EVALUATION OF STOCK OPTION PRICES BY USING THE PREDICTION OF FRACTAL TIME-SERIES

Abstract

This report deals with the prediction method for the time-series bearing fractal geometry. The method is applied to the forecast of stock price and option premium, and the results show better performance of investment compared to the conventional methods. At first, the time series is represented by the convolution of the impulse response expanded by a set of scaling function and the input signal. Then, by using the time scale expansion, future stock prices are estimated. An indicator showing whether the stock price is fractal is also shown.