Essays on the Econometric Analysis of Financial Market Volatility and Mutual Fund Performance

• Main Authors: Erh-Yin Sun, 孫而音
• Other Authors: Huimin Chung
• Format: Others
• Language: en_US
• Online Access: http://ndltd.ncl.edu.tw/handle/44114787839247973601

博士 === 國立交通大學 === 財務金融研究所 === 96 === This dissertation consists of two separate issues. The first issue is to discuss the forecasting performance of HAR and MIDAS regression models of realized range-based volatility; we focus on the S&P 500 index. The empirical results show that the realized range-based volatility is more efficient than the realized return-based volatility; the regressors consisting of the continuous sample path and jump variability measures in the HAR and MIDAS regressions predict the future realized range volatilities, and thus dominate almost in all MSE terms. In addition, the realized range-based regressions are significant for short-run volatility forecasting, but the realized return-based regressions are almost invariant to jumps. Furthermore, we will employ the HAR and MIDAS regressions as encompassing regressions to examine the information content of the continuous and jump components of the realized range-based volatility, and the additional information content of the implied volatility as an additional regressor. We use the VIX as the measure of the implied volatility. We find that the implied volatility has a high information content and the past continuous components feature relevant information content by the implied volatility. Besides, the jump components do not contribute to future valuable information. The second issue is to detect mutual fund market timing abilities, using the threshold regression model. The empirical results show that the traditional Henriksson and Merton (1981) model is only a special case within our model, and we demonstrate the potential bias of using the traditional model, arguing that it tends to underestimate the market-timing effect. Indeed, we find that the use of the traditional market timing test may provide misleading results in some circumstances; thus, our proposed threshold model provides more accurate inferences on the market-timing effects of mutual funds.