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Examining the Impact of the Global Financial Crisis on the Deposit Banks’ Level of Systematic Risk: Evidence from AR(p)-DCCFIGARCH (p,d,q) and Asymmetric AR(p)-DBEKK-GARCH (p, q) Models

Yıl 2018, Cilt: 33 Sayı: 1, 39 - 73, 20.04.2018
https://doi.org/10.24988/deuiibf.2018331540

Öz

This study examines the impact of the 2007–2008 global financial crisis on the time-varying conditional systematic risk level of nine deposit banks using AR(p)-DCC-FIGARCH (p,d,q) and asymmetric AR(p)-DBEKK-GARCH (p,q) models under the assumption of a multivariate Student’s t distribution. Results show that the systematic risk level of two large-scale banks, in particular, significantly increased during the crisis period. The systematic risk level of two small- and medium-sized banks also significantly increased during the crisis period. Additionally, one-break unit root tests applied to all banks’ systematic risk coefficients show that all these series are stationary at their level form.

Kaynakça

  • ADAM, T., BENECKA, S., JANSKY, I. (2012), “Time-Varying Betas of Banking Sector”, Czech Journal of Economics and Finance, 62, 485-501.
  • ALOUI, C., MABROUK, S. (2012), “Value-at-risk Estimations of Energy Commodities via Long-Memory, Asymmetry and Fat-Tailed GARCH Models”, Energy Policy, 38, 2326–2339.
  • ALTINSOY, G. (2009), “ Time-Varying Beta Estimation for Turkish Real Estate Investment Trusts: An Analysis of Alternative Modeling Techniques”, A Thesis for the Degree of Master of Science”, Middle East TechnicalUniversity.https://etd.lib.metu.edu.tr/upload/3/12611309/index.pdf, (22.02.2016).
  • ANDREW, D. (1993), “Test for Parameter Instability and Structural Change with Unknown Change Point”, Econometrica, 61(4), 821-856.
  • AOHNA, T. (2010), “ Time-varying Betas and the Athens Stock Exchange Market”, Master Thesis, University of Macedonia. https://dspace.lib.uom.gr/handle/2159/15815, (22.2.2016).
  • BAI, J., PERRON, P. (1998), “ Estimating and Testing Linear Models with Multiple Structural Changes”, Econometrica, 66, 47–78.
  • BAI, J., PERRON, P. (2003), “ Computation and Analysis of Multiple Structural Change Models”, Journal of Applied Econometrics, 18 , 1–22.
  • BAILLIE, R.T., BOLLERSLEV, T., MIKKELSEN, H.O. (1996), “Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics 74, 3–30.
  • BAŞÇI, E., KARA, H. (2011), “ Finansal İstikrar ve Para Politikası”, İktisat, İşletme ve Finans Dergisi, 26 (302), 9-25.
  • BESSLER, W., KURMAN, P., NOHEL, T. (2015), “ Time-Varying Systematic and Idiosynctaric Risk Exposure of US Bank Holding Companies”, Journal of International Financial Markets, Institutions & Money, 35,45-68.
  • BLUME, M. (1971), “ On the Assesmentof the Risk”, The Journal of Finance, 26 (1),1-10.
  • BOLLENA, B., SKULLYB, M., TRIPEC, D., WEIB, X. (2015), “ The Global Financial Crisis and Its Impact on Australian Bank Risk”, International Review of Finance, 15(1), 89-112.
  • BROOKS, R., SHOUNG, L.C. (2006), “The Impact of Capital Controls on Malaysian Banking Industry”, Applied Financial Economic Letters, 2, 247-249.
  • BROOKS, R.D., FAFF, R.W. (1997), “Beta Forecasting in Malaysia: A Note”, Malaysian Management Review, 32, 48-50.
  • BROOKS, R.D., FAFF, R.W., MCKENZIE, M.D. (1998), “Time-varying Country: An Assessment Comparison of Alternative Modelling Techniques”, European Journal of Finance, 8, 249-279.
  • CAPORALE, T. (2012), “Time Varying CAPM Betas and Banking Risk” , Economic Letters, 115, 291-295.
  • CHIANG, T.C., JEON, B.N., LI, H. (2007), “Dynamic Correlation Analysis of Financial Contagion: Evidence from Asian Markets”, Journal of International Money and Finance, 26, 1206-1228.
  • CHKILI, W., ALOUIB, C., NGUYENC, D.K. (2012), “Asymmetric EffectsandLong Memory in Dynamic Volatility relationships between Stock Returns and Exchange Rates”, Journal of International Financial Markets, Institutions & Money,22,738-757.
  • CHOUDHRY, T. (2005)”, Time-Varying Beta and the Asian Financial Crisis: Evidence From Malaysian and Taiwanese Firms, Pacific-Basin Finance Journal, 13,93-118.
