Coverage for src / cvx / markowitz / models / holding_costs.py: 100%

1# Copyright 2023 Stanford University Convex Optimization Group 

2# 

3# Licensed under the Apache License, Version 2.0 (the "License"); 

4# you may not use this file except in compliance with the License. 

5# You may obtain a copy of the License at 

6# 

7# http://www.apache.org/licenses/LICENSE-2.0 

8# 

9# Unless required by applicable law or agreed to in writing, software 

10# distributed under the License is distributed on an "AS IS" BASIS, 

11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 

12# See the License for the specific language governing permissions and 

13# limitations under the License. 

14"""Model for holding costs.""" 

15 

16from __future__ import annotations 

17 

18from dataclasses import dataclass 

19 

20import cvxpy as cp 

21import numpy as np 

22 

23from cvx.markowitz.model import Model 

24from cvx.markowitz.names import DataNames as D 

25from cvx.markowitz.types import Expressions, Matrix, Parameter, Variables # noqa: F401 

26from cvx.markowitz.utils.fill import fill_vector 

27 

28 

29@dataclass(frozen=True) 

30class HoldingCosts(Model): 

31 """Model for holding costs.""" 

32 

33 def __post_init__(self) -> None: 

34 """Initialize holding-cost parameter vector.""" 

35 self.data[D.HOLDING_COSTS] = cp.Parameter(shape=self.assets, name=D.HOLDING_COSTS, value=np.zeros(self.assets)) 

36 

37 def estimate(self, variables: Variables) -> cp.Expression: 

38 """Return total holding costs as -sum(w_i * c_i).""" 

39 return cp.sum(cp.neg(cp.multiply(variables[D.WEIGHTS], self.data[D.HOLDING_COSTS]))) 

40 

41 def update(self, **kwargs: Matrix) -> None: 

42 """Update the holding-cost vector from kwargs[D.HOLDING_COSTS].""" 

43 self.data[D.HOLDING_COSTS].value = fill_vector(num=self.assets, x=kwargs[D.HOLDING_COSTS])