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Thanapol Kurujitkosol. Automated forex trading system using stacked machine learning and technical analysis. Master's Degree(Artificial Intelligence and Internet of Things). Thammasat University. Thammasat University Library. : Thammasat University, 2022.
Automated forex trading system using stacked machine learning and technical analysis
Name: Thanapol Kurujitkosol
keyword:
Financial market prediction
;
Forex
Abstract:
Forex appeals to investors who enjoy the challenge of profiting from market fluctuations. However, it also carries the risk of potential losses. To mitigate these risks, many investors seek tools for predicting price movements. This thesis suggests utilizing Stacking Machine Learning Models with Deep Q-Network to generate automated Forex trading, assisting investors in decision-making and strategy planning. Our experiments involve comparing four major currency pairs using Trading Metrics to evaluate model performance. As experiment results, our model demonstrated profitability and achieved a minimum accuracy of 65% in both Short Trades Won (%) and Long Trades Won (%)
Thammasat University. Thammasat University Library
Address:
BANGKOK
Email:
preserv@tu.ac.th
Name: Sasiporn Usanavasin
Role:
advisor
Created:
2022
Modified:
2023-12-25
Issued:
2023-12-25
วิทยานิพนธ์/Thesis
application/pdf
eng
DegreeName: Master of Engineering
Level: Master's Degree
Descipline: Artificial Intelligence and Internet of Things
Grantor: Thammasat University
©copyrights Thammasat University
RightsAccess:
ใช้เวลา
0.02925 วินาที
Thanapol Kurujitkosol
| Title | Contributor | Type |
|---|---|---|
| Automated forex trading system using stacked machine learning and technical analysis
มหาวิทยาลัยธรรมศาสตร์ Thanapol Kurujitkosol | Sasiporn Usanavasin | วิทยานิพนธ์/Thesis |
Sasiporn Usanavasin