portfolioperformance下載 - portfolioperformance功能源代碼下載

portfolioperformance

Ai源碼

v1.1.0

下載

投資組合性能

測試投資組合優化模型的樣本外部性能的工具。基於論文：最佳與天真多樣化：

我還為此軟件包開發了一個遊樂場網站，因此您可以在自己的數據上輕鬆運行這些模型。鏈接到網站

用法

安裝

pip install portfolioperformance

型號

 # 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

應用程序類

參數

path （ str ）：通往csv文件的路徑
gammas （ list[int] ）：伽馬值列表
timeHorizon （ list[int] ）：時間範圍列表
models （ list[Model] ）：模型類列表
dateFormat （ str ）：熊貓日期時間格式，默認值=“％y-％m％d”
dateRange （ [str, str] ）：開始和結束日期，默認值= []
delim （ str ）：劃界類型，“”或“ s+”（whitespace），默認=“，”
logScale （ bool ）：數據是否在日誌尺度中，默認值= false
riskFactorPositions （ list ）：風險因素資產列位置（位置1是日期列），默認值= []
riskFreePosition （ int ）：無風險資產列位置，默認值= 1

方法

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

獲得夏普比率

返回： - dict[str, float] ：具有型號名稱和夏普比率的詞典作為鑰匙值對

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

獲得基準模型的統計意義

參數：
- benchmark （ Model ）：基準模型

返回：
- dict[str, float] ：具有模型名稱和夏普比率的字典作為鑰匙值對

發展

設定

克隆項目： git clone https://github.com/sidnand/portfolioperformance
安裝軟件包： pip install -r requirements.txt
進行更改！

文件夾結構

 .
| -- __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