Problems when portfolio value approaches negative about cvxportfolio HOT 2 OPEN

Thanks! These are all valid observations.

1. Yup, I should change that. self.expression.value.A1 converts to numpy array (by default, cvxpy uses numpy matrices). It's kind of annoying, but unfortunately numpy has some inconsistencies there (i.e., there should be no difference between a n x 1 matrix and a n column vector, but there is).

2. If the portfolio value drops below zero, you've gone bankrupt. Stopping the simulation is the correct thing to do. However, it would be more correct to throw an appropriate exception, e.g.,

class SimulationBankruptcy(Exception): pass

3. I never really encountered negative values in my tests, so I haven't implemented guards against all possible breaking cases. Complex numbers in the Tcost model are clearly an absurdity. Negative portfolio values should be caught earlier and throw the same exception of point 2.

If you have implemented these changes, please go forward with a pull request.

Thanks!
Enzo

from cvxportfolio.

Thanks for your ideas.

1. So do changes need to be made in all the Costs.optimization_logs? Or just Result.log_policy?

2. Throwing an exception sounds interesting. I guess it would be thrown in Policy.get_trades? And then handled in Simulation.run_backtest? How would this handling work? Don't want the other 39 threads to get halted just because one went bankrupt.

The only changes I've made are to allow the simulation to continue, which sometimes maintains zero portfolio value for the rest of the time (at the cost of lots of unnecessary optimization), other times going further negative with further bankrupt trades (I guess, the leverage constraint unbinds when the portfolio becomes negative enough).

I think ideally, trades and portfolio values would get set to zero, and get_trades would return zeros without attempting optimization or throwing exceptions, and logging would record zero for everything. This way, the Result of a simulation that hits zero value has attributes with the same dimensions (DatetimeIndexs) as the other Results, and the simulation finishes very quickly. Then post-analysis doesn't have to worry about different results having different simulation lengths.

Hopefully I'll have time to try it out soon.

from cvxportfolio.