def date_accmulation_getall(today):
ma = [i for i in range(2,241)]
df_all = get_his_data('000300', ma=ma,index=True)
test = hs_300_strategy(df_all)
for ii in ma:
print('processing MA_'+str(ii))
test.backtest(ma_1=str(ii),ma_2=str(ii))
# return原始是1,100%
df = pd.concat([test._df.position,test._df['return'],test._df.beta,test._df.drawdown,test._df.long,
test._df.short],axis=1)
write_to_mongo(df, db='Single_MA_testback', collection=today, id='MA_'+str(ii))
test = hs_300_strategy(df_all)
def date_accmulation():
ma = [i + 1 for i in range(120)]
print(ma)
df_all = get_his_data('hs300', ma=ma)
length = len(df_all)
for i in range(length-29):
df = df_all[:i + 30]
start = df.index[0]
end = df.index[len(df) - 1]
print('start calculate :' + str(start) + ' to ' + str(end))
rr = test_(ma, df)
write_to_mongo(rr, db='Single_MA_testback', collection='2016-08-31', id=str(end))
def fixed_90():
ma = [i+1 for i in range(120)]
print(ma)
df_all = get_his_data('hs300', ma=ma)
length = len(df_all)
for i in range(length-89):
df = df_all[i:i+90]
start = df.index[0]
end = df.index[len(df)-1]
print('start calculate :'+str(start)+' to '+str(end))
rr = test_(ma, df)
write_to_mongo(rr,db='MA_testback',collection='Single_MA_90_rolling',id=str(end))
def hist_data_import_to_mongodb(self):
mongdb = MONGODB(db='ALL_STOCKS')
for i in self._all_codes[list(self._all_codes).index('600335'):]:
print('process code:' + i)
data = get_his_data(i,start='2005-01-01',end='2008-01-01',if_ma=False)
data2 = get_his_data(i,start='2008-01-01',end='2011-01-01',if_ma=False)
data3 = get_his_data(i, start='2011-01-01', end='2014-01-01', if_ma=False)
data4 = get_his_data(i, start='2014-01-01', end='2017-01-01', if_ma=False)
try:
mongdb.write_to_mongo(data,collection=i,id='2005-01-01/2008-01-01')
except Exception as e:
print(e)
try:
mongdb.write_to_mongo(data2, collection=i, id='2008-01-01/2011-01-01')
except Exception as e:
print(e)
try:
mongdb.write_to_mongo(data3, collection=i, id='2011-01-01/2014-01-01')
except Exception as e:
print(e)
try:
mongdb.write_to_mongo(data4, collection=i, id='2014-01-01/2016-09-06')
except Exception as e:
print(e)
drawback = []
Beta = []
position = []
for i in range(1, len(ma)):
print('Process MA'+str(ma[i]))
test.backtest(ma_1=str(ma[i]), ma_2=str(ma[i]))
comb.append(str(ma[i]))
# 不变为0,return, drawback,beta 都是 delta%变化
return_.append(float(test._df[len(test._df)-1:len(test._df)]['return'][0]-1)*100)
drawback.append(str(max(test._df.drawdown)*100))
Beta.append((test._df[len(test._df)-1:len(test._df)]['beta'][0]-1)*100)
position.append(test._df.position[len(test._df)-1])
# test._df.to_csv('1234.csv')
test = hs_300_strategy(df)
return pd.DataFrame({'MA':comb,'return':return_,'Beta':Beta,'drawback':drawback,
'start':test._df.index[0],'end':test._df.index[len(test._df)-1],
'position':position}).set_index('MA')
if __name__ == '__main__':
# df = get_his_data('hs300',ma = [5,12,13,18,20,30,60,120])
# print(df)
i=60
ma = [1,i]
df_all = get_his_data('hs300', ma=ma)
result = test_(ma,df_all)
print(result)
self.if_monkey(longest_period=longest_period)
self.long_or_short()
self._equity()
self._win_lose()
self._drawdown()
self._return_rate()
self.long_short_count()
self._beta()
print('最大回撤:' + str(max(self.drawdown) * 100) + '%')
print('买入信号统计:' + str(self.long_count))
print('卖出信号统计:' + str(self.short_count))
print('全仓平仓亏损:' + str(self.lost_rate))
print('全仓平仓赢: ' + str(self.win_rate))
print('最大回报:' + str((self._df['return'].max() - 1) * 100) + '%')
print('最大亏损:' + str((self._df['return'].min() - 1) * 100) + '%')
print('总回报:' + str(self._df[len(self._df) - 1:len(self._df)]['return']))
return self._df
