TY - THES A1 - Liu, Francis T1 - A Deep Reinforcement Learning Agent Using Multiple Assets Financial Signals for Portfolio Management N2 - In this study, we investigated possible applications of reinforcement learning in the area of portfolio management. Aa specific topology of reinforcement learning is choosen to study the feasibility, Deep Deterministic Policy Gradient (DDPG), to train neural networks to perform trade in an environment simulated real world trading. The results show that the DDPG agent is able to learn price pattern and perform profitable trades. In single stock backtest, the DDPG is able to generate an annual return of 7%. While in multiple stocks backtest, DDPG agent can generate an annual return of 12%. KW - Machine learning KW - Convolutional Neural Networks KW - Algorithmic Trading KW - Reinforcement Learning KW - Portfolio Management KW - Active Portfolio Management KW - Optimization on Continuous action Space Y1 - 2019 UR - https://opus4.kobv.de/opus4-hwr/frontdoor/index/index/docId/1735 ER -