I'm currently working on optimizing a mutual fund portfolio, but I'm encountering a common issue where there's a delay in trade processing by brokers, typically ranging from 1 day to 1 week. This delay prevents users from optimizing their portfolios on a daily basis.
I'm seeking suggestions for potential solutions to this problem. Should I consider modifying how the 'reward' is calculated or adjust the model training process?
One idea I have is to introduce a variable for setting the purchase delay and determining the frequency at which users can optimize their portfolios.
As I'm new to reinforcement learning, I'm also looking for resources or methods to better understand this technique. Any guidance or recommendations would be greatly appreciated.
I'm currently working on optimizing a mutual fund portfolio, but I'm encountering a common issue where there's a delay in trade processing by brokers, typically ranging from 1 day to 1 week. This delay prevents users from optimizing their portfolios on a daily basis.
I'm seeking suggestions for potential solutions to this problem. Should I consider modifying how the 'reward' is calculated or adjust the model training process? One idea I have is to introduce a variable for setting the purchase delay and determining the frequency at which users can optimize their portfolios.
As I'm new to reinforcement learning, I'm also looking for resources or methods to better understand this technique. Any guidance or recommendations would be greatly appreciated.