Date of Award
1999
Document Type
Thesis
Publication Status
Version of Record
Submission Date
October 2026
Thesis/Dissertation Advisor [Chair]
Pandya, Abhijit S.
Abstract
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.
Extent
140 p.
Recommended Citation
Shah, Trupti U., "new methodology to predict certain characteristics of stock market using time-series phenomena" (1999). Electronic Theses and Dissertations 1990 - 1999. 1498.
https://digitalcommons.fau.edu/etd_general_4/1498
Identifier
FADT15677
Comments
College of Engineering and Computer Science|FAU Electronic Theses and Dissertations Collection|Thesis (M.S.)--Florida Atlantic University, 1999.|College of Engineering and Computer Science