Forecasting Taiwan Stock Index Futures Trends and ConstructingTrading Strategies Using Machine Learning
| Autor: | Hao-Hsin Hsu, 許顥馨 |
|---|---|
| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 Forecasting the dynamics of financial market has always been a problem that many investors and researchers try to solve. In this research, we tried to build a stable model to predict market trends through machine learning, and used this model to design a strategy that can make profits in Taiwan stock index futures. First, we selected three different machine learning models: logistic regression, random forest and LSTM, and divided the trend into three categories: upward trend, downward trend and consolidation trend. Next, we selected the most suitable model from them. Afterwards, we tried to find the timings of buying in these trends. Therefore, we used dynamic programming to label all of the best timings of buying from historical data. Then, we used the aforementioned three models for training to predict the timings of buying and chose the model with the best performance. Finally, we combined the two models together to build a profitable strategy, and used several technical indicator strategies to compare the model designed in this study. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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