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On-Demand Forecasting of Stock Prices Using a Real-Time Predictor
July/August 2003 (vol. 15 no. 4)
pp. 1033-1037

Abstract—This paper presents a fuzzy stochastic prediction method for real-time predicting of stock prices. A complete contrast to the crisp stochastic method, it requires a fuzzy linguistic summary approach to computing parameters. This approach, which is found to be better than the gray prediction method, can eliminate outliers and limit the data to a normal condition for prediction, with a comparatively very small deviation of 4.5 percent.

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Index Terms:
Stock price prediction, gray theory, fuzzy theory, stochastic prediction.
Citation:
Yi-Fan Wang, "On-Demand Forecasting of Stock Prices Using a Real-Time Predictor," IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 4, pp. 1033-1037, July-Aug. 2003, doi:10.1109/TKDE.2003.1209017
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