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PY组合模型.py
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#coding:gbk
#HS300日线下运行
#股票池暂设为包含4只股票，每只分配可用资金的25%
import pandas as pd
import numpy as np
import time
import datetime
s = ['600000.SH','600004.SH','000001.SZ','000002.SZ'] #股票池
def init(ContextInfo):
ContextInfo.set_universe(s)
ContextInfo.day = 0
ContextInfo.weight = [0.25,0.25,0.25,0.25] #设置初始权重
ContextInfo.money_distribution_original = {k:i*ContextInfo.capital for (k,i) in zip(s,ContextInfo.weight)}
ContextInfo.money_distribution = ContextInfo.money_distribution_original
ContextInfo.buypoint = {}
ContextInfo.accountID='testS'
def handlebar(ContextInfo):
d = ContextInfo.barpos
timetag = ContextInfo.get_bar_timetag(d)
ContextInfo.holdings = get_holdings(ContextInfo.accountID,"STOCK")
if ContextInfo.day == 0:
ContextInfo.benchmark_start = ContextInfo.get_market_data(['close'],period='1d')
benchmark = ContextInfo.get_market_data(['close'],period='1d')
#print benchmark
net_hs300 = benchmark/ContextInfo.benchmark_start
ContextInfo.paint('沪深300指数净值',net_hs300,-1,0)
ContextInfo.paint('沪深300指数收益',net_hs300-1,-1,0)
tmp = ContextInfo.get_history_data(1,'1d','open',3)
if d > 60:
nowDate = timetag_to_datetime(ContextInfo.get_bar_timetag(d),'%Y%m%d')
print(nowDate)
buys, sells = signal(ContextInfo)
order = {}
for k in s:
if k not in ContextInfo.holdings and buys[k] == 1: #在买入备选中且无持仓
print('ready to buy',k)
order[k] = int(ContextInfo.money_distribution[k]/(tmp[k][-1]))/100
order_shares(k,order[k]*100,'fix',tmp[k][-1],ContextInfo,ContextInfo.accountID)
ContextInfo.buypoint[k] = tmp[k][-1]
ContextInfo.money_distribution[k] -= 0.0003*order[k]*100*tmp[k][-1]
#print ContextInfo.money_distribution[k]
elif k in ContextInfo.holdings and sells[k] == 1: #在卖出备选中且有持仓
print('ready to sell',k)
order_shares(k,-ContextInfo.holdings[k]*100,'fix',tmp[k][-1],ContextInfo,ContextInfo.accountID)
ContextInfo.money_distribution[k] += (tmp[k][-1]-ContextInfo.buypoint[k]) * ContextInfo.holdings[k] * 100 - 0.0003*ContextInfo.holdings[k]*100*tmp[k][-1]
#print tmp[k][-1]
#print ContextInfo.buypoint[k]
#print ContextInfo.money_distribution[k]
profit = sum(ContextInfo.money_distribution.values())/ContextInfo.capital - 1
ttt = 0
for v in list(ContextInfo.holdings.values()):
if v > 0:
ttt += 1
ContextInfo.paint('收益',profit,-1,0)
ContextInfo.paint('对冲收益',profit-net_hs300-1,-1,0)
ContextInfo.paint('对冲收益净值',profit+1-net_hs300,-1,0)
ContextInfo.paint('个股',ttt,-1,0)
ContextInfo.day += 1
def signal(ContextInfo):
buy = {i:0 for i in s}
sell = {i:0 for i in s}
data_high = ContextInfo.get_history_data(22,'1d','high',3)
data_high_pre = ContextInfo.get_history_data(2,'1d','high',3)
data_close60 = ContextInfo.get_history_data(62,'1d','close',3)
#print data_high
#print data_close
#print data_close60
for k in list(data_high_pre.keys()):
if k in data_close60:
if len(data_high_pre[k]) == 2 and len(data_high[k]) == 22 and len(data_close60[k]) == 62:
if data_high_pre[k][-2] > max(data_high[k][:-2]):
buy[k] = 1 #超过20日最高价，加入买入备选
elif data_high_pre[k][-2] < np.mean(data_close60[k][:-2]):
sell[k] = 1 #低于60日均线，加入卖出备选
#print buy
#print sell
return buy,sell #买入卖出备选
def get_holdings(accountid,datatype):
holdinglist={}
resultlist=get_trade_detail_data(accountid,datatype,"POSITION")
for obj in resultlist:
holdinglist[obj.m_strInstrumentID+"."+obj.m_strExchangeID]=obj.m_nVolume/100
return holdinglist