  • CHOUDHRY, T., LU, L., PENG, K. (2010), “Time-Varying Beta and the Asain Financial Crisis: Evidence from the Asain Indutrial Sectors”, Japan and the World Economy, 22,228-234.
  • CINER, C. (2015), “ Time Variation in Systematic Risk, Returnsand Trading Volume: Evidence from Precious Metals Mining Stocks”, International Review of Financial Analysis, 41, 277-283.
  • CLEMENTE, J., MONTANES, A., REYES, M. (1998), “Testing for a Unit Root in Variables with a Double Change in the Mean”, Economic Letters, 59, 175 182.
  • DASH, M. (2016), “ Testing the Stationarity of Beta for Banking Sector Stocks in Indian Stock Markets: Panel Regression Analysis”, Skyline Business Journal, 11 (2), 53-60.
  • DIMITRIOU, D., KENOURGIOS, D., SIMOS,T. (2013), “Global Financial Crisis and Emerging Stock Market Contagion: A Multivariate FIAPARCH-DCC Approach”, International Review of Financial Analysis, 30, 46-56.
  • EISENBEISS, M., KAUERMANN, G., SEMMIER, W. (2007), “ Estimating Beta-Coefficients of German Stock Data: A Non-Parametric Approach , The European Journal of Finance, 13 (6), 503-522.
  • ENGLE, R. (2002), “Dynamic ConditionalCorrelation. A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models” , Journal of Business and Economic Statistics, 20,339–350.
  • ENGLE, R., KRONER, K. (1995), “Multivariate Simultaneous Generalized ARCH ”, Econometric Theory, 11, 122-150.
  • FABOZZI, F.J., FRANCIS, J.C. (1978), “Beta as a Random Coefficient”, Journal of Financial and Quantitative Analysis, 13, 101-116.
  • FAFF, R.W., HILLER, D., HILLER, J. (2000), “Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques”, Journal of Business, Finance & Accounting, 27 (5), 523-537.
  • GEWEKE, J., PORTER-HUDAK, S. (1983), “The Estimation and Application of Long Memory Time Series Models”, Journal of Time Series Analysis, 4, 221 238.
  • HANSEN, B. (1997) ,“Approximate Asymptotic p-values for Structural-Change Test”, Journal of Business and Economic Statistics,15(1), 60-67.
  • JOHANSSON, A.C. (2009), “Stochastic Volatility and Time-varying Country Risk in Emerging Markets, The European Journal of Finance, 15 (3), 337-363.
  • KARA, A.H. (2012), “ Küresel Kriz Sonrası Para Politikası”, İktisat, İşletme ve Finans Dergisi, 27 (315), 9-36.
  • KURACH, R., STELMACH, J. (2014), “Time-Varying Behaviour of Sector Beta Risk–The Case of Poland ”, Romanian Journal of Economic Forecasting, 17 (1), 139-156.
  • LIE, F., BROOKS, R., FAFF, R.W. (2000), “ Modeling the Equity Beta Risk of Australian Financial Sector Companies”, Australian Economic Papers, 39, 301-311.
  • LINTNER, J., (1965), “ The Valuation of Risk Assets and Selection of Risky in Stock Portfolios and Capital Budgets, Review of Economics and Statistics, 47, 13-37.
  • MERGNER, S., BULLA, J. (2008), “ Time-Varying Beta Risk of Pan-European Industry Portfolios: A Comparison of Alternative ModelingTechniques”, European Journal of Finance , 14 (8), 772-802.
  • QUANDT, R. (1960), “Test for Hypothesis that a Linear Regression System Obeys two Separate Regimes”, Journal of the Americans Statistical Association, 55 (290), 324-330.
  • ROBINSON, P.M., HENRY, M. (1999), “Long and Short Memory Conditional Hetereskedasticity in Estimating the Memory Parameters of Levels”, Economic Theory, 15, 299-336.
  • SCHWERT, W., SEGUIN, P. (1990), “Heteroskedasticity in Stock Returns”, Journal of Finance, 45,1129-1155.
  • SHARPE, W. (1964), “ Capital Asset Prices: A Theory of Market Equilibrium Under Condition of Risk”, Journal of Finance, 19, 425-442.
  • STRACCA, L. (2015), “Our Currency, Your Problem? The Global Effectsof the Euro Debt Crisis”, European Economic Review, 74, 1–13.
  • SYLLIGNAKIS, M.N., KOURETAS, G.P. (2011), “Dynamic Correlation Analysis of Financial Contagion: Evidence from the Central and Eastern European Markets”, International Review of Economics and Finance, 20, 717–732.
  • YIU, M.S., HO, W.Y.A., CHOI, D.F. (2010), “Dynamic Correlation Analysis of Financial Contagion in Asian Markets in Global Financial Turmoil”, Applied Financial Economics, 20, 345–354.
  • ZIVOT, E., ANDREWS D. W.K. (1992), “Further Evidence on the Great Crash, The Oil Price Shocks, and Unit Root Hypothesis”, Journal of Business & Economic Statistics, 10: 251-270.

Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, q) ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz

Yıl 2018, Cilt: 33 Sayı: 1, 39 - 73, 20.04.2018
https://doi.org/10.24988/deuiibf.2018331540

Öz

Bu çalışmada çoklu student t dağılım varsayımı altında AR(p)-DCC-FIGARCH (p,d,q) ve asimetrik AR(p)-DBEKK-GARCH (p,q) modelleri kullanılarak 2007-2008 küresel finans krizinin 9 mevduat bankasının zamanla değişen sistematik risk düzeyi üzerindeki etkisi incelenmiştir. Bulgular, özellikle büyük ölçekli bankalardan 2 tanesinin sistematik risk düzeyinin küresel kriz dönemi ile birlikte belirgin bir şeklide arttığına işaret etmektedir. İki küçük ve orta ölçekli bankanın da sistematik risk düzeyinin kriz döneminde belirgin bir şekilde arttığı belirlenmiştir. Ayrıca, tüm bankaların sistematik risk düzeylerine uygulanan tek yapısal kırılmalı birim kök testi sonuçları bankaların sistematik risk düzeylerinin düzey değerlerinde durağan olduğuna işaret etmektedir

Kaynakça

  • ADAM, T., BENECKA, S., JANSKY, I. (2012), “Time-Varying Betas of Banking Sector”, Czech Journal of Economics and Finance, 62, 485-501.
  • ALOUI, C., MABROUK, S. (2012), “Value-at-risk Estimations of Energy Commodities via Long-Memory, Asymmetry and Fat-Tailed GARCH Models”, Energy Policy, 38, 2326–2339.
  • ALTINSOY, G. (2009), “ Time-Varying Beta Estimation for Turkish Real Estate Investment Trusts: An Analysis of Alternative Modeling Techniques”, A Thesis for the Degree of Master of Science”, Middle East TechnicalUniversity.https://etd.lib.metu.edu.tr/upload/3/12611309/index.pdf, (22.02.2016).
  • ANDREW, D. (1993), “Test for Parameter Instability and Structural Change with Unknown Change Point”, Econometrica, 61(4), 821-856.
  • AOHNA, T. (2010), “ Time-varying Betas and the Athens Stock Exchange Market”, Master Thesis, University of Macedonia. https://dspace.lib.uom.gr/handle/2159/15815, (22.2.2016).
  • BAI, J., PERRON, P. (1998), “ Estimating and Testing Linear Models with Multiple Structural Changes”, Econometrica, 66, 47–78.
  • BAI, J., PERRON, P. (2003), “ Computation and Analysis of Multiple Structural Change Models”, Journal of Applied Econometrics, 18 , 1–22.
  • BAILLIE, R.T., BOLLERSLEV, T., MIKKELSEN, H.O. (1996), “Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics 74, 3–30.
  • BAŞÇI, E., KARA, H. (2011), “ Finansal İstikrar ve Para Politikası”, İktisat, İşletme ve Finans Dergisi, 26 (302), 9-25.
  • BESSLER, W., KURMAN, P., NOHEL, T. (2015), “ Time-Varying Systematic and Idiosynctaric Risk Exposure of US Bank Holding Companies”, Journal of International Financial Markets, Institutions & Money, 35,45-68.
  • BLUME, M. (1971), “ On the Assesmentof the Risk”, The Journal of Finance, 26 (1),1-10.
  • BOLLENA, B., SKULLYB, M., TRIPEC, D., WEIB, X. (2015), “ The Global Financial Crisis and Its Impact on Australian Bank Risk”, International Review of Finance, 15(1), 89-112.
  • BROOKS, R., SHOUNG, L.C. (2006), “The Impact of Capital Controls on Malaysian Banking Industry”, Applied Financial Economic Letters, 2, 247-249.
  • BROOKS, R.D., FAFF, R.W. (1997), “Beta Forecasting in Malaysia: A Note”, Malaysian Management Review, 32, 48-50.
  • BROOKS, R.D., FAFF, R.W., MCKENZIE, M.D. (1998), “Time-varying Country: An Assessment Comparison of Alternative Modelling Techniques”, European Journal of Finance, 8, 249-279.
  • CAPORALE, T. (2012), “Time Varying CAPM Betas and Banking Risk” , Economic Letters, 115, 291-295.
  • CHIANG, T.C., JEON, B.N., LI, H. (2007), “Dynamic Correlation Analysis of Financial Contagion: Evidence from Asian Markets”, Journal of International Money and Finance, 26, 1206-1228.
  • CHKILI, W., ALOUIB, C., NGUYENC, D.K. (2012), “Asymmetric EffectsandLong Memory in Dynamic Volatility relationships between Stock Returns and Exchange Rates”, Journal of International Financial Markets, Institutions & Money,22,738-757.
  • CHOUDHRY, T. (2005)”, Time-Varying Beta and the Asian Financial Crisis: Evidence From Malaysian and Taiwanese Firms, Pacific-Basin Finance Journal, 13,93-118.
  • CHOUDHRY, T., LU, L., PENG, K. (2010), “Time-Varying Beta and the Asain Financial Crisis: Evidence from the Asain Indutrial Sectors”, Japan and the World Economy, 22,228-234.
