Conference Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 17 - Statistics in Finance
Type: Topic Contributed
Date/Time: Sunday, August 7, 2022 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract #323352
Title: Using Bayesian Non-Gaussian Time Series Models for Analysis of Financial Data
Author(s): Refik Soyer*
Companies: George Washington University
Keywords: Financial time series; Particle filtering; Multivariate time series; MCMC

In this talk, we consider a class of multivariate non-Gaussian time series models which can be used for analysis of financial time-series. A key feature of our proposed model is its ability to account for correlations across time as well as across series (contemporary) via a random environment. The proposed modeling approach yields analytically tractable dynamic marginal likelihoods which allow us to develop efficient estimation methods for various settings using Markov chain Monte Carlo as well as sequential Monte Carlo methods. To illustrate our methodology, we use simulated data examples and a real application of multivariate time series for modeling the joint dynamics of stochastic volatility in financial indexes, the VIX and VXN.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2022 program