Coverage for src/cvx/risk/cvar/__init__.py: 100%

1"""Conditional Value at Risk (CVaR) models for portfolio optimization. 

2 

3This subpackage provides the CVar class for CVaR-based risk estimation. 

4CVaR, also known as Expected Shortfall, measures the expected loss in the 

5tail of the return distribution. 

6 

7Example: 

8 >>> import numpy as np 

9 >>> from cvx.risk.cvar import CVar 

10 >>> # Create CVaR model 

11 >>> model = CVar(alpha=0.95, n=100, m=5) 

12 >>> # Update with historical returns 

13 >>> np.random.seed(42) 

14 >>> returns = np.random.randn(100, 5) 

15 >>> model.update( 

16 ... returns=returns, 

17 ... lower_assets=np.zeros(5), 

18 ... upper_assets=np.ones(5) 

19 ... ) 

20 >>> w = np.ones(5) / 5 

21 >>> cvar = model.estimate(w) 

22 >>> isinstance(cvar, float) 

23 True 

24 

25""" 

26 

27# Copyright (c) 2025 Jebel Quant Research 

28# 

29# Licensed under the MIT License. See the LICENSE file in the project root 

30# for the full license text. 

31from .cvar import CVar as CVar