Asimetrik Stokastik Volatilite Modelinin BIST100 Endeksine Uygulanması

Yıl 2019, Sayı: 18, 503 - 525, 01.04.2019

Önder Büberkökü

Öz

Bu çalışmada asimetrik stokastik volatilite ASV modeli lognormal dağılım varsayımları altında 2007-2008 küresel finans krizi dikkate alınarak BIST100 endeksine uygulanmıştır. ASV modelinin parametrelerinin tahmininde Bayesyen yaklaşımına dayalı MCMC Markov Chain Monte Carlo, MCMC algoritmasından yararlanılmıştır. Çalışma bulguları BIST100 endeksi için asimetrik tepkinin ve yüksek volatilite kalıcılığının söz konusu olduğuna işaret etmektedir. 2007-2008 küresel finans krizinin daha çok asimetri parametresi üzerinde etkili olduğu bu nedenle küresel finans krizi döneminde BIST100 endeksi getirisindeki değişimlerin BIST100 endeksi volatilitesi üzerinde daha fazla etkili olduğu anlaşılmaktadır. Çalışma bulgularının BIST100 endeksinin volatilite dinamiklerinin daha iyi anlaşılabilmesi ve ASV modellerinin Türk finans piyasalarına uygulanabilirliği açısından önemli olduğu düşünülmektedir.

Anahtar Kelimeler

Asimetrik stokastik volatilite modeli, BIST100 endeksi, Bayesyen yaklaşımı.

An Empirical Application of an Asymmetric Stochastic Volatility Model to ISE100 Index

Öz

This study applies an asymmetric stochastic volatility ASV model to the ISE100 index by considering the 2007–2008 global financial crisis under the assumption of a lognormal distribution. The MCMC Markov Chain Monte Carlo algorithm based on a Bayesian approach is used to estimate the parameters of the ASV model. According to the results, the return volatility of the ISE100 index exhibits volatility persistence and leverage effect. Additionally, the model indicates that the global financial crisis of 2007–2008 mostly affects the leverage-effect parameter, implying that changes in the return of the ISE100 index more greatly influenced its volatility during the crisis. The findings contribute to the understanding of the volatility dynamics of the ISE100 index and the applicability of ASV models to Turkish financial markets.

Anahtar Kelimeler

Asymmetric stochastic volatility model, ISE100 index, Bayesian approach.

Kaynakça

• Abiyev,V. (2015), “Time-varying beta and its modeling techniques for Turkish industry portfolio”, İktisat İşletme ve Finans, 30(352), 79-108.
• 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.
• Barndorff- Nielsen, O.E. ve Shephard, N. (2006), “Impacts of jumps on returns and realised variances : Econometric analysis of time-deformed Levy processes”, Journal of Econometrics, 131, 217-252.
• Broto, C. ve Ruiz, E. (2004), “ Estimation methods for stochastic volatility models : A survey” , Journal of Economic Surveys, 18, 613-649.
• Carnero, A., Pena, D. ve Ruiz, E. (2004), “Persistence and kurtosis in GARCH and stochastic volatility models”, Journal of Fi- nancial Econometrics, 2 (2), 319-342.
• Chan, J.C.C. ve Grant, A. L. (2016), “ Modeling energy price Dy- namics: GARCH versus stochastic volatility”, Energy Econo- mics, 54, 182-189.
• Dimitrakopoulos, S. (2017), “ The semiparametric asymmetric stochas- tic volatility model with time-varying parameters: The case of US inflation”, Economic Letters, 155, 14-18.
• 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.
• Göktaş, Ö. ve Hepsağ, A. (2016), “ BIST100 endeksinin volatil dav- ranışlarının simetrik ve asimetrik stokastik volatilite modelleri ile Analizi”, Ekonomik Yaklaşım, 27 (99), 1-15.
• Jacquier, E., Polson, N.G. ve Rossi, P.E. (2004), “Bayesian Analysis of Stochastic Volatility Models with fat-tails and correlated er- rors,”, Journal of Econometrics, 122, 185-212.
• Jensen, M.J. ve Maheu, J.M. (2014), “ Estimating a semiparametric asymmetric stochastic volatility model with Dirichlet process mixture”, Journal of Econometrics, 178, 523-538.
• Kim, S., Shephard, N. ve Chib,S. (1998), “ Stochastic Volatility: Likeli- hood inference and comparison with ARCH models”, Review of Economic Studies, 65, 361-393.
• Krichene, N. (2003), “Modeling stochastic volatility with application to stock https://www.imf.org/en/Publications/WP/Issues/2016/12/30 /. IMF Working Paper, No:03/125.
• Mariani, M.C., Bhuiyan, Md. A.M. ve Tweneboah, O.K.. (2018), “Estimation of stochastic volatility by using Ornstein- Uhlenbeck type models”, Physica A, 491, 167-176.
• Men, Z., McLeish, D., Kolkiewicz, A.W. ve Wirjanto, T.S. (2017), “Comparison of asymmetric stochastic volatility models under different correlation structures”, Journal of Applied Statistics, 44 (8), 1350-1368.
• Nakajima, J. (2008), “ EGARCH and stochastic volatility: Modeling jumps and heavy-tails for stock returns”, IMES Institute for Monetary and Economic Studies, Bank of Japan, No: 2008-E-23. https://www.imes.boj.or.jp/research/abstracts/english/08-E- 23.html.
• Nakajima, J. ve Omori, Y. (2009), “Leverage, heavy-tails and correla- ted jumps in stochastic volatiliy models”, Computational Sta- tistics and Data Analysis, 53, 2335-2353.
• Nakajima, J. ve Omori, Y. (2012), “ Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution”, Computational Statistics and Data Anlysis, 56, 3690-3704.
• Omori, Y., Chib, S., Shephard, N. ve Nakajima, J. (2007), “Stochastic volatility with leverage: Fast and efficient likelihood inferences”, Journal of Econometrics, 140, 425-449.
• Özün, A. ve Türk, M. (2008), “ Döviz kurlarının öngörüsünde stokas- tik oynaklık modelleri”, İktisat İşletme ve Finans, 23 (265), 50-67.
• Stracca, L. (2015), “Our currency, your problem? The Global effects of the Euro debt crisis”, European Economic Review, 74, 1–13.
• Wang, J.J.J., Chan, J.S.K. ve Choy, S.T.B. (2011), “Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures”, Computational Statistics & Data Analysis, 55(1), 852-862.
• Yalçın, Y. (2007), “ Stokastik oynaklık modeli ile İstanbul Menkul Kıymetler Borsası’nda Kaldıraç etkisinin incelenmesi”, 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.