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Hi, I like the direction where backtesting.py is going, but I am missing some backtrader functionality... Maybe the most important - currently only one stock is supported right?
Because if I have a strategy which uses 2 stocks, how would I deal with that? The backtrader way was using self.datas instead of data, which then becomes an array with all the stock datas, and then obviously the buy/sell functions would need a ticker parameter...
Or is there already a way to achieve this?
The text was updated successfully, but these errors were encountered:
class _Data:
"""
A data array accessor. Provides access to OHLCV "columns"
as a standard `pd.DataFrame` would, except it's not a DataFrame
and the returned "series" are _not_ `pd.Series` but `np.ndarray`
for performance reasons.
"""
def __init__(self, df: pd.DataFrame):
self.__df = df
self.__i = len(df)
self.__pip: Optional[float] = None
self.__cache: Dict[str, _Array] = {}
self.__arrays: Dict[str, _Array] = {}
self._update()
so would I pass something like
data = { "MSFT" : yf.download("MSFT"), "AAPL" : ...?
Check out https://github.com/dodid/minitrade, a fork from this project which allows for multiasset backtesting.
Would love to have this functionality here under @kernc project though!
Hi, I like the direction where backtesting.py is going, but I am missing some backtrader functionality... Maybe the most important - currently only one stock is supported right?
Because if I have a strategy which uses 2 stocks, how would I deal with that? The backtrader way was using self.datas instead of data, which then becomes an array with all the stock datas, and then obviously the buy/sell functions would need a ticker parameter...
Or is there already a way to achieve this?
The text was updated successfully, but these errors were encountered: