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This study presents contemporaneous modeling of asset return and price rangewithin the framework of stochastic volatility with leverage. A newrepresentation of the probability density function for the price range isprovided, and its accurate sampling algorithm is developed. A Bayesianestimation using Markov chain Monte Carlo (MCMC) method is provided for themodel parameters and unobserved variables. MCMC samples can be generatedrigorously, despite the estimation procedure requiring sampling from a densityfunction with the sum of an infinite series. The empirical results obtainedusing data from the U.S. market indices are consistent with the stylized factsin the financial market, such as the existence of the leverage effect. Inaddition, to explore the model's predictive ability, a model comparison basedon the volatility forecast performance is conducted.

Stochastic volatility model with range-based correction and leverage