Variable dimension via stochastic volatility model using FX rates |
| |
Authors: | Wantanee Surapaitoolkorn |
| |
Institution: | Sasin Graduate Institution of Business Administration of Chulalongkorn University , Chula Soi 12, Pathumwan, Bangkok , 10330 , Thailand |
| |
Abstract: | In this paper, changepoint analysis is applied to stochastic volatility (SV) models which aim to understand the locations and movements of high frequency FX financial time series. Bayesian inference using the Markov Chain Monte Carlo method is performed using a process called variable dimension for SV parameters. Interesting results are that FX series have locations where one or more positions of the sequence correspond to systemic changes, and overall non-stationarity, in the returns process. Furthermore, we found that the changepoint locations provide an informative estimate for all FX series. Importantly in most cases, the detected changepoints can be identified with economic factors relevant to the country concerned. This helps support the fact that macroeconomics news and the movement in financial price are positively related. |
| |
Keywords: | changepoint analysis variable dimension process stochastic volatility model Bayesian computation MCMC FX rates |
|
|