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).

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.