Date Thesis Awarded

5-2021

Access Type

Honors Thesis -- Access Restricted On-Campus Only

Degree Name

Bachelors of Science (BS)

Department

Computer Science

Advisor

Zhenming Liu

Committee Members

Bin Ren

Anh Ninh

Abstract

Many studies have used machine learning techniques, including neural networks, to predict equity returns. This paper uses macroeconomic and fundamental factors, and employs regression analysis and deep learning techniques to build forecasting models for equity returns in the Electric Vehicle market. Our results show that selected macroeconomic and fundamental factors are statistically significant in explaining trends of excess returns. Our deep neural networks achieved great in-sample testing results. Also, the results show that deep neural networks generally outperform shallow neural networks.

Available for download on Wednesday, September 01, 2021

On-Campus Access Only

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