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dynstrategy.py
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# -*- coding: utf-8 -*-
"""
Created on Thu Sep 14 15:42:12 2017
@author: wangm
"""
import numpy as np
import robolib as rl
from pylab import *
import mpt as mpt
import pandas as pd
import iolib as il
def getMW_MaxReturn(funds_input):
"""
根据马科维茨理论获得最大收益情况下的资产组合
"""
mpt.funds_daily = funds_input
mpt.nod = len(funds_input)
mpt.nof = len(funds_input.columns)
mpt.funds = rl.getNetWorthFromDailyProfit(funds_input)
mpt.returns = np.log(mpt.funds / mpt.funds.shift(1))
optr = mpt.MK_MaxReturn()
return optr['x']
def getMW_MaxSharp(funds_input):
"""
根据马科维茨理论获得最大夏普情况下的资产组合
"""
mpt.funds_daily = funds_input
mpt.nod = len(funds_input)
mpt.nof = len(funds_input.columns)
mpt.funds = rl.getNetWorthFromDailyProfit(funds_input)
mpt.returns = np.log(mpt.funds / mpt.funds.shift(1))
optr = mpt.MK_MaxSharp()
return optr['x']
def getMW_MinVariance(funds_input):
"""
根据马科维茨理论获得最小方差（风险）情况下的资产组合
"""
mpt.funds_daily = funds_input
mpt.nod = len(funds_input)
mpt.nof = len(funds_input.columns)
mpt.funds = rl.getNetWorthFromDailyProfit(funds_input)
mpt.returns = np.log(mpt.funds / mpt.funds.shift(1))
optr = mpt.MK_MinVariance()
return optr['x']
def getCombinationProfit_Month_Mk(fundpercent, fundprofit, combinationname, change_weekcount=3, change_weekday=2,
returnexp=0, optgoal="maxsharp"):
lastindex = fundprofit.index[0]
comprofit = pd.DataFrame(np.zeros((len(fundprofit.index.tolist()), 1)), index=fundprofit.index.tolist(),
columns=[combinationname + "-combination_profit"])
fundweight = [fundpercent["depsoit"], fundpercent["fund1"], fundpercent["fund2"], fundpercent["fund3"]]
temp_df = pd.DataFrame([fundweight],
columns=["存款比例", "基金1比例", "基金2比例", "基金3比例"])
percent_detail = temp_df
fundweightnparr = np.array(fundweight)
for index, row in fundprofit.iterrows():
year = int(index[0:4])
month = int(index[5:7])
day = int(index[9:])
# 判断当天的日期是不是当月的第三个周二
comprofit.loc[index] = np.sum(fundweightnparr * fundprofit.loc[index])
# 使用下面这种语句方式可以记录每一天的仓位情况
# percent_detail.loc[index] = fundweightnparr
if index == rl.get_date_by_year_month_weekcount_weekday(year, month, change_weekcount, change_weekday):
fundinput = fundprofit[lastindex:index]
fundinput = fundinput[["fund1", "fund2", "fund3"]]
if optgoal == "maxsharp":
fundweighttemp = getMW_MaxSharp(fundinput)
elif optgoal == "minvariance":
fundweighttemp = getMW_MinVariance(fundinput)
else:
fundweighttemp = getMW_MaxReturn(fundinput)
fundweighttemp = np.array(fundweighttemp)
fundweighttemp = fundweighttemp / np.sum(fundweighttemp)
fundweightnparr[1] = (1 - fundweightnparr[0]) * fundweighttemp[0]
fundweightnparr[2] = (1 - fundweightnparr[0]) * fundweighttemp[1]
fundweightnparr[3] = (1 - fundweightnparr[0]) * fundweighttemp[2]
lastindex = index
# 使用下面这种方式则只在调仓时记录数据
temp_df = pd.DataFrame([fundweightnparr],
columns=["存款比例", "基金1比例", "基金2比例", "基金3比例"])
if percent_detail.empty:
percent_detail = temp_df
else:
percent_detail = pd.concat([percent_detail, temp_df])
return comprofit, percent_detail
if __name__ == '__main__':
user_type_str_mw = "test"
funds_daily_df = il.getFunds_Everyday(startday_str="2017-01-01", endday_str="2017-08-31")
fundpercent = {"depsoit": 0.25, "fund1": 0.25, "fund2": 0.25, "fund3": 0.25}
# 根据马科维茨最优化理论进行调仓
combination_mw, percent_detail = getCombinationProfit_Month_Mk(fundpercent, funds_daily_df, user_type_str_mw)
print(combination_mw)
print(percent_detail)