exchange markets, but it became more obvious when exchange rates are extremely high or low.…”

Section: Brief Theoretical Reviewmentioning

confidence: 99%

Dynamic Nexus between Exchange Rate and Stock Prices in the Major East European Economies

Živkov¹,

Njegić²,

Mirović³

2016

Prague Economic Papers

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This paper investigates the dynamic conditional correlation (DCC) between stock returns and exchange rate in four East European emerging markets. Due to persistent long memory and the presence of the asymmetric effect in all asset markets we applied DCC-FIAPARCH model. The estimated negative DCC parameters in all scrutinized countries confirmed that portfoliobalanced theory has predominance in the short run in all selected economies. DCC parameters revealed significant time-varying behaviour, especially during the major crisis periods. By embedding dummy variables in the variance equations, we came to the conclusion that global shocks affect the volatility of DCCs. Particularly, it happened during the Global Financial Crisis and European sovereign debt crisis, but the effects were not linearly equal in all countries. Complementary rolling analysis unveils how conditional volatilities of analysed assets influence DCC. The results suggested that exchange rate conditional volatility has higher influence on DCC than stock conditional volatility.

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Section: Brief Theoretical Reviewmentioning

confidence: 99%

Dynamic Nexus between Exchange Rate and Stock Prices in the Major East European Economies

Živkov¹,

Njegić²,

Mirović³

2016

Prague Economic Papers

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“…It's the Quantile Regression (QR) model, which has been previously used in the financial literature to study the value-at-risk (Engle and Manganelli, 2004;Rubia and Sanchis-Marco, 2013), the systemic risk (Adrian and Brunnermeier, 2011) the prediction of failure (Li and Miu, 2010) and also the modeling of dependence between financial variables (Bassett and Chen, 2001;Chuang et al, 2009;Baur et al, 2012;. Lee and Li, 2012;Tsai, 2012;Ciner et al, 2013;Gebka and Wohar, 2013). This approach seems to be more robust because it uses different measures of central tendency and dispersion statistics for a further detailed analysis of the relationship between variables.…”

Section: Introductionmentioning

confidence: 99%

Financial market interdependencies: A quantile regression analysis of volatility spillover

Rejeb

Arfaoui

2016

Research in International Business and Finance

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This paper investigates the degree and structure of interdependence between emerging (Asian and Latin American) and developed (USA and Japan) stock markets through the study of volatility spillovers for the period spanning from January 1, 1993 to October 13, 2010. Using both standard GARCH model and quantile regression approach, we find the evidence of significant interdependence between financial markets which may give evidence of volatility transmission existence. The volatility transmission is closely associated with geographical proximity as well as with crisis periods which confirm the presence of contagion. The analysis of upper and lower quantiles allows observing that the interdependence increases during bullish markets while decreases during bearish markets. Accordingly, the structure of interdependence is asymmetric for both Asian and Latin American emerging markets. These findings open up new insights for government policy makers and for managerial purposes.

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“…Support for stock-oriented model is found by Bartov and Bodnar (1994); Soenen and Hennigar (1988); Tai (2007); Tsai (2012); Liang et al (2013). However, it is evident from these studies that relationship between exchange and stock prices needs consensus and therefore, it should be further investigated.…”

Section: Monetary Policy Block and Stock Returnsmentioning

confidence: 95%

Stock Return Response to Monetary and Fiscal Policy Interaction in Singapore

Ali

Zaman

Ziaei³

et al. 2014

MJSS

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The relationship between stock price index and exchange rate in Asian markets: A quantile regression approach

Cited by 195 publications

References 22 publications

Dynamic Nexus between Exchange Rate and Stock Prices in the Major East European Economies

Dynamic Nexus between Exchange Rate and Stock Prices in the Major East European Economies

Financial market interdependencies: A quantile regression analysis of volatility spillover

Stock Return Response to Monetary and Fiscal Policy Interaction in Singapore

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