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Finansal Varlık Fiyatlarındaki Yüksek Oranlı Ani Değişimlerin (Price Jumps) Etkilerinin Analizi: Türkiye Örneği

Year 2020, Volume: 5 Issue: 9, 253 - 282, 30.06.2020

Abstract

Bu çalışmada finansal varlık fiyatlarındaki yüksek oranlı ani değişimlerin (jump) stokastik volatilite (SV) ile GARCH modellerine dahil edilmesinin bu modellerin performansları üzerindeki etkisi incelenmiştir. Analizler BİST100, BİST Mali ve BİST Sınai endeksleri dikkate alınarak yapılmıştır. Modeller Bayesyen yöntemi ile tahmin edilmiş ve model performanslarının karşılaştırılmasında bir Bayes faktörü olarak Log-ML değerinden yararlanılmıştır. Çalışma bulguları Türk hisse senedi piyasalarındaki yüksek oranlı ani değişimlerin yılda yaklaşık 3 kez gerçekleştiğini, bu etkinin standart GARCH ve SV modellerine dahil edilmesinin model performanslarını arttırdığını, neredeyse her durumda SV modellerinin GARCH modellerinden daha iyi bir performans sergilediğini ve her durumda en iyi performansı sergileyen modelin yüksek oranlı ani değişimleri dikkate alan SV (SV with jumps) modeli olduğunu göstermektedir.

