Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
A comparison of a factor-based investment strategy and machine learning for predicting excess returns on the JSE
This study investigated the application of Machine Learning to portfolio selection by comparing the application of a Factor Based Investment strategy to one using a Support Vector Machine performing a classification task. The Factor Based Strategy uses regression in order to identify factors correla...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Computer Science
2020
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
Similar Items: A comparison of a factor-based investment strategy and machine learning for predicting excess returns on the JSE
- An analysis of the performance and interpretability of machine learning classification algorithms to predict long-term share returns on the JSE
- A comparative analysis of machine learning models for forecasting JSE Stock Returns
- A comparative study of recurrent neural networks and statistical techniques for forecasting the stock prices of JSE-listed securities
- A Comparison Between Machine Learning Techniques to Find Leaks in Pipe Networks
- Dualisms in modernity : a machine for learning in
- Quality factors explaining returns on the FTSE/JSE All-Share