Abstract
A Bayes Study of Extended Auto Regressive Model with Stochastic Volatility
by
Praveen Kumar Tripathi
This paper proposes an extension of the autoregressive (AR) model with stochastic volatility error. It then provides the Bayes analysis of the proposed model using vague priors for the parameters of the conditional mean equation and informative prior for the conditional volatility equation. The Gibbs sampler with intermediate Metropolis steps is used to find the desired posterior samples to draw the posterior based inferences for the relevant model parameters. The data set on exchange rate of Indian rupees relative to US dollar is considered for numerical illustration. The data are used after assuring the stationarity behaviour by differencing the same once. The retrospective short term predictions of the data are provided based on the different components of the general AR process. The results are found satisfactory.
Committee
Workshop
Key Dates
Communication
First Conference Link