resample_returns#
API documentation for tradeexecutor.visual.equity_curve.resample_returns Python function.
- resample_returns(returns, freq)[source]#
Resample returns series to a longer time frame.
Transform daily returns series to monthly and so on
The returns of each period is the cumulative product of the sub-returns
Does this with a cumulative product transformation
Example:
We have returns:
2021-06-01 00:00:00 0.000000 2021-06-01 08:00:00 0.000000 2021-06-01 16:00:00 0.000000 2021-06-02 00:00:00 0.000000 2021-06-02 08:00:00 0.000000 ... 2024-03-08 08:00:00 -0.002334 2024-03-08 16:00:00 -0.012170 2024-03-09 00:00:00 -0.003148 2024-03-09 08:00:00 0.010400 2024-03-09 16:00:00 -0.000277
Make it quarterly:
# Transform daily returns to monthly for easier comparison freq = QuarterBegin() resampled_returns = resample_returns(returns, freq)
Now it is:
2021-06-01 0.483777 2021-09-01 0.287191 2021-12-01 0.265714 2022-03-01 -0.035728 2022-06-01 0.194215 2022-09-01 0.059003 2022-12-01 0.062195 2023-03-01 -0.091300
- Parameters:
returns (Series) ā Hourly, 8h, etc. returns
freq (pandas._libs.tslibs.offsets.DateOffset | str) ā
Pandas resample frequency.
Use āDā for daily.
- Returns:
Returns series where the returns are binned by a new timeframe.
- Return type:
Series