I was looking for examples of market trading environments for OpenAI for an idea I had around machine learning for risk management (I don't think you can teach a computer to trade on random walk data better than you can teach a human - it's like locking both in a box and hoping they can make money) but what I am hoping you can do is teach them risk management/position sizing based on prevailing market conditions which has much more useful applications.
Hooking OpenAI into Backtrader turns out to be more than I could hope for.
Just one issue I ran into which might be worth noting for others or updating your documentation...
When running your examples they all (or at least all the ones I tried) log "No running server found." then exit.
The issue is that you haven't got an agent running. It might be worth demonstrating a basic agent. Eg:
env = ..........
env.reset()
for _ in range(1000):
env.render()
env.step(env.action_space.sample()) # take a random action
Hi,
Great work.
I was looking for examples of market trading environments for OpenAI for an idea I had around machine learning for risk management (I don't think you can teach a computer to trade on random walk data better than you can teach a human - it's like locking both in a box and hoping they can make money) but what I am hoping you can do is teach them risk management/position sizing based on prevailing market conditions which has much more useful applications.
Hooking OpenAI into Backtrader turns out to be more than I could hope for.
Just one issue I ran into which might be worth noting for others or updating your documentation...
When running your examples they all (or at least all the ones I tried) log "No running server found." then exit.
The issue is that you haven't got an agent running. It might be worth demonstrating a basic agent. Eg:
env = .......... env.reset() for _ in range(1000): env.render() env.step(env.action_space.sample()) # take a random action