# Copyright 2023 Stanford University Convex Optimization Group
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Abstract risk model
"""
from __future__ import annotations
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
import cvxpy as cp
@dataclass
[docs]
class Model(ABC):
"""Abstract risk model"""
[docs]
parameter: dict[str, cp.Parameter] = field(default_factory=dict)
@abstractmethod
[docs]
def estimate(self, weights, **kwargs):
"""
Estimate the variance given the portfolio weights
"""
@abstractmethod
[docs]
def update(self, **kwargs):
"""
Update the data in the risk model
"""
@abstractmethod
[docs]
def constraints(self, weights, **kwargs):
"""
Return the constraints for the risk model
"""