portfolioperformance下载 - portfolioperformance功能源代码下载

portfolioperformance

Ai源码

v1.1.0

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投资组合性能

测试投资组合优化模型的样本外部性能的工具。基于论文：最佳与天真多样化：

我还为此软件包开发了一个游乐场网站，因此您可以在自己的数据上轻松运行这些模型。链接到网站

用法

安装

pip install portfolioperformance

型号

 # Each model takes a name parameter
ew = EqualWeight ( "Equal Weight" )
minVar = MinVar ( "Minimum Variance" )
JagannathanMa = JagannathanMa ( "Jagannathan Ma" )
minVarShortSellCon = MinVarShortSellCon ( "Minimum Variance with Short Sell Constrains" )
kanZhouEw = KanZhouEw ( "Kan Zhou EW" )

meanVar = MeanVar ( "Mean Variance (Markowitz)" )
meanVarShortSellCon = MeanVarShortSellCon ( "Mean Variance with Short Sell Constrains" )
kanZhou = KanZhou ( "Kan Zhou Three Fund" )
bayesStein = BayesStein ( "Bayes Stein" )
bayesSteinShortSellCon = BayesSteinShortSellCon ( "Bayes Stein with Short Sell Constrains" )
macKinlayPastor = MacKinlayPastor ( "MacKinlay and Pastor" )

例子

 import numpy as np
from portfolioperformance import *

# Risk aversion levels
GAMMAS = [ 1 , 2 , 3 , 4 , 5 , 10 ]

# Time horizons
TIME_HORIZON = [ 60 , 120 ]

benchmark = < benchmark model >

# List of models
models = [
    benchmark ,
    # <add other list of models>
]

app = App ( < data path > , GAMMAS , TIME_HORIZON , models , dateFormat = < pandas datetime format > ,
            dateRange = [ "01011990" , "01012010" ], delim = < "," or " \ s+" > ,
            riskFactorPositions = [ positions for risk factor column ],
            riskFreePosition = < risk free asset column > )

sr = app . getSharpeRatios ()
sig = app . getStatisticalSignificanceWRTBenchmark ( benchmark )

API

应用程序类

参数

path （ str ）：通往csv文件的路径
gammas （ list[int] ）：伽马值列表
timeHorizon （ list[int] ）：时间范围列表
models （ list[Model] ）：模型类列表
dateFormat （ str ）：熊猫日期时间格式，默认值=“％y-％m％d”
dateRange （ [str, str] ）：开始和结束日期，默认值= []
delim （ str ）：划界类型，“”或“ s+”（whitespace），默认=“，”
logScale （ bool ）：数据是否在日志尺度中，默认值= false
riskFactorPositions （ list ）：风险因素资产列位置（位置1是日期列），默认值= []
riskFreePosition （ int ）：无风险资产列位置，默认值= 1

方法

`getSharpeRatios() -> dict[str, float]`

获得夏普比率

返回： - dict[str, float] ：具有型号名称和夏普比率的词典作为钥匙值对

`getStatisticalSignificanceWRTBenchmark(benchmark) -> dict[str, float]`

获得基准模型的统计意义

参数：
- benchmark （ Model ）：基准模型

返回：
- dict[str, float] ：具有模型名称和夏普比率的字典作为钥匙值对

发展

设置

克隆项目： git clone https://github.com/sidnand/portfolioperformance
安装软件包： pip install -r requirements.txt
进行更改！

文件夹结构

 .
| -- __init__.py # import /src/app.py and all models
| -- /src
    | -- app.py # code for running all the optimiation models
    | -- model.py # parent class to all the models
    | -- modelNoGamma.py # class for models that don't take extra parameters
    | -- modelGamma.py # class for models that take an extra gamma parameter; gamma is a list of constants for the investors risk-aversion level
    | -- ./models # all the models
    | -- ./utils
        | -- filter.py # includes a function that is used to filter the parameters passed to a function
        | -- quadprog.py # quadratic programming
        | -- sharedOptions.py # models options that are in common with >2 models
        | -- statistics.py # statistics functions