Yapısal kırılmalar altında oynaklık öngörümlemesi: İstanbul Menkul Kıymetler Borsası sektör endeksleri örneği

The purpose of this study is to forecast the volatility of the Turkish stock market indices in the presence of structural breaks. The empirical relevance of structural breaks in the volatility of the Istanbul Stock Exchange (ISE) sector indices are examined by conducting GARCH family models in both in-sample and out-of-sample tests.Empirical results indicate the existence of significant structural breaks in the unconditional variance for all the ISE indices, and GARCH parameter estimates differ across subsamples defined by the modified Iterative Cumulative Sum of Squares (ICSS) algorithm indicating instable GARCH processes governing volatility for all of them. In out-of-sample analysis, two different statistical loss functions over forecast horizons of 1, 5, 10, 15, 20, 60, and 120 days are used to compare forecasts of daily stock market index return volatility produced by the econometric models that assume stable GARCH processes to the forecasts generated by the GARCH type of models that accommodate sudden volatility shifts due to the structural breaks in the unconditional variance of daily stock market index returns. It is evidenced that structural breaks are relevant features for the ISE indices and allowing for instabilities in the data leads to forecasting gains. Moreover, empirical findings reveal that decision makers should consider structural breaks as well as sectoral differences in modeling and forecasting stock market volatility in both short-term and long-term. Thus, one should be aware of those facts to reach more accurate conclusions in terms of Value-at-Risk (VaR) calculation, risk management, derivative pricing, and hedging and portfolio allocation.Keywords: Volatility, Structural Breaks, Forecasting, GARCH model, Estimation Window, ISE