Title

Using Neural Networks and Technical Indicators for Generating Stock Trading Signals

Abstract

Technical analysis is a common method used by financial managers and traders to predict buy and sell trading signals for individual stocks. Unfortunately, it is often the case that each trader, based on their own level of expertise, will have a different way of interpreting an indicator, or identifying the time series trend that is currently presented by the stock's price history. This study involves training feed-forward neural networks to generate buy and sell trading signals. The predictability and profitability results given by the trained neural networks (with both discrete and fuzzified technical indicators) are compared against rule-based models of the technical indicators, as well as a standard benchmark buy-and-hold strategy.

Department(s)

Engineering Management and Systems Engineering

Keywords and Phrases

Neural Networks; Stock Trading; Trading Signals

Library of Congress Subject Headings

Stocks

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2002 American Society of Mechanical Engineers (ASME), All rights reserved.

This document is currently not available here.


Share

 
COinS