Optimal Combination of Trading Rules Using Neural Networks

Subrata Kumar Mitra

Abstract


A large number of trading rules based on technical analysis of prices are being used by investing community for generating trading signals for short term investments. As profitability of these trading rules vary, it is not easy to judge which particular rule really ‘works’. Instead of a single trading rule, combination of rules are likely to offer the portfolio benefits of better risk adjusted return and hence, an experiment is carried out to combine signals generated from of moving averages of different window size using an artificial neural network.  It is observed that the risk adjusted performance measure of the artificial neural network based trading model is better than that of simple ‘Buy and Hold’ strategy.

Full Text: PDF DOI: 10.5539/ibr.v2n1p86

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

International Business Research  ISSN 1913-9004 (Print), ISSN 1913-9012 (Online)

Copyright © Canadian Center of Science and Education

To make sure that you can receive messages from us, please add the 'ccsenet.org' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.