References

  • Abdennadher, E., & Hallara, S. (2018), “ Structural Breaks and Stock Market Volatility in Emerging Countries”, International Journal of Business and Risk Management, 1, 9-16.
  • Abiyev, V. (2015), “Time-varying Beta and its Modeling Techniques for Turkish Industry Portfolio”, İktisat İşletme ve Finans, 30(352), 79-108.
  • Aloui, C., & Hamida, H.B. (2014), “Modelling and Forecasting Value-at-Risk and Expected Shortfall for GCC Stock Markets: Do Long Memory, Structural Breaks, Asymmetry, and Fat-Tails Matter?”, The North American Journal of Economics and Finance, 29, 349-380.
  • Assaf, A. (2017), “ The Stochastic Volatility Model, Regime Switching and Value-at-Risk (VaR) in International Equity Markets”, Journal of Mathematical Finance, 7, 491-512. Belkhouja, M., & Boutahary, M. (2011), “Modeling Volatility with Time-Varying FIGARCH Models”, Economic Modelling, 28 (3), 1106-1116.
  • Bentes, S. R. (2015), “Forecasting Volatility in Gold Returns under the GARCH, IGARCH and FIGARCH Frameworks: New Evidence”, Physica A, 438: 355–364.
  • Bouchaud, J-P., Kockelkoren, J., & Potters, M. (2006), “Random Walks, Liquidity Molasses and Critical Response İn Financial Markets”, Quantitative Finance, 6 (2), 115-123.
  • Büberkökü, Ö. (2019), “Asimetrik Stıkastik Volatilite Modelinin BİST100 Endeksine Uygulanması”, Iğdır Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18, 503-525.
  • Büberkökü, Ö., & Kızıldere, C. (2017), “ BİST100 Endeksinin Volatilite Dinamiklerinin İncelenmesi”, V Anadolu International Conference in Economics.11-13 Mayıs, Eskişehir,Türkiye. https://www. researchgate.net/publication /337007633_BIST100 _Endeksinin_Volatilite_ Ozelliklerinin_ Incelenmesi
  • Carnero, A., Pena, D., & Ruiz, E. (2004), “Persistence and Kurtosis in GARCH and Stochastic Volatility Models”, Journal of Financial Econometrics, 2 (2), 319-342.
  • Chan, JCC., & Grant, A.L. (2016)., “Modeling Energy Price Dynamics: GARCH Versus Stochastic Volatility”, Energy Economics, 54, 182-189.
  • Chan, W.H., & Maheu, J.M. (2002), “Conditional Jump Dynamics in Stock Market Returns”, American Statistical Association Journal of Business & Economic Statistics, 20 (3), 377-389.
  • Chen, C., & Sato, S. (2008), “In homogeneous Jump-GARCH Models with Applications in Financial Time Series Analysis”, In: Brito P. (eds) COMPSTAT, 217-228, Publisher Name: Physica-Verlag HD.
  • Chkili, W., Aloui, C., & Nguyen, D.K. (2012), “Asymmetric Effects and Long Memory in Dynamic Volatility Relationships Between Stock Returns and Exchange Rates”, Journal of International Financial Markets, Institutions and Money, 22 (4), 738- 757.
  • Christoffersen, P., Jacobs, K., & Ornthanalai, C. (2012), “Dynamic Jump Intensities and Risk Premiums: Evidence from S&P500 Returns and Options”, Journal of Financial Economics, 106 (3), 447-72.
  • Cochran, S.J., Mansur, I., & Odusami, B. ( 2012), “Volatility Persistence in Metal Returns: A FIGARCH Approach”, Journal of Economics and Business, 64 (4), 287-305.
  • Çevik, E.İ., & Topaloğlu, G. (2014), “Volatilitede Uzun Hafıza ve Yapısal Kırılma: Borsa İstanbul Örneği”, Balkan Sosyal Bilimler Dergisi, 3(6), 40-55.
  • Dickey, D. A., & Fuller, W. A. (1979), “Distribution of the Estimators for Autoregressive Time Series with Unit Root”, Journal of the American Statistical Association, 74, 427–431.
  • Ewing, B. T., & Malik, F. (2013), “Volatility Transmission Between Gold and Oil Futures Under Structural Breaks”, International Review of Economics & Finance, 25,113-121.
  • G. Li, G., & Zhang, C. (2013), “Jump Intensities, Jump Sizes, and the Relative Stock Price Level”, Available from: https://pdfs.semanticscholar.org/fbb3/f a78d25cfd146947 1310 65c7a966fad268f1.pdf. (Erişim Tarihi, Şubat 2020).
