Forecasting Financial Markets Using Neural Networks: An Analysis of Methods and Accuracy by Jason E. Kutsurelis

Forecasting Financial Markets Using Neural Networks: An Analysis of Methods and Accuracy



Download Forecasting Financial Markets Using Neural Networks: An Analysis of Methods and Accuracy




Forecasting Financial Markets Using Neural Networks: An Analysis of Methods and Accuracy Jason E. Kutsurelis
Language: English
Page: 82
Format: pdf
ISBN: 1423557301, 9781423557302
Publisher: Storming Media

This is a NAVAL POSTGRADUATE SCHOOL MONTEREY CA report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A500553. The abstract provided by the Pentagon follows: This research examines and analyzes the use of neural networks as a forecasting tool. Specifically a neural network's ability to predict future trends of Stock Market Indices is tested. Accuracy is compared against a traditional forecasting method, multiple linear regression analysis. Finally, the probability of the model's forecast being correct is calculated using conditional probabilities. While only briefly discussing neural network theory, this research determines the feasibility and practicality of using neural networks as a forecasting tool for the individual investor. This study builds upon the work done by Edward Gately in his book Neural Networks for Financial Forecasting. This research validates the work of Gately and describes the development of a neural network that achieved a 93.3 percent probability of predicting a market rise, and an 88.07 percent probability of predicting a market drop in the S&P500. It was concluded that neural networks do have the capability to forecast financial markets and, if properly trained, the individual investor could benefit from the use of this forecasting tool.

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