Back

Pandas/Numpy in Lean

Hi,

I'm looking at Lean as a possible home backtesting framework. From the framework I've seen, they fall into 2 categories - either they use pandas/numpy (and associated libraries) or they code everything themselves. I come from a Matlab background and at the moment I use pandas/numpy for backtesting.

From what I can see Lean falls into the second category. Is it possible however, to use pandas/numpy etc. when writing backtests in python? Do you have any examples?

Update Backtest








It is possible, yes.
Moreover, when you make a historical data request, the method return a pandas.DataFrame:

# Get history in pandas.DataFrame format, use list of string
df = self.History(["EURUSD"], timedelta(7))
df = self.History(["EURUSD"], timedelta(7), Resolution.Minute)
df = self.History(["EURUSD"], 14)
df = self.History(["EURUSD"], 14, Resolution.Minute)
1

The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


Update Backtest





0

The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


Loading...

This discussion is closed