Stock Market Forecasting Using Time Invariant Fuzzy Time Series Model

Authors

  • R. Sasikumar
  • A. Sheik Abdullah

DOI:

https://doi.org/10.37591/rrjost.v7i1.1475

Abstract

Stock market volatility is an important for investment, option pricing and financial market regulation. In recent years a different types of models which apparently predict changes in stock market prices have been introduced. There are many methods in the literature to solve the problem of future prediction. The present study provides a foundation for the development and application of fuzzy time series model for short term investor as well as long term investors. From the empirical results, our approach is useful in real world applications where forecasting stock prices is useful in order to make investment decisions for investor.

 

Keywords: Fuzzy time series, fuzzy sets, linguistic variables, stock market

Cite this Article

R. Sasikumar, A. Sheik Abdullah. Stock Market Forecasting Using Time Invariant, Fuzzy Time Series Model. Research & Reviews: Journal of Statistics. 2018; 7(1): 104s–111sp.

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Published

2018-10-31

Issue

Vol. 7 No. 1 (2018)

Section

Review Article

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