Forecasting the Behavior of the Global Market Price Using Markov Chain of the Fuzzy States - Case study: gold price

Abstract

The estimation regarding to the return rate of global market prices has been one of the most popular topics for the financial area due to its high return. In this work we consider gold prices as case study. Closing retraction Rt is studied as a fuzzy concept and several types of fuzzy numbers are applied to Rt : triangle, trapezoidal, parabolic, and K Trapezoidal-Triangular fuzzy numbers. We create a Markov chain model (MC) and a Markov model with fuzzy states (MCFS) and compare between them. The two models MC and MCFS are used to predict for long run time. At the end, we estimate the expected return price in specific months. Whereas, the MCFS model has more accurate results than the MC model. In this work Excel is used to process the data and the MATLAB is used for other calculations.