if __name__=='__main__':
df = get_his_data('513100',ma=[3,60,120,250])
print(df)
#df = get_his_data('162411',ma=[4,5,13,12,20,30,60,120,18,14])
print(df)
test = NSDK(df)
#print(test._df)
pgraph = test.backtest()
print('start date: ' + test.start_date)
test._df.to_csv('test3.csv')
#test.coef_find()
pgraph = get_rid_unchanged_equity(pgraph)
plot_return_beta(pgraph)
all_return[str(ma[i]) + ',' + str(ma[k])] = test.backtest(ma_1=str(ma[k]), ma_2=str(ma[i]))
#test._df.to_csv('test!!!'+str(i)+'.csv')
comb.append(str(ma[i]) + ',' + str(ma[k]))
return_.append(str((test._df[len(test._df)-1:len(test._df)]['return'][0]-1)*100)+'%')
drawback.append(str(max(test._df.drawdown)*100)+'%')
Beta.append(test._df[len(test._df)-1:len(test._df)]['beta'][0])
test = hs_300_strategy(df)
print('Get result of (' + str(ma[i]) + ',' + str(ma[k]) + '):', end='')
print(all_return[str(ma[i]) + ',' + str(ma[k])])
return pd.DataFrame({'comb':comb,'return':return_,'Beta':Beta,'drawback':drawback,
'start':test._df.index[0],'end':test._df.index[len(test._df)-1]})
if __name__=='__main__':
ma = [1,2,3,4,5,6,7,8,9,10]+[i for i in range(20,40)]+[j for j in range(100, 120)]+[seg for seg in range(230,251)]
df = get_his_data('hs300',ma=ma,start='2014-08-01')
test_1 = hs_300_strategy(df)
all_return_1 = {}
resu = test_(ma,all_return_1,test_1)
resu.to_csv('20_to_40_results_3years',mode='w')
"""
#
df = get_his_data('hs300', ma=ma, start='2015-01-01', end='2015-03-31')
test_2 = hs_300_strategy(df)
all_return_2 = {}
resu = test_(ma, all_return_2, test_2)
resu.to_csv('ma_test_result.csv', mode='a')
#
df = get_his_data('hs300', ma=ma, start='2015-04-01', end='2015-06-31')
test_3 = hs_300_strategy(df)
print(all_return[str(ma[i]) + ',' + str(ma[k])])
return pd.DataFrame({
'comb': comb,
'return': return_,
'Beta': Beta,
'drawback': drawback,
'start': test._df.index[0],
'end': test._df.index[len(test._df) - 1]
})
if __name__ == '__main__':
ma = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] + [i for i in range(20, 40)] + [
j for j in range(100, 120)
] + [seg for seg in range(230, 251)]
df = get_his_data('hs300', ma=ma, start='2014-08-01')
test_1 = hs_300_strategy(df)
all_return_1 = {}
resu = test_(ma, all_return_1, test_1)
resu.to_csv('20_to_40_results_3years', mode='w')
"""
#
df = get_his_data('hs300', ma=ma, start='2015-01-01', end='2015-03-31')
test_2 = hs_300_strategy(df)
all_return_2 = {}
resu = test_(ma, all_return_2, test_2)
resu.to_csv('ma_test_result.csv', mode='a')
#
df = get_his_data('hs300', ma=ma, start='2015-04-01', end='2015-06-31')
test_3 = hs_300_strategy(df)
all_return_3 = {}
elif self._df.bear[i] ==1 and \
self._df.ma_5_close[i] < self._df.ma_5_close[i - 1] and \
self._df.ma_5_close[i - 1] > self._df.ma_5_close[i - 2]:
self._df.loc[i:i + 1, 'short'] = 1
return True, 1, 1
# 猴市---------->
elif self._df.monkey[i] ==1 and \
self._df.ma_5_close[i] < self._df.ma_13_close[i] and \
self._df.ma_5_close[i-1] > self._df.ma_13_close[i-1]:
self._df.loc[i:i + 1, 'short'] = 1
return True, 1, 1
else:
return False, 1, 1
if __name__ == '__main__':
df = get_his_data('hs300',
start='2014-01-01',
ma=[5, 12, 13, 18, 20, 30, 60, 120],
index=True)
#print(df)
#df = read_csv_excel('/Users/leotao/Downloads/沪深300回测.xlsx', '择时分析-创')
#df = MA_CALCULATOR(df)
#df = df.get_ma(ll = [5,12,13,18,20,30,60,120])
test = hs_300_strategy(df)
pgraph = test.backtest()
print('start date: ' + test.start_date)
#test._df.to_csv('test2.csv')
#test.coef_find()
pgraph = get_rid_unchanged_equity(pgraph)
plot_return_beta(pgraph)
return True, 1, 1
else:
return False,1,1
# 猴市---------->
elif self._df.monkey[i] == 1:
