trading

Expected Behavior

backtesting binance cypto

Actual Behavior

Can't place an order

Potential Solution

• Add all crypto exchanges missing stable coins to be added at https://github.com/QuantConnect/Lean/blob/master/Common/Currencies.cs#L116

Reproducing the Problem

def Initialize(self):
self.SetStartDate(2018, 5, 2)
self.SetEndDate(2021, 5, 4)

Wondering if this already exists? If not happy to create if valuable.

I'm looking for a mapping from the column names outputted, to the actual technical indicator it represents.

examples:
momentum_ao == "Momentum, Awesome Oscilator"
momentum_kama == "Momentum, Kaufman’s Adaptive Moving Average (KAMA)"

Can help quickly grasp what the features represent without having to refer back to do

According to @rspadim, functions in entropy.py could use numpy array instead of strings, as it's better to numba.

Guide on how to implement this is available in the comments in PR #311 .

Is your feature request related to a problem? Please describe.
Ugly title for asset new asset. The asset node gets New Asset title after entering the codename.

Describe the solution you'd like
auto rename by referring the codeName --> iconName
set iconName as variable.

Describe alternatives you've considered

Additional context
Add any other context or screenshots

Say I have two points on the Dataframe (price and UNIX timestamp) and I want to draw a Ray (endless) that goes through these two points. Does Pandas TA or Pandas has a function for this? Is there an easy way to draw a Linear Regression ray, I just have the two points and I want to draw a Ray through them and get all the Datapoints (price and timestamp of each) say 1 week into the future to be pred

this is how Buy & Hold Return is calculated:

        c = data.Close.values
        s.loc['Buy & Hold Return [%]'] = (c[-1] - c[0]) / c[0] * 100  # long-only return

so it's calced use day one and the day last.

Expected Behavior

Buy & Hold Return is used for compare with strategy gain. Therefore, I guess they should started at same time, since the strategy get enough data to w