Bayesian inference for volatility models in financial time series

Wantanee Surapaitoolkorn
The aim of the thesis is to study the two principal volatility models used in ¯nancial time series, and to perform inference using a Bayesian approach. The ¯rst model is the Deterministic Time-Varying volatility represented by Autoregressive Conditional Heteroscedastic (ARCH) models. The second model is the Stochastic Time Varying volatility or Stochastic Volatility (SV) model. The thesis concentrates on using Financial Foreign Exchange (FX) data including time series for four Asian countries of Thailand, Singapore,...
This data repository is not currently reporting usage information. For information on how your repository can submit usage information, please see our documentation.