Financial time series analysis in a fuzzy view

Abstract

In financial markets, fuzzy data are always observed. These observations are recorded in the form of intervals. In this paper, we constructed a fuzzy financial time series to describe the dynamic characters of such uncertain observations, tested the stationary of it and then proposed a fuzzy auto-regression model (FAR). We estimated the unknown parameters with Fuzzy Linear Program (FLP) method and gave a principle of evaluating the fitness of the model by using the sample average of the closeness (SAC). An empirical analysis would go to Shanghai Composite Index (SCI), in which we illustrated the modeling of fuzzy financial time series, evaluation of the fitness of the model and the modeling forecast effect. © 2009 Springer Berlin Heidelberg.