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Estimating time-varying conditional correlations between stock and foreign exchange markets

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  • Tastan, Hüseyin

Abstract

This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 360 (2006)
Issue (Month): 2 ()
Pages: 445-458

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Handle: RePEc:eee:phsmap:v:360:y:2006:i:2:p:445-458

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Stock prices; Exchange rates; Multivariate GARCH; News impact surface; Time-varying conditional correlations;

References

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Citations

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Cited by:
  1. Daniel Kohler, 2007. "Carry Trades: Betting Against Safe Haven," University of St. Gallen Department of Economics working paper series 2007 2007-12, Department of Economics, University of St. Gallen.
  2. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2013. "Intraday volatility spillovers between spot and futures indices: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1795-1802.
  3. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2011. "Structural changes and volatility transmission in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4317-4324.
  4. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
  5. Münnix, Michael C. & Schäfer, Rudi, 2011. "A copula approach on the dynamics of statistical dependencies in the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4251-4259.
  6. Christos Kollias & Nikolaos Mylonidis & Suzanna-Maria Paleologou, 2012. "The nexus between exchange rates and stock markets: evidence from the euro-dollar rate and composite European stock indices using rolling analysis," Journal of Economics and Finance, Springer, vol. 36(1), pages 136-147, January.
  7. Sun, Xiaolei & Li, Jianping & Tang, Ling & Wu, Dengsheng, 2012. "Identifying the risk-return tradeoff and exploring the dynamic risk exposure of country portfolio of the FSU's oil economies," Economic Modelling, Elsevier, vol. 29(6), pages 2494-2503.
  8. Chun-Pin Hsu & Chin-Wen Huang & Wan-Jiun Chiou, 2012. "Effectiveness of copula-extreme value theory in estimating value-at-risk: empirical evidence from Asian emerging markets," Review of Quantitative Finance and Accounting, Springer, vol. 39(4), pages 447-468, November.

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