کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10325266 | 666673 | 2005 | 31 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A hybrid genetic-neural architecture for stock indexes forecasting
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A hybrid genetic-neural architecture for stock indexes forecasting A hybrid genetic-neural architecture for stock indexes forecasting](/preview/png/10325266.png)
چکیده انگلیسی
In this paper, a new approach for time series forecasting is presented. The forecasting activity results from the interaction of a population of experts, each integrating genetic and neural technologies. An expert of this kind embodies a genetic classifier designed to control the activation of a feedforward artificial neural network for performing a locally scoped forecasting activity. Genetic and neural components are supplied with different information: The former deal with inputs encoding information retrieved from technical analysis, whereas the latter process other relevant inputs, in particular past stock prices. To investigate the performance of the proposed approach in response to real data, a stock market forecasting system has been implemented and tested on two stock market indexes, allowing for account realistic trading commissions. The results pointed to the good forecasting capability of the approach, which repeatedly outperformed the “Buy and Hold” strategy.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 170, Issue 1, 18 February 2005, Pages 3-33
Journal: Information Sciences - Volume 170, Issue 1, 18 February 2005, Pages 3-33
نویسندگان
G. Armano, M. Marchesi, A. Murru,