کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
474338 | 698866 | 2005 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market](/preview/png/474338.png)
چکیده انگلیسی
Evidence exists that emerging market stock returns are influenced by a different set of factors than those that influence the returns for stocks traded in developed countries. This study uses artificial neural networks to predict stock price movement (i.e., price returns) for firms traded on the Shanghai stock exchange. We compare the predictive power using linear models from financial forecasting literature to the predictive power of the univariate and multivariate neural network models. Our results show that neural networks outperform the linear models compared. These results are statistically significant across our sample firms, and indicate neural networks are a useful tool for stock price prediction in emerging markets, like China.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Operations Research - Volume 32, Issue 10, October 2005, Pages 2499–2512
Journal: Computers & Operations Research - Volume 32, Issue 10, October 2005, Pages 2499–2512
نویسندگان
Qing Cao, Karyl B. Leggio, Marc J. Schniederjans,