The empirical study of the comparisons of the volatility prediction and the stock price prediction-TXO

In the past, there were many literatures using the historical model and time series model which are based on historical information or implied volatility model to estimate the volatility of stock price. In this thesis, we use the historical model, time series model, and the transfer function model of implied volatility to forecast the volatility and compare the information content and forecasting ability of these models. From the empirical results, time series model performs better than the transfer function model of implied volatility. Besides, from the results of error analysis, among the transfer function models of implied volatility, the at-the-price put option implied volatility model performs better. Moreover, except for the historical volatility model, all models don’t improve their forecasting ability after adding the trading volume in. At the end, we use these models to price the out-of-sample at-the-price TXO. We find that time series model performs the best in pricing call options, and the transfer function model on implied volatility of at-the-price put option performs the best in pricing put options. However, overall, time series model have better forecasting ability towards the volatility of future stock price and also has smaller error in pricing options.