| Summary: | 博士 === 國立交通大學 === 財務金融研究所 === 96 === This study contains two essays on the Bayesian threshold model in financial markets.
In essay 1, we propose a Bayesian three-regime threshold four-factor model to compare the asymmetric risk adjustment between the transitions from neutral to downside markets and those from neutral to upside markets and investigate the performance of mutual funds in changing market conditions. We show that not only fund managers have asymmetric timing ability but three-regime models are more powerful and exhibit significant timing ability more often than two-regime models. In addition, we use panel data model to examine fund investors’ behavior and the relationships between fund performances and characteristics. Empirical results suggest that investor’s behavior is positively associated with past selectivity performances and fund sizes, while it is negatively correlated to past turnover, load charges and expenses. In addition, funds with large contemporaneous net cash flows will results in better upside market timing ability but worse downside market timing ability.
Essay 2 proposes a robust multivariate threshold vector autoregressive (VAR) model with generalized autoregressive conditional heteroskedasticities (GARCH) and dynamic conditional correlations (DCC) to describe conditional mean, volatility and correlation asymmetries in financial markets. In addition, the threshold variable for regime switching is formulated as a weighted average of endogenous variables to eliminate excessively subjective belief in the threshold variable decision and to serve as the proxy in deciding which market to be the price leader. Estimation is performed using Markov chain Monte Carlo (MCMC) methods. Furthermore, several meaningful criteria are introduced to assess the forecasting performance in conditional covariance matrix. The proposed methodology is illustrated using two data sets including daily S&P500 futures and spot prices, and S&P500 and Nasdaq100 spot prices.
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