Checking if I have implemented my back test correctly using a custom data frame

[pranavlal]

Hi all,
I have the following strategy.

1. I buy when my machine learning model tells me to do so. The model is based on a number of indicators. The signal from the model as well as the price ohlc data is contained in a data frame.
2. 2. I sell if the closing price is above 3 times atr at the time I bought.
3. If I have an open position for a stock, I do not buy it again.

I have the following implementation.
``
from backtesting import Backtest
from backtesting import Strategy
class testModel(Strategy):
def init(self):
super().init()

def next(self):
	super().next()
	if (self.data.signal==1):
		self.buy()
	else:
		for trade in self.trades:
			if self.data.Close>trade.entry_price+(3*self.data.df["atr"][trade.entry_bar]):
				self.sell()
	


bt = Backtest(df, testModel, commission=.0002,cash=20000,margin=0.1,exclusive_orders=True)
stats = bt.run()
print(stats)

``

Have I implemented the above strategy as I have described it in words?

[kernc]

Instead of self.data.signal==1, you'd make the condition be: self.data.signal[-1] == 1 and not self.position.
Instead of self.sell(), you'd call self.position.close().

[pranavlal]

Many thanks. That works better and is the answer I needed.