Comments (2)
It appears that when setting all of the initial weights to zero (we haven't invested anything yet), the weights last_b at the first time step are always set to 1/N, with N the number of stocks in the portfolio. Then, at the next step, all the weights are set to 0 except one which is set to 1. From there, things look normal and realistic weights are assigned to particular stocks.
Good catch, that's most likely a bug. I haven't used olmar for quite some time. In case you have a fix, could you create a PR?
I also noticed that when setting them already to 1/N, the first step is skipped (logically). One could say that this assumption is valid (we already own said stocks before the start), but the 2nd step remains anyway where everything is sold except one. Is there a way to change this behavior?
Sure, you can subclass method OLMAR.init_weights
and set all weights to zero. You might also have to subclass update
to avoid weight change penalization when starting with zero weights.
from universal-portfolios.
I checked but couldn't find the issue : maybe some transformation due to the simplex projection ? I don't know.
Closing this issue for now, feel free to re-open it if you have an idea :)
from universal-portfolios.
Related Issues (20)
- It seem like the two functions "run" and "run_combination" do not calculate the same the total_wealth? HOT 6
- some question about the transaction cost code HOT 1
- Question about data format HOT 3
- Data reference HOT 2
- Convergence Issue: "Converged, but not successfully." and Weight Sum Not Equal to 1 HOT 3
- ModuleNotFoundError: No module named 'scipy.special'
- undefined self.window in update_tco() in algo.py HOT 1
- Invalid equity result using result weight
- MaybeEncodingError while using the run_combination() method
- Issue with Mac M1 HOT 2
- Data information HOT 3
- 2 questions HOT 1
- Installation Issues HOT 10
- specifying the args of CORN class HOT 8
- a self.eta error in TCO
- Try to include transaction cost into OLMAR, but does not work HOT 1
- Assertion error # update logarithms, fees, etc. AssertionError:` HOT 2
- tools.simplex_project() returns the largest positive vector only? HOT 1
- There are several FeatureWarnings with the code
- Equity calculation, shift issue? HOT 5
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from universal-portfolios.