Comments (4)
Once done, we can mention in the notebook that fastquant does this automatically. :)
I think this merits backtest to be a class of its own so we access it's properties e.g. the best parameters, the backtrader figure using the best parameters, etc.
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@jpdeleon Noted on the notebook :)
hmm not necessary for it to have its own class if all of these properties are found straight from the cerebro object rigth?
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@enzoampil I agree. Sorry I missed earlier your note about cerebro.optstrategy
that does parameter optimization under the hood already. I think any parameter in a strategy can be optimized already using that method.
So the grid_search notebook is only useful for presentation but not useful in practice.
Also check this backtrader script that optimizes across strategies.
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Planning to apply the ff:
- Perform grid search if any of the parameters are input as an
iterable
(kwargs
input) - If
plot = True
only the "optimal" version of the strategy is returned - Add explicit usage of
Analyzers
to choose the metric of comparison across strategies (ref) - Will set returns and sharpe as the default analyzers.
- Instead of
cerebro
,parameters
andmetrics
will be returned bybacktest
. These come fromstratruns
, since this contains both analyzer metrics and all metrics related to the run (e.g. final portfolio value)
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Related Issues (20)
- get_stock_data() error HOT 1
- New Strategies
- Not able to optimize the stop loss and other floating parameters. HOT 6
- How to give flags or limit our buy and sell signal for the backtesting?? HOT 8
- How to get multiple dataframe and backtest at same time HOT 10
- Not able to import strategy class from another python file HOT 3
- Backtest function not working while deploying flask application HOT 1
- How to get previous and current row while implementing the strategy HOT 2
- [BUG] Issue with imports HOT 3
- [FEATURE]Would you like to support the library to add extended plotting capabilities -- backtrader_plotting ? HOT 1
- [BUG] HOT 2
- [Indicator import from Pandas-ta ] HOT 1
- Testing with machine learning model and a data frame with pre-generated signals
- Error when get stock data from Thai stock
- new
- [BUG] Error when install packgage HOT 2
- [BUG] json_normalize issue HOT 1
- [BUG] pypi.org hosted fastquant 0.1.8.1 breaks due to json_normalize (fix already in master) HOT 2
- Still problem "cannot import name 'json_normalize' from 'pandas.io.json'" HOT 1
- AttributeError: 'DataFrame' object has no attribute 'append' HOT 1
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