GARCH-type forecasting models for volatility of stock market and MCS test |
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| Authors: | Lingling Luo Sattayatham Pairote Ratthachat Chatpatanasiri |
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| Institution: | 1. School of Mathematics, Institute of Science, Suranaree University of Technology, Muang District, Nakhon Ratchasima, Thailand;2. School of Mathematics and Statistics, Guizhou University of Finance and Economics, Guizhou, China |
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| Abstract: | The prediction of time-changing volatility is an important task in the modeling of financial data. In the paper, a comprehensive analysis of the mean return and conditional variance of SSE380 index is performed to use GARCH, EGARCH and TGARCH models with Normal innovation and Student's t innovation. Conducting a bootstrap simulation study which shows the Model Confidence Set (MCS) captures the superior models across a range of significance levels. The experimental results show that, under various loss functions, the GARCH using Student's t innovation model is the best model for volatility predictions of SSE380 among the six models. |
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| Keywords: | GARCH-type MCS test SSE380 Volatility |
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