Range-based volatility modeling in financial markets using a family of scale mixtures of Birnbaum-Saunders distribution

Abstract

We propose scale mixtures of Birnbaum-Saunders distributions as a new class of positive skewed and leptokurtic distributions and use it to model volatility in stock markets. To estimate the model parameters, we develop an Expectation-Conditional-Maximization algorithm. The numerical performance of the proposed methodology is evaluated by means of Monte Carlo simulations. Application of the new model in volatility modeling is illustrated with some real-life data.