The Switching Model in Index Portfolios Leads to Better Performance in Computing ‎Value at Risk

Abstract

We seek to measure the function of the switching model in estimating the value at risk for the formation of index portfolios. The switching model is explicitly designed to solve the risk managers' problem who do not trust a particular value-at-risk model and allows the model to compute the value at risk in different times and conditions. In this study, predictive methods such as EWMA, historical simulation, Monte Carlo and constant variance model will be discussed. This approach is explicitly designed to predict managers' predictive problems who do not contingent their estimates for a specific VaR model, and allows the estimated model to change over time. This approach assumes that investors at any point of time use only the historical information available to select a model, and the choice of model is based on a pre-determined selection criterion, and then the selection model is used to predict value at risk in another date. The results of the research indicate that the switching model is highly desirable compared to other models over time.