Bernstein, Jordan2016-09-082016-09-082006http://hdl.handle.net/10012/10828The Independent Studies program closed in 2016. This thesis was one of 25 accepted by Library for long-term preservation and presentation in UWSpace.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.enfuzzy-logicneural networksforecasting theoryeconomic theoryequityshort-term forecasting theoryBachelor Thesis