BORSA İSTANBUL 100 ENDEKSİ İÇİN DİNAMİK RİSKE MARUZ DEĞER VE BEKLENEN KAYIP ANALİZİ

Bu çalışmada, BIST 100 endeks getirileri için, önemli finansal risk ölçütlerinden dinamik riske maruz değer ve beklenen kayıp tahmini ve öngörüsü yapılmıştır. Öngörü modeli olarak genelleştirilmiş özyenilemeli skor, ARMA-GARCH ve yuvarlanan pencere tabanlı tahmin modelleri kullanılmıştır. Ayrıca, farklı frekanslarda hesaplanan getiri serileri kullanılarak, farklı frekanslarda risk ölçütleri Nisan 2016 ve Şubat 2019 tarihleri arası için elde edilmiştir. Çalışmanın temel bulguları, 1) Yapılan örneklem dışı analizde genelleştirilmiş özyenilemeli skor tabanlı yöntemlerin daha verimli olduğu ve 2) Risk ölçütlerinin örneklem sonuna doğru dalgalanması azalırken seviyelerinin yavaş bir şekilde arttığı olgularıyla özetlenebilir.

Anahtar Kelimeler:

Riske maruz değer, Beklenen kayıp, GARCH modeli, GAS modeli

ANALYSIS OF DYNAMIC VALUE-AT-RISK AND EXPECTED SHORTFALL FOR BIST 100 INDEX

In this study, the dynamic Value-at-Risk and Expected shortfall, which are the fundamental financial risk measures, are estimated and forecasted. As the forecasting model, the generalized autoregressive score, ARMA-GARCH, and rolling window-based forecasting models are used. Besides, risk criteria at different frequencies are obtained between April 2016 and February 2019 by using the return series calculated at different frequencies. The main findings of the study can be summarized as, 1) In the out-of-sample analysis, the generalized autoregressive score-based methods exhibit better forecasting performance, and 2) while the fluctuation of risk criteria lowers, their levels gradually increase towards the end of the sample.

Keywords:

Value-at-Risk, Expected shortfall, GARCH model, GAS model,

PDF

___

Alfonsi, A., & Schied, A. (2010). Optimal trade execution and absence of price manipulations in limit order book models. SIAM Journal on Financial Mathematics, 1(1), 490-522.
Ardia, D., Bluteau, K., Boudt, K., & Catania, L. (2018). Forecasting risk with Markov-switching GARCH models: A large-scale performance study. International Journal of Forecasting, 34(4), 733-747.
Basel Committee on Banking Supervision (2010). Basel III: A Global Regulatory Framework for More Resilient Banks and Banking Systems, Bank for International Settlements. http://www.bis.org/publ/bcbs189.pdf
Bayraktar, E., & Ludkovski, M. (2014). Liquidation in limit order books with controlled intensity. Mathematical Finance, 24(4), 627-650.
Bekaert, G., & Harvey, C. R. (1997). Emerging equity market volatility. Journal of Financial Economics, 43(1), 29-77.
Bu, D., Liao, Y., Shi, J., & Peng, H. (2019). Dynamic expected shortfall: A spectral decomposition of tail risk across time horizons. Journal of Economic Dynamics and Control, 108, 103753.
Creal, D.D., S.J. Koopman, and A. Lucas, 2013, Generalized Autoregressive Score Models with Applications, Journal of Applied Econometrics, 28(5), 777-795.
Davis, M. H. (2016). Verification of internal risk measure estimates. Statistics & Risk Modeling, 33(3-4), 67-93.
Demireli, E., & Taner, B. (2009). Risk yönetiminde riske maruz değer yöntemleri ve bir uygulama. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 14(3), 127-148.
Deng, K., & Qiu, J. (2021). Backtesting expected shortfall and beyond. Quantitative Finance, 21(7), 1109-1125.
Diebold, F.X. and R.S. Mariano, 1995. Comparing predictive accuracy, Journal of Business & Economic Statistics,13(3), 253–263.
Engle, R.F. and S. Manganelli, 2004, CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles, Journal of Business & Economic Statistics, 22, 367-381
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383-417.
Fissler, T., and J. F. Ziegel, 2016, Higher order elicitability and Osband’s principle, Annals of Statistics, 44(4), 1680-1707.
Hansen, B.E., (1994). Autoregressive Conditional Density Estimation, International Economic Review, 35(3), 705-730.
Koenker, R.W. (2005) Quantile Regression. Cambridge, UK: Cambridge University Press.
Mandelbrot, B. (1963). The variation of certain speculative prices. The Journal of Business, 45(4), 542-543.
Patton, A. J., Ziegel, J. F., & Chen, R. (2019). Dynamic semiparametric models for expected shortfall (and value-at-risk). Journal of Econometrics, 211(2), 388-413.
Rappoport, P. (1993). A new approach: Average Shortfall. JP Morgan Fixed Income Research Technical Document.
Lazar, E., & Xue, X. (2020). Forecasting risk measures using intraday data in a generalized autoregressive score framework. International Journal of Forecasting, 36(3), 1057-1072.
Yamai, Y., & Yoshiba, T. (2005). Value-at-risk versus expected shortfall: A practical perspective. Journal of Banking & Finance, 29(4), 997-1015.