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This doesn't look right to me when I stepped through it. My code includes Interactive Brokers commissions but othewise the same
if action > 0: # buy_stock available_amount = self.account // adj delta_stock = min(available_amount, action) self.stocks[index] += delta_stock if USE_IB_COST: comm = max(delta_stock * TRANSACTION_FEE_PER_SHARE, 1.0) else: comm = (adj * delta_stock) * self.transaction_fee_percent self.account -= adj * delta_stock + comm elif self.stocks[index] > 0: # sell_stock delta_stock = min(-action, self.stocks[index]) if USE_IB_COST: comm = max(delta_stock * TRANSACTION_FEE_PER_SHARE, 1.0) else: comm = (adj * delta_stock) * self.transaction_fee_percent self.account += adj * delta_stock - comm
A typical action value on the 3rd line above is 0.295 while the available_amount is unscaled at say 47778. So action will always be the minimum.
action
available_amount
I assume this is your scaling
state = np.hstack(( self.account * 2 ** -16, self.day_npy * 2 ** -8, self.stocks * 2 ** -12, ), ).astype(np.float32)
Looks like a bug to me. Why not use MinMaxScaler?
The text was updated successfully, but these errors were encountered:
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This doesn't look right to me when I stepped through it. My code includes Interactive Brokers commissions but othewise the same
A typical
action
value on the 3rd line above is 0.295 while theavailable_amount
is unscaled at say 47778. So action will always be the minimum.I assume this is your scaling
Looks like a bug to me. Why not use MinMaxScaler?
The text was updated successfully, but these errors were encountered: