Risk Performance Benchmark

perfana.monte_carlo.risk.prob_loss(data, weights, rebalance=True, terminal=False)[source]

Calculates the probability of the portfolio suffering a loss。

Parameters

  • data (ndarray) – Monte carlo simulation data. This must be 3 dimensional with the axis representing time, trial and asset respectively.

  • weights (Union[Iterable[Union[int, float]], ndarray, Series]) – Weights of the portfolio. This must be 1 dimensional and must match the dimension of the data’s last axis.

  • rebalance – If True, portfolio is assumed to be rebalanced at every step.

  • terminal – If True, this only compares the probability of a loss at the last stage. If False (default), the calculation will take into account if the portfolio was “ruined” and count it as a loss even though the terminal value is positive.

Returns

A named tuple containing the probability of underperformance and loss

Return type

float

Examples

>>> from perfana.datasets import load_cube
>>> from perfana.monte_carlo import prob_loss
>>> data = load_cube()
>>> weights = [0.25, 0.18, 0.13, 0.11, 0.24, 0.05, 0.04]
>>> prob_loss(data, weights)
0.198