This paper proposes a Bayesian approach t o a v ector autoregression with stochastic volatility, where the multiplicative e v olution of the precision matrix is driven by a m ultivariate beta variate.Exact updating formulas are given to the nonlinear ltering of the precision matrix.Estimation of the autoregressive parameters requires numerical methods: an importance-sampling based approach is explained here.i