  • CINER, C. (2015), “ Time Variation in Systematic Risk, Returnsand Trading Volume: Evidence from Precious Metals Mining Stocks”, International Review of Financial Analysis, 41, 277-283.
  • CLEMENTE, J., MONTANES, A., REYES, M. (1998), “Testing for a Unit Root in Variables with a Double Change in the Mean”, Economic Letters, 59, 175 182.
  • DASH, M. (2016), “ Testing the Stationarity of Beta for Banking Sector Stocks in Indian Stock Markets: Panel Regression Analysis”, Skyline Business Journal, 11 (2), 53-60.
  • DIMITRIOU, D., KENOURGIOS, D., SIMOS,T. (2013), “Global Financial Crisis and Emerging Stock Market Contagion: A Multivariate FIAPARCH-DCC Approach”, International Review of Financial Analysis, 30, 46-56.
  • EISENBEISS, M., KAUERMANN, G., SEMMIER, W. (2007), “ Estimating Beta-Coefficients of German Stock Data: A Non-Parametric Approach , The European Journal of Finance, 13 (6), 503-522.
  • ENGLE, R. (2002), “Dynamic ConditionalCorrelation. A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models” , Journal of Business and Economic Statistics, 20,339–350.
  • ENGLE, R., KRONER, K. (1995), “Multivariate Simultaneous Generalized ARCH ”, Econometric Theory, 11, 122-150.
  • FABOZZI, F.J., FRANCIS, J.C. (1978), “Beta as a Random Coefficient”, Journal of Financial and Quantitative Analysis, 13, 101-116.
  • FAFF, R.W., HILLER, D., HILLER, J. (2000), “Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques”, Journal of Business, Finance & Accounting, 27 (5), 523-537.
  • GEWEKE, J., PORTER-HUDAK, S. (1983), “The Estimation and Application of Long Memory Time Series Models”, Journal of Time Series Analysis, 4, 221 238.
  • HANSEN, B. (1997) ,“Approximate Asymptotic p-values for Structural-Change Test”, Journal of Business and Economic Statistics,15(1), 60-67.
  • JOHANSSON, A.C. (2009), “Stochastic Volatility and Time-varying Country Risk in Emerging Markets, The European Journal of Finance, 15 (3), 337-363.
  • KARA, A.H. (2012), “ Küresel Kriz Sonrası Para Politikası”, İktisat, İşletme ve Finans Dergisi, 27 (315), 9-36.
  • KURACH, R., STELMACH, J. (2014), “Time-Varying Behaviour of Sector Beta Risk–The Case of Poland ”, Romanian Journal of Economic Forecasting, 17 (1), 139-156.
  • LIE, F., BROOKS, R., FAFF, R.W. (2000), “ Modeling the Equity Beta Risk of Australian Financial Sector Companies”, Australian Economic Papers, 39, 301-311.
  • LINTNER, J., (1965), “ The Valuation of Risk Assets and Selection of Risky in Stock Portfolios and Capital Budgets, Review of Economics and Statistics, 47, 13-37.
  • MERGNER, S., BULLA, J. (2008), “ Time-Varying Beta Risk of Pan-European Industry Portfolios: A Comparison of Alternative ModelingTechniques”, European Journal of Finance , 14 (8), 772-802.
  • QUANDT, R. (1960), “Test for Hypothesis that a Linear Regression System Obeys two Separate Regimes”, Journal of the Americans Statistical Association, 55 (290), 324-330.
  • ROBINSON, P.M., HENRY, M. (1999), “Long and Short Memory Conditional Hetereskedasticity in Estimating the Memory Parameters of Levels”, Economic Theory, 15, 299-336.
  • SCHWERT, W., SEGUIN, P. (1990), “Heteroskedasticity in Stock Returns”, Journal of Finance, 45,1129-1155.
  • SHARPE, W. (1964), “ Capital Asset Prices: A Theory of Market Equilibrium Under Condition of Risk”, Journal of Finance, 19, 425-442.
  • STRACCA, L. (2015), “Our Currency, Your Problem? The Global Effectsof the Euro Debt Crisis”, European Economic Review, 74, 1–13.
  • SYLLIGNAKIS, M.N., KOURETAS, G.P. (2011), “Dynamic Correlation Analysis of Financial Contagion: Evidence from the Central and Eastern European Markets”, International Review of Economics and Finance, 20, 717–732.
  • YIU, M.S., HO, W.Y.A., CHOI, D.F. (2010), “Dynamic Correlation Analysis of Financial Contagion in Asian Markets in Global Financial Turmoil”, Applied Financial Economics, 20, 345–354.
  • ZIVOT, E., ANDREWS D. W.K. (1992), “Further Evidence on the Great Crash, The Oil Price Shocks, and Unit Root Hypothesis”, Journal of Business & Economic Statistics, 10: 251-270.
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Önder Büberkökü

