IDEAS home Printed from https://ideas.repec.org/a/fau/fauart/v64y2014i4p296-311.html
   My bibliography  Save this article

Effectiveness of Portfolio Diversification and the Dynamic Relationship between Stock and Currency Markets in the Emerging Eastern European and Russian Markets

Author

Listed:
  • Yen-Hsien Lee

    (Department of Finance, Chung Yuan Christian University, Chung Li, Taiwan)

  • Hao Fang

    (Department of Assets and Property Management, Hwa Hsia Institute of Technology, Taipei, Taiwan)

  • Wei-Fan SU

    (Department of Finance, Chung Yuan Christian University, Chung Li, Taiwan)

Abstract

This study investigates volatility spillovers and the dynamic relationship between the stock and currency markets in the Czech Republic, Poland, Hungary and Russia using four multivariate GARCH models. We analyze the optimal weights and the effectiveness of diversification for stock-currency portfolio holdings with respect to the following points. First, the empirical results show that the dynamic conditional correlation model with spillovers (DCC-S) generally yields the most effective diversification model, which implies that DCC-S can significantly improve the effectiveness of diversification. Second, we also provide the results of a Value at Risk analysis to determine the amount of capital reserves that investors should set aside to cover potential extreme losses when investing in a currency-stock portfolio. Third, our consideration of the time-varying weighting trend finds that weighting generally increases when economic events occur, except for in Russia, whose economic policies are considered to be unique. We find significant dynamic correlation in all of the countries considered in our analysis. Finally, we apply the unit root test for both time-varying correlations and weightings and find that the variables are stationary at their levels.

Suggested Citation

  • Yen-Hsien Lee & Hao Fang & Wei-Fan SU, 2014. "Effectiveness of Portfolio Diversification and the Dynamic Relationship between Stock and Currency Markets in the Emerging Eastern European and Russian Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 296-311, September.
  • Handle: RePEc:fau:fauart:v:64:y:2014:i:4:p:296-311
    as

