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Применение нейронных сетей для прогнозирования поведения инвесторов на фондовом рынке

Полный текст:


The present study is mainly based on time series of stock prices. In this article, I propose to predict the stock price based on trading behavior of investors. For each stock, we study the trade relations between the investors through the trading network. Then classified network nodes in three ways, according to their wiring diagram, we projected the stock price by the inclusion of these indicators in a neural network based time series stock prices.

Об авторе

В. М. Русаков
Российский экономический университет им. Г.В. Плеханова

Список литературы

1. Fama, E. F. Efficient capital markets II. J. Finance 46, 1575-1617 (1991).

2. Cootner, P. The random character of stock market prices, (MIT Press, 1964).

3. Mantegna, R. N. & Stanley, H. E. Scaling behavior in the dynamics of an economic index.

4. Walczak, S. An empirical analysis of data requirements for financial forecasting with neural networks. J. Manage. Inform. Syst. 17, 203-222 (2001).

5. Cai, S.-M., Zhou, Y-B., Zhou, T. & Zhou, P.-L. Hierarchical organization and disassortative mixing of correlation-based weighted financial networks. Int. J. Mod. Phys. C 21, 433-441 (2010).


Для цитирования:

Русаков В.М. Применение нейронных сетей для прогнозирования поведения инвесторов на фондовом рынке. Путеводитель предпринимателя. 2016;(32):206-214.

For citation:

Rusakov V.M. Prediction of stock price is an important and challenging problem for studying financial markets. Entrepreneur’s Guide. 2016;(32):206-214. (In Russ.)

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ISSN 2073-9885 (Print)
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