This paper introduces a new way of estimating parameters in a Brownian motion regime switching asset model to incorporate volatility clustering. The regime switching model is then applied to pricing of up-and-in barrier call options. We take probability of crossing the barrier between simulation points into account, and we increase accuracy in simulations by importance sampling. The regime switching model is compared to the Normal Inverse Gaussian model and the traditional Black and Scholes model, and option prices from the regime switching model is compared to the closed form expression of up-and-in barrier calls in a Black and Scholes market.