    Download full text from publisher

    File URL: http://journal.fsv.cuni.cz/storage/1303_296-311_-_lee.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jian Yang & Yinggang Zhou & Wai Leung, 2012. "Asymmetric Correlation and Volatility Dynamics among Stock, Bond, and Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 491-521, August.
    2. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
    3. Yang, Yung-Lieh & Chang, Chia-Lin, 2008. "A double-threshold GARCH model of stock market and currency shocks on stock returns," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 458-474.
    4. Chang, Chia-Lin & Khamkaew, Thanchanok & McAleer, Michael & Tansuchat, Roengchai, 2011. "Modelling conditional correlations in the volatility of Asian rubber spot and futures returns," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1482-1490.
    5. John Cotter & Simon Stevenson, 2006. "Multivariate Modeling of Daily REIT Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 32(3), pages 305-325, May.
    6. Fan, Ying & Zhang, Yue-Jun & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach," Energy Economics, Elsevier, vol. 30(6), pages 3156-3171, November.
    7. Milunovich, George & Thorp, Susan, 2006. "Valuing volatility spillovers," Global Finance Journal, Elsevier, vol. 17(1), pages 1-22, September.
    8. El Hedi Arouri, Mohamed & Jouini, Jamel & Nguyen, Duc Khuong, 2011. "Volatility spillovers between oil prices and stock sector returns: Implications for portfolio management," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1387-1405.
    9. Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.
    10. Elena Fedorova & Kashif Saleem, 2010. "Volatility Spillovers between Stock and Currency Markets: Evidence from Emerging Eastern Europe," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(6), pages 519-533, December.
    11. Lucía de las Nieves Morales, 2008. "Volatility Spillovers between Equity and Currency Markets: Evidence from Major Latin American Countries," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 45(132), pages 185-215.
    12. Bill B. Francis & Iftekhar Hasan & Delroy M. Hunter, 2006. "Dynamic Relations between International Equity and Currency Markets: The Role of Currency Order Flow," The Journal of Business, University of Chicago Press, vol. 79(1), pages 219-258, January.
    13. Bradford Case & Yawei Yang & Yildiray Yildirim, 2012. "Dynamic Correlations Among Asset Classes: REIT and Stock Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 44(3), pages 298-318, April.
    14. Hang Chan, Ngai & Deng, Shi-Jie & Peng, Liang & Xia, Zhendong, 2007. "Interval estimation of value-at-risk based on GARCH models with heavy-tailed innovations," Journal of Econometrics, Elsevier, vol. 137(2), pages 556-576, April.
    15. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    16. Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
    17. Tse, Y. K., 2000. "A test for constant correlations in a multivariate GARCH model," Journal of Econometrics, Elsevier, vol. 98(1), pages 107-127, September.
    18. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    19. Sheng-Yung Yang & Shuh-Chyi Doong, 2004. "Price and Volatility Spillovers between Stock Prices and Exchange Rates: Empirical Evidence from the G-7 Countries," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 3(2), pages 139-153, August.
    20. Christos A. Grambovas, 2003. "Exchange Rate Volatility and Equity Markets," Eastern European Economics, Taylor & Francis Journals, vol. 41(5), pages 24-48, January.
    21. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    22. Ülkü, Numan & Demirci, Ebru, 2012. "Joint dynamics of foreign exchange and stock markets in emerging Europe," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 55-86.
    23. Tai, Chu-Sheng, 2007. "Market integration and contagion: Evidence from Asian emerging stock and foreign exchange markets," Emerging Markets Review, Elsevier, vol. 8(4), pages 264-283, December.
    24. Kang, Sang Hoon & Kang, Sang-Mok & Yoon, Seong-Min, 2009. "Forecasting volatility of crude oil markets," Energy Economics, Elsevier, vol. 31(1), pages 119-125, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dejan Živkov & Slavica Manić & Jelena Kovačević & Željana Trbović, 2022. "Assessing volatility transmission between Brent and stocks in the major global oil producers and consumers – the multiscale robust quantile regression," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 21(1), pages 67-93, January.
    2. Harald Schmidbauer & Angi Rösch & Erhan Uluceviz & Narod Erkol, 2016. "The Russian Stock Market during the Ukrainian Crisis: A Network Perspective," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 478-509, December.
    3. Simona Moagăr-Poladian & Dorina Clichici & Cristian-Valeriu Stanciu, 2019. "The Comovement of Exchange Rates and Stock Markets in Central and Eastern Europe," Sustainability, MDPI, vol. 11(14), pages 1-22, July.
    4. Dejan Živkov & Boris Kuzman & Jonel Subić, 2020. "What Bayesian quantiles can tell about volatility transmission between the major agricultural futures?," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(5), pages 215-225.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yen-Hsien Lee, 2014. "An international analysis of REITs and stock portfolio management based on dynamic conditional correlation models," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(2), pages 165-180, May.
    2. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    3. El Hedi Arouri, Mohamed & Lahiani, Amine & Nguyen, Duc Khuong, 2015. "World gold prices and stock returns in China: Insights for hedging and diversification strategies," Economic Modelling, Elsevier, vol. 44(C), pages 273-282.
    4. Laura Wallenius & Elena Fedorova & Sheraz Ahmed & Mikael Collan, . "Surprise Effect of Euro Area Macroeconomic Announcements on CIVETS Stock Markets," Prague Economic Papers, University of Economics, Prague, vol. 0, pages 1-17.
    5. Muhammad Irfan Malik & Abdul Rashid, 2017. "Return And Volatility Spillover Between Sectoral Stock And Oil Price: Evidence From Pakistan Stock Exchange," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 1-22, June.
    6. Syriopoulos, Theodore & Makram, Beljid & Boubaker, Adel, 2015. "Stock market volatility spillovers and portfolio hedging: BRICS and the financial crisis," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 7-18.
    7. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2012. "Asymmetric effects and long memory in dynamic volatility relationships between stock returns and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 738-757.
    8. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    9. Laura Wallenius & Elena Fedorova & Sheraz Ahmed & Mikael Collan, 2017. "Surprise Effect of Euro Area Macroeconomic Announcements on CIVETS Stock Markets," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(1), pages 55-71.
    10. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    11. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    12. Zhou, Jian, 2014. "Modeling conditional covariance for mixed-asset portfolios," Economic Modelling, Elsevier, vol. 40(C), pages 242-249.
    13. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    14. He, Kaijian & Lai, Kin Keung & Yen, Jerome, 2011. "Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach," Energy Economics, Elsevier, vol. 33(5), pages 903-911, September.
    15. Boubaker, Heni & Raza, Syed Ali, 2017. "A wavelet analysis of mean and volatility spillovers between oil and BRICS stock markets," Energy Economics, Elsevier, vol. 64(C), pages 105-117.
    16. Cheng, Wan-Hsiu & Hung, Jui-Cheng, 2011. "Skewness and leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 160-173, January.
    17. Khalil Jebran & Amjad Iqbal, 2016. "Dynamics of volatility spillover between stock market and foreign exchange market: evidence from Asian Countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-20, December.
    18. Chan, Joshua C.C. & Grant, Angelia L., 2016. "Modeling energy price dynamics: GARCH versus stochastic volatility," Energy Economics, Elsevier, vol. 54(C), pages 182-189.
    19. Tsuji, Chikashi, 2020. "Correlation and spillover effects between the US and international banking sectors: New evidence and implications for risk management," International Review of Financial Analysis, Elsevier, vol. 70(C).
    20. Adams, Zeno & Füss, Roland & Glück, Thorsten, 2017. "Are correlations constant? Empirical and theoretical results on popular correlation models in finance," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 9-24.

    More about this item

    Keywords

    Emerging Eastern Europe; stock and currency markets; portfolio; VaR;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fau:fauart:v:64:y:2014:i:4:p:296-311. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Natalie Svarcova (email available below). General contact details of provider: https://edirc.repec.org/data/icunicz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.