SYSTEM AND METHOD FOR AUTOMATED STOCK MARKET OPERATION
First Claim
1. A method of predicting the value of a stock, comprising:
- i) inputting M previous time period values for the stock into a M-order finite impulse response (FIR) filter, the M-order finite impulse filter having a filter order M, a least mean square (LMS) prediction algorithm with step-size mu, and M adjustable filter coefficients;
ii) obtaining an output from the M-order FIR filter, the output from the M-order FIR filter being a predicted next time period value for the stock;
iii) comparing the predicted next time period value for the stock with an actual next time period value for the stock to calculate a prediction error;
iv) inputting the calculated prediction error into an adaptive algorithm to obtain an adjustment for the M adjustable filter coefficients; and
v) applying the adjustment for the M adjustable filter coefficients and repeating all steps until halted.
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Abstract
A system and method for automated stock market investment. In an embodiment, the method includes: i) inputting M previous time period values for the stock into a M-order finite impulse response (FIR) filter, the M-order finite impulse filter having a filter order M, a least mean square (LMS) prediction algorithm with step-size mu, and M adjustable filter coefficients; ii) obtaining an output from the M-order FIR filter, the output from the M-order FIR filter being a predicted next time period value for the stock; iii) comparing the predicted next time period value for the stock with an actual next time period value for the stock to calculate a prediction error; iv) inputting the calculated prediction error into an adaptive algorithm to obtain an adjustment for the at least one adjustable filter coefficient; and v) applying the adjustment for the at least one adjustable filter coefficient and repeating all steps until halted.
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Citations
20 Claims
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1. A method of predicting the value of a stock, comprising:
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i) inputting M previous time period values for the stock into a M-order finite impulse response (FIR) filter, the M-order finite impulse filter having a filter order M, a least mean square (LMS) prediction algorithm with step-size mu, and M adjustable filter coefficients; ii) obtaining an output from the M-order FIR filter, the output from the M-order FIR filter being a predicted next time period value for the stock; iii) comparing the predicted next time period value for the stock with an actual next time period value for the stock to calculate a prediction error; iv) inputting the calculated prediction error into an adaptive algorithm to obtain an adjustment for the M adjustable filter coefficients; and v) applying the adjustment for the M adjustable filter coefficients and repeating all steps until halted. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for predicting the value of a stock, comprising:
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means for inputting M previous time period values for the stock into a M-order finite impulse response (FIR) filter, the M-order finite impulse response filter having a filter order M, a least mean square (LMS) prediction algorithm with step-size mu, and M adjustable filter coefficients; means for obtaining an output from the M-order FIR filter, the output from the M-order FIR filter being a predicted next time period value for the stock; means for comparing the predicted next time period value for the stock with an actual next time period value for the stock to calculate a prediction error; means for inputting the calculated prediction error into an adaptive algorithm to obtain an adjustment for the M adjustable filter coefficients; and means for applying the adjustment for the at least one adjustable filter coefficient and repeating all steps until halted. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A data processor readable medium storing data processor code that when loaded onto and executed by a data processing device adapts the device to perform a method of predicting the value of a stock, the data processor readable medium comprising:
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code for inputting M previous time period values for the stock into a M-order finite impulse response (FIR) filter, the M-order finite impulse filter having a filter order M, a least mean square (LMS) prediction algorithm with step-size mu, and M adjustable filter coefficients; code for obtaining an output from the M-order FIR filter, the output from the M-order FIR filter being a predicted next time period value for the stock; code for comparing the predicted next time period value for the stock with an actual next time period value for the stock to calculate a prediction error; code for inputting the calculated prediction error into an adaptive algorithm to obtain an adjustment for the at least one adjustable filter coefficient; and code for applying the adjustment for the at least one adjustable filter coefficient and repeating all steps until halted. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification