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Update __init__.py.

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Charles Young
2021-03-04 22:47:42 +08:00
parent 83c6e74783
commit 0f3e3d206b
6 changed files with 30 additions and 15 deletions
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7
qlib/model/riskmodel/__init__.py
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@@ -0,0 +1,7 @@
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from .base import RiskModel
from .poet import POETCovEstimator
from .shrink import ShrinkCovEstimator
from .structured import StructuredCovEstimator

4
qlib/model/riskmodel/base.py
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@@ -7,10 +7,6 @@ from typing import Union
from qlib.model.base import BaseModel from qlib.model.base import BaseModel
from qlib.model.riskmodel_poet import POETCovEstimator
from qlib.model.riskmodel_shrink import ShrinkCovEstimator
from qlib.model.riskmodel_structured import StructuredCovEstimator
class RiskModel(BaseModel): class RiskModel(BaseModel):
"""Risk Model """Risk Model

2
qlib/portfolio/__init__.py
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6
qlib/portfolio/optimizer/__init__.py
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# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from .base import BaseOptimizer
from .optimizer import PortfolioOptimizer
from .enhanced_indexing import EnhancedIndexingOptimizer

13
qlib/portfolio/optimizer/base.py
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@@ -0,0 +1,13 @@
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import abc
class BaseOptimizer(abc.ABC):
""" Construct portfolio with a optimization related method """
@abc.abstractmethod
def __call__(self, *args, **kwargs) -> object:
""" Generate a optimized portfolio allocation """
pass

13
qlib/portfolio/optimizer/optimizer.py
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@@ -1,23 +1,14 @@
# Copyright (c) Microsoft Corporation. # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License. # Licensed under the MIT License.
import abc
import warnings import warnings
import numpy as np import numpy as np
import pandas as pd import pandas as pd
import scipy.optimize as so import scipy.optimize as so
from typing import Optional, Union, Callable, List from typing import Optional, Union, Callable, List
from qlib.portfolio.enhanced_indexing import EnhancedIndexingOptimizer from qlib.portfolio.optimizer import BaseOptimizer
class BaseOptimizer(abc.ABC):
""" Construct portfolio with a optimization related method """
@abc.abstractmethod
def __call__(self, *args, **kwargs) -> object:
""" Generate a optimized portfolio allocation """
pass
class PortfolioOptimizer(BaseOptimizer): class PortfolioOptimizer(BaseOptimizer):