policy
advance-time-series-forecasting-with-deep-reinforcement-learning
gavisangavi2502-max · PyTorch
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Overview
Name
advance-time-series-forecasting-with-deep-reinforcement-learning
Author
gavisangavi2502-max
Framework
PyTorch
License
unknown
Skill type
other
Evidence level
untested
Task description
Deep Reinforcement Learning is used to train a trading agent on synthetic financial time-series data. A custom Gym environment models Buy, Sell, Hold decisions. PPO learns to maximize returns vs a moving-average baseline using Sharpe ratio, drawdown, and cumulative profit metrics.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
20anybotics-anymal-cnot in seedalohanot in seedgoogle-barkour-vbnot in seedboston-dynamics-spotnot in seedfranka-fr3not in seedgoogle-barkour-v0not in seedagilex-pipernot in seedberkeley-humanoidnot in seedbitcraze-crazyflie-2not in seedanybotics-anymal-bnot in seedagility-cassienot in seedarx-l5not in seedbooster-t1not in seedfranka-emika-pandanot in seedfranka-fr3-v2not in seeddynamixel-2rnot in seedflexiv-rizon4not in seedassetsnot in seedapptronik-apollonot in seedfourier-n1not in seed
Compatible environments
0No environments list advance-time-series-forecasting-with-deep-reinforcement-learning yet.
Datasets that reference this policy
0No datasets reference advance-time-series-forecasting-with-deep-reinforcement-learning yet.