The goal of this study is to investigate the performance of the Markov regime switching autoregressive (MRS-AR) model to estimate and forecast the gold prices in Pakistan. Initial analysis of the data covering from January 1995 to January 2019 reveals the existence of nonstationarity, heteroscedasticity, and structural changes. The dynamics of the data are studied in two distinct regimes. The empirical analysis provides evidence that the regime shifts are mattered and MRS-AR model is found to be suitable even in the case of nonstationarity. Moreover, it is worthwhile to note that the Markov regime switching successfully captures the nonlinearities and heteroscedasticity underlying the selected data and provides efficient forecasts. Based on empirical evidence it is recommended that the applications of regime switching models should be promoted in other fields of life.
Inference for Markov Regime-Switching Models of Electricity Spot Prices