  • Göktaş, Ö., & Hepsağ, A. (2016), “ BIST100 Endeksinin Volatil Davranışlarının Simetrik ve Asimetrik Stokastik Volatilite Modelleri ile Analizi”, Ekonomik Yaklaşım, 27 (99), 1-15.
  • Hanousek, J., Kocenda, E., & Novotny, J. (2014), “Price Jumps on European Stock Markets”, Borsa Istanbul Review, 14 (1), 10-22.
  • Hwang, S., Satchell, S. E., & Pereıra, P. L.V. (2007), “How Persistent is Stock Return Volatility ? An Answer with Markov Regime Switching Stochastic Volatility Models”, Journal of Business Finance & Accounting, 34 (5-6), 1002-1024.
  • Ishihara, T., & Omori, Y. (2012), “Efficient Bayesian Estimation of a Multivariate Stochastic Volatility Model with Cross Leverage and Heavy-Tailed Errors”, Computational Statistics & Data Analysis, 56(11), 3674-3689.
  • Jensen, M.J., & Maheu, J.M. (2014), “ Estimating a Semiparametric Asymmetric Stochastic Volatility Model with Dirichlet Process Mixture”, Journal of Econometrics, 178, 523-538.
  • Kang, S.H., Cho, H-G.& Yoon, S-M. (2009), “Modeling Sudden Volatility Changes: Evidence from Japanese and Korean Stock Markets”, Physica A: Statistical Mechanics and its Applications, 388 (17), 3543–3550
  • Kim, S., Shephard, N., & Chib,S. (1998), “ Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models”, Review of Economic Studies, 65, 361-393.
  • Krichene, N. (2003), “Modeling Stochastic Volatility with Application to Stock Returns”, IMF Working Paper, No:03/125. https://www.imf.org/en/ Publications/ WP/Issues /2016 /12/30/.
  • Larsson, K., & Nossman, M. (2011), “Jumps and Stochastic Volatility in Oil Prices: Time Series Evidence”, Energy Economics, 33(3), 504-514.
  • Lee, S. S., & Mykland, Per A. (2008), “Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics”, The Review of Financial Studies, 21(6), 2535–2563.
  • Mariani, M.C., Bhuiyan, M. A.M., &.,Tweneboah, O.K.. (2018), “Estimation of Stochastic Volatility by Using Ornstein-Uhlenbeck Type Models”, Physica A, 491, 167-176.
  • Mensi, W., Hammoudeh, S., &., Kang, S.H. (2015), “Precious Metals, Cereal, Oil and Stock Market Linkages and Portfolio Risk Management: Evidence from Saudi Arabia”, Economic Modelling, 51, 340-358.
  • Merton, R. C. (1976), “Option Pricing when Underlying Stock Returns are Discontinuous”, Journal of Financial Economics, 3 (1-2), 125-144.
  • Özdemir, A., Vergili, G., & Çelik, İ. (2018), “Döviz Piyasalarının Etkinliği Üzerinde Uzun Hafızanın Rolü: Türk Döviz Piyasasında Ampirik Bir Araştırma”, BDDK Bankacılık ve Finansal Piyasalar, 12 (1), 87-107.
  • Özün, A., & Türk, M. (2008), “Döviz Kurlarının Öngörüsünde Stokastik Oynaklık Modelleri”, İktisat İşletme ve Finans, 23 (265), 50-67.
  • Selçuk, F. (2004), “Free Float and Stochastic Volatility: The Experience of a Small Open Economy”, Physica A: Statistical Mechanics and its Applications 342(3-4).
  • Sethapramote, Y., & Prukumpai, S. (2012), “Structural Breaks in Stock Returns Volatility: Evidence from the Stock Exchange of Thailand”, The Empirical Econometrics and Quantitative Economics Letters, 1 (3), 113-130.
  • Ural, M., & Küçüközmen, C.C. (2011), “Analyzing the Dual Long Memory in Stock Market Returns”, Ege Academic Review, 11, 19-28.
  • Wang, P. (2011), “Pricing Currency Options with Support Vector Regression and Stochastic Volatility Model with Jumps”, Expert Systems with Applications, 38 (1), 1-7.
  • Yalçın, Y. (2007), “ Stokastik Oynaklık Modeli ile İstanbul Menkul Kıymetler Borsası’nda Kaldıraç Etkisinin İncelenmesi”, Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Dergisi, 22(2), 357-365.
  • Yu, J. (2005), “On Leverage in a Stochastic Volatility Model”, Journal of Econometrics, 127, 165-178.
  • Yu, J-S., & Daal, E. (2005), “A Comparison of Mixed Garch-Jump Models with Skewed T-Distribution for Asset Returns”, Papers SSRN. https://ssrn.com/abstract= 670502 . (Erişim Tarihi, Şubat 2020).
Year 2020, Volume: 5 Issue: 9, 253 - 282, 30.06.2020

