Zhengyao Jiang

Thanks for your contribution again! > Adding support for additional layers such as Batch Normalization and ReLU Yes, this makes sense. > Support for multiple pre-configured networks in net_config.json. For...

We have two guesses about this: 1. the agent perform worse when there are big differences in the market. The agent bases its decision on the history of the market....

> It seems the framework does not support volume feature. Is there any reason that the framework can not support volume feature? I think volume feature is very important to...

> However, it seems that such loss function only contains instantaneous reward, not average cumulated reward. If there is no commission fee, when the action won't affect the state transition,...

https://github.com/ZhengyaoJiang/GradientInduction/blob/b762f18e3313e67b31b5f3bc5d0103fcee112778/core/induction.py#L36

Greetings, Thanks for your effort. Yes, the agent will perform badly in particular hyper-parameter settings. Also, it's nice for you to do further test rather blindly believe the results we...

@dlacombejr Hi, My interpretation of this is reserving BTC is not a wise decision when the agent aims to maximize expectations. Since the btc_bias is fixed to 0, the agent...

@dlacombejr Hi, Thanks for your contribution! One thing I want to mention is, in order to see loss value or gradients on training set, we should turn the "fast_train" in...

@dlacombejr About the growing voting value. It seems that it only happens on the test set:  This shows that the agent thinks the test data is more promising than...

> Still no luck on getting non-zero cash bias values during backtesting. Any thoughts on this? So as I claimed before, I think that the agent doesn't reserve cash because...