Method of recovering the real value of a stock from the stock pricing data

Patent 6415268 Issued on July 2, 2002. Estimated Expiration Date:

October 8, 2019. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.

Abstract Claims Description Full Text

Patent References

Predictive neural network means and method for selecting a portfolio of securities wherein each network has been trained using data relating to a corresponding security Patent #: 5761442
Issued on: 06/02/1998
Inventor: Barr, et al.

Inventor

Korisch, Semmen I.

Application

No. 414166 filed on 10/08/1999

Examiners

Primary: Hafiz, Tariq R.
Assistant: Meinecke-Diaz, Susanna

Foreign Patent References

408197872 JP. 08/13/1996

International Class

G06F 017/60

Abstract

A method of recovering the real value of a stock from the stock pricing data collected in a stock market and related ways of selecting stocks in the market are described. The method involves the steps of separating stock pricing data into two components. The first one represents the real value of a stock because it is firmly linked with financial fundamentals of an underlying enterprise. The second one is a random function of time, herein referred to as the noise wave of a stock. The real stock value is represented by a function of time, herein referred to as the value function of a stock. The value function of a stock represents the trend of appreciation of a stock in a stock market. The growth rate of the value function of a stock is introduced as a measure of appreciation of an investment in a stock. A measure of risk of an investment in a stock is introduced as a function of ordinates of the noise wave of the stock. An integral indicator of investment value of a stock is introduced and proven effective for selecting individual stocks or components for a portfolio of stocks.

Other References

Omes et al., "A Neural Network that Explains as Well as Predicts Financial Market Behavior," Computational Intelligence for Financial Engineering (CIFEr), Proceedings of IEEE/IAFE, pp. 43-49, Mar. 24-25, 1997.
Trippi et al. (eds.), Neural Networks in Finance and Investing, McGraw-Hill, Chapter 24, 1996.
Hong et al., "Conservative Thirty Calender Day Stock Prediction Using a Probabilistic Neural Network," Applied Computational Intelligence Laboratory, IEEE, 1995.
Wuthrich et al., "Daily Stock Market Forecast From Textual Web Data," IEEE International Conference on Systems, Man, and Cybernetics, vol. 3, pp. 2720-2725, 1998.
Takahashi et al., "Multiple Line-Segments Regression for Stock Prices and Long-Range Forecasting System by Neural Network," Proceedings of the 37^th SICE Annual Conference, pp. 1127-1132, 199