I was going through this algorithm from the docs and I quite understand it but theres something that I cant just get my head around. When it says
'''
Enter or exit positions based on relationship of the open price of the current bar and the prices defined by the machine learning model.
Liquidate if the open price is below the sell price and buy if the open price is above the buy price
'''
for holding in self.Portfolio.Values:
if self.CurrentSlice[holding.Symbol].Open < self.sell_prices[holding.Symbol] and holding.Invested:
self.Liquidate(holding.Symbol)
if self.CurrentSlice[holding.Symbol].Open > self.buy_prices[holding.Symbol] and not holding.Invested:
self.SetHoldings(holding.Symbol, 1 / len(self.symbols))
Shouldnt that be the orthe way around? I mean, how is buying an asset once it reached a certain price profitable? What am I not getting?
Thanks for your help!
Rahul Chowdhury
Hi Guillermo,
This strategy uses the neural network to create a boundary for the future price and then makes a trade if there is a breakout. The upper boundary is defined by buy_prices and the lower boundary is defined by sell_prices. If the price of a symbol breaks above the buy_price, the algorithm enters a trade and if the price breaks below the sell_price, the algorithm exits if it is invested.
Best
Rahul
Guillermo Bondonno
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