A new methodology to predict certain characteristics of stock market using time-series phenomena |
Posted on:2000-06-02 | Degree:M.S | Type:Thesis |
University:Florida Atlantic University | Candidate:Shah, Trupti U | Full Text:PDF |
GTID:2469390014965076 | Subject:Economics |
Abstract/Summary: | |
The goal of time series forecasting is to identify the underlying pattern and use these patterns to predict the future path of the series. To capture the future path of a dynamic stock market variable is one of the toughest challenges.; This thesis is about the development of a new methodology in financial forecasting. An effort is made to develop a neural network forecaster using time-series phenomena. The main outcome of this new approach for financial forecasting is a systematic way of constructing a Neural Network Forecaster for nonlinear and non-stationary time-series data that leads to very good out-of-sample prediction.; The tool used for the validation of this research is "Brainmaker". This thesis also contains a small survey of available tools used for financial forecasting. |
Keywords/Search Tags: | Forecasting, New, Time-series |
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