Graduation Semester and Year
2022
Language
English
Document Type
Thesis
Degree Name
Master of Science in Industrial Engineering
Department
Industrial and Manufacturing Systems Engineering
First Advisor
Shouyi Wang
Abstract
Financial market analysis is process of analyzing market closely and predict the next move of market whether it will go up or down using historical data. Financial market is stochastic and has rapid changes over time, therefore it is very difficult to predict. The main goal of this work is to understand novel approaches of machine learning in finance, data parsing techniques, labelling the financial data. Furthermore, understand state of art Transformer model and implement and compare results with other traditional machine learning algorithms. Experiment carried out in python along with pytorch.
Keywords
Triple barrier method, Transformer, Deep learning, Machine learning, Multivariate time series, Data sampling
Disciplines
Engineering | Operations Research, Systems Engineering and Industrial Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Deshpande, Abhijit Anand Anand, "Exploring Deep Learning in Finance" (2022). Industrial, Manufacturing, and Systems Theses. 10.
https://mavmatrix.uta.edu/industrialmanusys_theses/10
Comments
Degree granted by The University of Texas at Arlington