The Wishart Autoregressive process of multivariate stochastic volatility

A-Tier
Journal: Journal of Econometrics
Year: 2009
Volume: 150
Issue: 2
Pages: 167-181

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

The Wishart Autoregressive (WAR) process is a dynamic model for time series of multivariate stochastic volatility. The WAR naturally accommodates the positivity and symmetry of volatility matrices and provides closed-form non-linear forecasts. The estimation of the WAR is straighforward, as it relies on standard methods such as the Method of Moments and Maximum Likelihood. For illustration, the WAR is applied to a sequence of intraday realized volatility-covolatility matrices from the Toronto Stock Market (TSX).

Technical Details

RePEc Handle
repec:eee:econom:v:150:y:2009:i:2:p:167-181
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-25