Yayımlanma Tarihi 20 Nisan 2018
Kabul Tarihi 15 Ağustos 2017
Yayımlandığı Sayı Yıl 2018 Cilt: 33 Sayı: 1

Kaynak Göster

APA Büberkökü, Ö. (2018). Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, q) ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi, 33(1), 39-73. https://doi.org/10.24988/deuiibf.2018331540
AMA Büberkökü Ö. Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, q) ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi. Nisan 2018;33(1):39-73. doi:10.24988/deuiibf.2018331540
Chicago Büberkökü, Önder. “Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, Q) Ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz”. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi 33, sy. 1 (Nisan 2018): 39-73. https://doi.org/10.24988/deuiibf.2018331540.
EndNote Büberkökü Ö (01 Nisan 2018) Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, q) ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi 33 1 39–73.
IEEE Ö. Büberkökü, “Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, q) ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz”, Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi, c. 33, sy. 1, ss. 39–73, 2018, doi: 10.24988/deuiibf.2018331540.
ISNAD Büberkökü, Önder. “Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, Q) Ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz”. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi 33/1 (Nisan 2018), 39-73. https://doi.org/10.24988/deuiibf.2018331540.
JAMA Büberkökü Ö. Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, q) ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi. 2018;33:39–73.
MLA Büberkökü, Önder. “Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, Q) Ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz”. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi, c. 33, sy. 1, 2018, ss. 39-73, doi:10.24988/deuiibf.2018331540.
Vancouver Büberkökü Ö. Küresel Finans Krizinin Mevduat Bankalarının Sistematik Risk Düzeyi Üzerindeki Etkisinin İncelenmesi: AR(p)-DCCFIGARCH (p,d, q) ve Asimetrik AR(p)-DBEKK-GARCH (p,q) Modellerine Dayalı Bir Analiz. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi. 2018;33(1):39-73.