The objective of economic analysis is to interpret the past, 
present or future economic state by analyzing economical data.
In many cases an economic analysis is pursued based on the time-series data.
Time-series analysis is a central tool to analyze time-series data. 

Nevertheless, economic systems are a complex system resulted 
from human behaviors and related to many factors.
When the system includes much uncertainty such as ones of human behaviors, 
it is better to employ methodologies of a fuzzy system in the analysis.

In this paper, we compare the characteristic 
between two fuzzy time-series models 
which are a fuzzy AR (autoregressive) model proposed 
by Ozawa et al and fuzzy autocorrelation model 
by Yabuuchi and Watada.
Both models are built on the basis of the concepts of fuzzy systems.
In the analysis of the Nikkei Stock Average, 
we compare the effectiveness and meaning between both the models.