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
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