-
- Tác giả: Võ Minh Hiếu
- Thông tin XB: TP Hồ Chí Minh: Trường Đại học Ngoại thương, 2024
- Mô tả vật lý: 91 p.
- Tóm tắt: This study adapts and fine-tunes the Policy Gradient Portfolio (PGPortfolio), a reinforcement learning-based model, for the Vietnamese stock market. It addresses unique market characteristics like the T+2 settlement period and high commission fees, using data from 2018 to 2023. The results indicate that the adapted model can outperform certain passive fund benchmarks despite high transaction costs and liquidity constraints, although the integration of technical indicators shows limited impact, with ...
- Từ khóa: Portfolio management; Deep reinforcement learning; Policy gradient portfolio; Vietnam stock market
- Chế độ xem
- 63
Tìm kiếm thêm
