Comments (1)
Hello @emanuele, you are correct.
As a general rule, the most tested code pathways involve (1) default parameters or (2) are clearly documented / shown in the examples.
If you use the default cvx.ReturnsForecast()
with no arguments, or you implement a forecaster as is shown in the user_provided_forecasters.py
example, none of these issues appear.
Also, I suspect that if you pass your own returns
dataframe to a simulator class (and it has no np.nan
), everything runs fine.
I'll work on fixing you usecase as well (by improving the internal DataEstimator
class, which does all the heavy lifting of serving user-provided data).
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Related Issues (20)
- Failure on non-numeric (object dtpye) user-provided data difficult to understand HOT 6
- Example request - Margin in a different currency HOT 14
- BUG: packaging failed to include modules moved into submodules (constraints, data)
- Feature request: handle user-defined time-varying universes (and better error checks with temporary `nan`s in user-provided returns) HOT 13
- Data quality issues in `ftse100_daily` example strategy
- EOFError: Ran out of input HOT 4
- Rendering of code blocks in README on github is broken
- Feature request: add `market_data=None` option to `Policy.execute`
- Feature request: Add constraint priority with automatic resolution into soft-constraints HOT 1
- Is it possible to have different costs definition depending on entry or exit HOT 1
- can we load into our custom crypto data into cvxportfolio for backtesting and portfolio construction ? [bounty possible] HOT 1
- Feature Request: Online Data Loading HOT 1
- Ecos needs to added in pyproject "test" optional dependencies HOT 1
- Issue loading data from FRED HOT 9
- Testsuite failing on py 3.9 b/c of dependencies HOT 1
- The result of backtesting 30 years is different from 5 years? HOT 5
- Feature Request: Ignore Tcosts in first period HOT 2
- Incompatible with Numpy 2.0 HOT 1
- How are returns computed? HOT 1
- New Cvxportfolio versions will have the General Public License
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