Analyzing stock market tick data using piecewise nonlinear model
نویسندگان
چکیده
Trading in stock market indices has gained unprecedented popularity in major ®nancial markets around the world. However, the prediction of stock price index is a very dif®cult problem because of the complexity of the stock market data. This study proposes stock trading model based on chaotic analysis and piecewise nonlinear model. The core component of the model is composed of four phases: The ®rst phase determines time-lag size in input variables using chaotic analysis. The second phase detects successive change-points in the stock market data and the third phase forecasts the change-point group with backpropagation neural networks (BPNs). The ®nal phase forecasts the output with BPN. The experimental results are encouraging and show the usefulness of the proposed model with respect to pro®tability. q 2002 Elsevier Science Ltd. All rights reserved.
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ورودعنوان ژورنال:
- Expert Syst. Appl.
دوره 22 شماره
صفحات -
تاریخ انتشار 2002