A Bayesian estimation procedure is developed for estimating multiple regime vector autoregressive models appropriate for deviations from financial arbitrage relationships. This approach has clear advantages over classical stepwise threshold autoregressive analysis.

This study proposes a new approach to the estimation of daily volatility. This approach is different ( in the sense of using all available intraday price data) and unbiased ( in the sense of accounting for the high levels of autocorrelation found in intraday price data).