Abstract

References

  • Abdennadher, E., & Hallara, S. (2018), “ Structural Breaks and Stock Market Volatility in Emerging Countries”, International Journal of Business and Risk Management, 1, 9-16.
  • Abiyev, V. (2015), “Time-varying Beta and its Modeling Techniques for Turkish Industry Portfolio”, İktisat İşletme ve Finans, 30(352), 79-108.
  • Aloui, C., & Hamida, H.B. (2014), “Modelling and Forecasting Value-at-Risk and Expected Shortfall for GCC Stock Markets: Do Long Memory, Structural Breaks, Asymmetry, and Fat-Tails Matter?”, The North American Journal of Economics and Finance, 29, 349-380.
  • Assaf, A. (2017), “ The Stochastic Volatility Model, Regime Switching and Value-at-Risk (VaR) in International Equity Markets”, Journal of Mathematical Finance, 7, 491-512. Belkhouja, M., & Boutahary, M. (2011), “Modeling Volatility with Time-Varying FIGARCH Models”, Economic Modelling, 28 (3), 1106-1116.
  • Bentes, S. R. (2015), “Forecasting Volatility in Gold Returns under the GARCH, IGARCH and FIGARCH Frameworks: New Evidence”, Physica A, 438: 355–364.
  • Bouchaud, J-P., Kockelkoren, J., & Potters, M. (2006), “Random Walks, Liquidity Molasses and Critical Response İn Financial Markets”, Quantitative Finance, 6 (2), 115-123.
  • Büberkökü, Ö. (2019), “Asimetrik Stıkastik Volatilite Modelinin BİST100 Endeksine Uygulanması”, Iğdır Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 18, 503-525.
  • Büberkökü, Ö., & Kızıldere, C. (2017), “ BİST100 Endeksinin Volatilite Dinamiklerinin İncelenmesi”, V Anadolu International Conference in Economics.11-13 Mayıs, Eskişehir,Türkiye. https://www. researchgate.net/publication /337007633_BIST100 _Endeksinin_Volatilite_ Ozelliklerinin_ Incelenmesi
  • Carnero, A., Pena, D., & Ruiz, E. (2004), “Persistence and Kurtosis in GARCH and Stochastic Volatility Models”, Journal of Financial Econometrics, 2 (2), 319-342.
  • Chan, JCC., & Grant, A.L. (2016)., “Modeling Energy Price Dynamics: GARCH Versus Stochastic Volatility”, Energy Economics, 54, 182-189.
  • Chan, W.H., & Maheu, J.M. (2002), “Conditional Jump Dynamics in Stock Market Returns”, American Statistical Association Journal of Business & Economic Statistics, 20 (3), 377-389.
  • Chen, C., & Sato, S. (2008), “In homogeneous Jump-GARCH Models with Applications in Financial Time Series Analysis”, In: Brito P. (eds) COMPSTAT, 217-228, Publisher Name: Physica-Verlag HD.
  • Chkili, W., Aloui, C., & Nguyen, D.K. (2012), “Asymmetric Effects and Long Memory in Dynamic Volatility Relationships Between Stock Returns and Exchange Rates”, Journal of International Financial Markets, Institutions and Money, 22 (4), 738- 757.
  • Christoffersen, P., Jacobs, K., & Ornthanalai, C. (2012), “Dynamic Jump Intensities and Risk Premiums: Evidence from S&P500 Returns and Options”, Journal of Financial Economics, 106 (3), 447-72.
  • Cochran, S.J., Mansur, I., & Odusami, B. ( 2012), “Volatility Persistence in Metal Returns: A FIGARCH Approach”, Journal of Economics and Business, 64 (4), 287-305.
  • Çevik, E.İ., & Topaloğlu, G. (2014), “Volatilitede Uzun Hafıza ve Yapısal Kırılma: Borsa İstanbul Örneği”, Balkan Sosyal Bilimler Dergisi, 3(6), 40-55.
  • Dickey, D. A., & Fuller, W. A. (1979), “Distribution of the Estimators for Autoregressive Time Series with Unit Root”, Journal of the American Statistical Association, 74, 427–431.
  • Ewing, B. T., & Malik, F. (2013), “Volatility Transmission Between Gold and Oil Futures Under Structural Breaks”, International Review of Economics & Finance, 25,113-121.
  • G. Li, G., & Zhang, C. (2013), “Jump Intensities, Jump Sizes, and the Relative Stock Price Level”, Available from: https://pdfs.semanticscholar.org/fbb3/f a78d25cfd146947 1310 65c7a966fad268f1.pdf. (Erişim Tarihi, Şubat 2020).
  • Göktaş, Ö., & Hepsağ, A. (2016), “ BIST100 Endeksinin Volatil Davranışlarının Simetrik ve Asimetrik Stokastik Volatilite Modelleri ile Analizi”, Ekonomik Yaklaşım, 27 (99), 1-15.
  • Hanousek, J., Kocenda, E., & Novotny, J. (2014), “Price Jumps on European Stock Markets”, Borsa Istanbul Review, 14 (1), 10-22.
