I Don't Care Whose Fault It Is! Or, An Introduction to the Short-Term Forecasting Theory, Implementing Fuzzy-logic and Neural Networks

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Date

2006

Authors

Bernstein, Jordan

Advisor

Vetzal, Ken
Perez, Alonzo

Journal Title

Journal ISSN

Volume Title

Publisher

University of Waterloo

Abstract

In contradiction with much conventional economic theory, this thesis argues that successful short-term forecasting is both possible and practicable. Beginning with the assumption, and widely-held belief, that there are patterns to be discovered in the stock market, the thesis develops the Short-Term Forecasting Theory (STFT) to demonstrate how useful and accurate short-term forecasts might be achieved. In short, this thesis posits that, if short-term financial forecasting of an equity can be broken down to a mechanical procedure, the problem of short-term forecasting is reduced to the question of finding the proper tools for this procedure. This thesis presents two computing methods – fuzzy logic and neural networks – that, when combined, could serve as an appropriate tool for implementation.

Description

The Independent Studies program closed in 2016. This thesis was one of 25 accepted by Library for long-term preservation and presentation in UWSpace.

Keywords

fuzzy-logic, neural networks, forecasting theory, economic theory, equity, short-term forecasting theory

LC Keywords

Citation