The Optimal Forecasting Modeling in the VIX Index ofTXO：Application of the CARR Model

• Main Authors: Chun-Kai Liang, 梁竣剴
• Other Authors: Yu-Chen Tu
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/59343199790072186975

碩士 === 銘傳大學 === 財務金融學系碩士班 === 98 === The studies have mostly measured by the standard deviation of close prices in Previous. We use time series（like ARIMA、GARCH）to catch leptokurtic and fat tail of Reward of Financial assets. Parkinson (1980) forcefully argues and demonstrates the superiority of using range as a volatility estimator as compared with standard methods. Then , Chou（2002）provided the Conditional Autoregressive Range Model (CARR) which is the range Combined with the GARCH mondel.In this experimental , the CARR model outperforms than GARCH model both in in-sample and out-of sample forecasts of weekly stock market volatilities. In recent years, the option of stock index in Taiwan , its trading volume was growing rapidly, and the option price is closely related to its volatility, and Taiwan Futures Exchange has been officially available VIX index for investors. So, the purpose of this study is to establish the Optimal Forecasting Modeling in the VIX Index of TXO. This applies the following six single models, such as ARIMA model, ARIMAX model, ARIMA-GARCH model, ARIMAX-GARCH model, ARIMA-CARR model, ARIMAX-CARR model. Compare real volatility index with the above six models and them forecast performance. By comparing the forecasting performance of the volatility form the above six models mentioned, ARIMAX-CARR model which adds Exogenous（the rate of change of volume of TWSE） ranked the best.