  • Hwang, S., Satchell, S. E., & Pereıra, P. L.V. (2007), “How Persistent is Stock Return Volatility ? An Answer with Markov Regime Switching Stochastic Volatility Models”, Journal of Business Finance & Accounting, 34 (5-6), 1002-1024.
  • Ishihara, T., & Omori, Y. (2012), “Efficient Bayesian Estimation of a Multivariate Stochastic Volatility Model with Cross Leverage and Heavy-Tailed Errors”, Computational Statistics & Data Analysis, 56(11), 3674-3689.
  • Jensen, M.J., & Maheu, J.M. (2014), “ Estimating a Semiparametric Asymmetric Stochastic Volatility Model with Dirichlet Process Mixture”, Journal of Econometrics, 178, 523-538.
  • Kang, S.H., Cho, H-G.& Yoon, S-M. (2009), “Modeling Sudden Volatility Changes: Evidence from Japanese and Korean Stock Markets”, Physica A: Statistical Mechanics and its Applications, 388 (17), 3543–3550
  • Kim, S., Shephard, N., & Chib,S. (1998), “ Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models”, Review of Economic Studies, 65, 361-393.
  • Krichene, N. (2003), “Modeling Stochastic Volatility with Application to Stock Returns”, IMF Working Paper, No:03/125. https://www.imf.org/en/ Publications/ WP/Issues /2016 /12/30/.
  • Larsson, K., & Nossman, M. (2011), “Jumps and Stochastic Volatility in Oil Prices: Time Series Evidence”, Energy Economics, 33(3), 504-514.
  • Lee, S. S., & Mykland, Per A. (2008), “Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics”, The Review of Financial Studies, 21(6), 2535–2563.
  • Mariani, M.C., Bhuiyan, M. A.M., &.,Tweneboah, O.K.. (2018), “Estimation of Stochastic Volatility by Using Ornstein-Uhlenbeck Type Models”, Physica A, 491, 167-176.
  • Mensi, W., Hammoudeh, S., &., Kang, S.H. (2015), “Precious Metals, Cereal, Oil and Stock Market Linkages and Portfolio Risk Management: Evidence from Saudi Arabia”, Economic Modelling, 51, 340-358.
  • Merton, R. C. (1976), “Option Pricing when Underlying Stock Returns are Discontinuous”, Journal of Financial Economics, 3 (1-2), 125-144.
  • Özdemir, A., Vergili, G., & Çelik, İ. (2018), “Döviz Piyasalarının Etkinliği Üzerinde Uzun Hafızanın Rolü: Türk Döviz Piyasasında Ampirik Bir Araştırma”, BDDK Bankacılık ve Finansal Piyasalar, 12 (1), 87-107.
  • Özün, A., & Türk, M. (2008), “Döviz Kurlarının Öngörüsünde Stokastik Oynaklık Modelleri”, İktisat İşletme ve Finans, 23 (265), 50-67.
  • Selçuk, F. (2004), “Free Float and Stochastic Volatility: The Experience of a Small Open Economy”, Physica A: Statistical Mechanics and its Applications 342(3-4).
  • Sethapramote, Y., & Prukumpai, S. (2012), “Structural Breaks in Stock Returns Volatility: Evidence from the Stock Exchange of Thailand”, The Empirical Econometrics and Quantitative Economics Letters, 1 (3), 113-130.
  • Ural, M., & Küçüközmen, C.C. (2011), “Analyzing the Dual Long Memory in Stock Market Returns”, Ege Academic Review, 11, 19-28.
  • Wang, P. (2011), “Pricing Currency Options with Support Vector Regression and Stochastic Volatility Model with Jumps”, Expert Systems with Applications, 38 (1), 1-7.
  • Yalçın, Y. (2007), “ Stokastik Oynaklık Modeli ile İstanbul Menkul Kıymetler Borsası’nda Kaldıraç Etkisinin İncelenmesi”, Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Dergisi, 22(2), 357-365.
  • Yu, J. (2005), “On Leverage in a Stochastic Volatility Model”, Journal of Econometrics, 127, 165-178.
  • Yu, J-S., & Daal, E. (2005), “A Comparison of Mixed Garch-Jump Models with Skewed T-Distribution for Asset Returns”, Papers SSRN. https://ssrn.com/abstract= 670502 . (Erişim Tarihi, Şubat 2020).
There are 41 citations in total.

Details

Primary Language Turkish
Subjects Economics
Journal Section Articles
Authors

Önder Büberkökü 0000-0002-7140-557X

Publication Date June 30, 2020
Submission Date March 22, 2020
Published in Issue Year 2020 Volume: 5 Issue: 9

Cite

APA Büberkökü, Ö. (2020). Finansal Varlık Fiyatlarındaki Yüksek Oranlı Ani Değişimlerin (Price Jumps) Etkilerinin Analizi: Türkiye Örneği. Van Yüzüncü Yıl Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 5(9), 253-282.