A NEW APPROACH OF BIVARIATE FUZZY TIME SERIES ANALYSIS TO THE FORECASTING OF A STOCK INDEX

DOI10.1142/S0218488503002478zbMath1074.91530OpenAlexW2157850792MaRDI QIDQ5696982

Berlin Wu, Yu-Yun Hsu, Szeman Tse

Publication date: 19 October 2005

Published in: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218488503002478

zbMATH Keywords

fuzzy relationfuzzy rule basebivariate fuzzy time seriesfuzzy Markov relation matrixmean absolute forecasting accuracy

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Economic time series analysis (91B84)

Related Items (5)

A new hybrid artificial neural networks and fuzzy regression model for time series forecasting ⋮ Statistical Analysis with Soft Computation for Fuzzy Answering in Sampling Survey ⋮ A FCM-based deterministic forecasting model for fuzzy time series ⋮ Deterministic vector long-term forecasting for fuzzy time series ⋮ AN ENHANCED DETERMINISTIC FUZZY TIME SERIES FORECASTING MODEL

Cites Work

• Unnamed Item
• Fuzzy adaptive control of a first-order process
• Fuzzy time series and its models
• A fuzzy seasonal ARIMA model for forecasting
• Fuzzy sets in a approximate reasoning. I: Inference with possibility distributions
• Detection of change points in time series analysis with fuzzy statistics
• Mining time series data by a fuzzy linguistic summary system
• Heuristic models of fuzzy time series for forecasting

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