if self._df.ma_5_close[i] < self._df.ma_10_close[i] and \
self._df.ma_5_close[i - 1] > self._df.ma_10_close[i - 1]:
self._df.loc[i:i + 1, 'short'] = 1
return True, 1, 1
elif self._df.bull[i-1] ==1 and self._df.ma_5_close[i] < self._df.ma_10_close[i]:
self._df.loc[i:i + 1, 'short'] = 1
return True, 1, 1
else:
return False, 1, 1
else:
return False, 1, 1
if __name__=='__main__':
#df = read_csv_excel('/Users/leotao/Downloads/创业板回测(1).xlsx','择时分析-创')
df = get_his_data('cyb',ma=[4,5,13,20,30,60,120,18,10])
#df = MA_CALCULATOR(df)
#df = df.get_ma(ll =[4,5,13,12,20,30,60,120,18,14])
print(df)
test = CYB(df)
#print(test._df)
pgraph = test.backtest()
print('start date: ' + test.start_date)
test._df.to_csv('test3.csv')
#test.coef_find()
pgraph = get_rid_unchanged_equity(pgraph)
plot_return_beta(pgraph)
from Models.Closed_Price_Prediction_model import arbitrary_prediction
from Strategys.INDEX_STRATEGY.CYB import CYB
from Strategys.INDEX_STRATEGY.Gold_ETF import GOLD_ETF
from Strategys.INDEX_STRATEGY.NSDK import NSDK
from Strategys.INDEX_STRATEGY.hs_300_strategy import hs_300_strategy
from Strategys.INDEX_STRATEGY.petro_ETF import PETRO_ETF
from pitcher import get_his_data
today = datetime.datetime.today()-datetime.timedelta(1)
yesterday = str(today)[0:10]
def tree_predict(df):
xx = arbitrary_prediction(df)
return [xx.one_day_gradient_change()]
start = '2015-10-10'
gold_index = get_his_data('159934',start=start,ma=[4,5,12,13,16,18,20,30,60,120,14],index=True)
gold_index = tree_predict(gold_index)
petro_index = get_his_data('162411',ma=[4,5,12,13,16,18,20,30,60,120,14],start=start,index=True)
petro_index = tree_predict(petro_index)
hs300_index = get_his_data('000300',ma = [5,12,13,16,18,20,30,60,120,14],start=start,index=True)
hs300_index = tree_predict(hs300_index)
return False, 1, 1
# 猴市---------->
elif self._df.monkey[i] == 1:
if self._df.ma_5_close[i] < self._df.ma_10_close[i] and \
self._df.ma_5_close[i - 1] > self._df.ma_10_close[i - 1]:
self._df.loc[i:i + 1, 'short'] = 1
return True, 1, 1
elif self._df.bull[i - 1] == 1 and self._df.ma_5_close[
i] < self._df.ma_10_close[i]:
self._df.loc[i:i + 1, 'short'] = 1
return True, 1, 1
else:
return False, 1, 1
else:
return False, 1, 1
if __name__ == '__main__':
#df = read_csv_excel('/Users/leotao/Downloads/创业板回测(1).xlsx','择时分析-创')
df = get_his_data('cyb', ma=[4, 5, 13, 20, 30, 60, 120, 18, 10])
#df = MA_CALCULATOR(df)
#df = df.get_ma(ll =[4,5,13,12,20,30,60,120,18,14])
print(df)
test = CYB(df)
#print(test._df)
pgraph = test.backtest()
print('start date: ' + test.start_date)
test._df.to_csv('test3.csv')
#test.coef_find()
pgraph = get_rid_unchanged_equity(pgraph)
plot_return_beta(pgraph)
self._equity()
self._win_lose()
self._drawdown()
self._return_rate()
self.long_short_count()
self._beta()
print('最大回撤:' + str(max(self.drawdown) * 100) + '%')
print('买入信号统计:' + str(self.long_count))
print('卖出信号统计:' + str(self.short_count))
print('全仓平仓亏损:' + str(self.lost_rate))
print('全仓平仓赢: ' + str(self.win_rate))
print('最大回报:' + str((self._df['return'].max() - 1) * 100) + '%')
print('最大亏损:' + str((self._df['return'].min() - 1) * 100) + '%')
print('总回报:' +
str(self._df[len(self._df) - 1:len(self._df)]['return']))
return self._df
if __name__ == '__main__':
df = get_his_data('513100', ma=[3, 60, 120, 250])
print(df)
#df = get_his_data('162411',ma=[4,5,13,12,20,30,60,120,18,14])
print(df)
test = NSDK(df)
#print(test._df)
pgraph = test.backtest()
print('start date: ' + test.start_date)
test._df.to_csv('test3.csv')
#test.coef_find()
pgraph = get_rid_unchanged_equity(pgraph)
plot_return_beta(pgraph)
# 不变为0,return, drawback,beta 都是 delta%变化
return_.append(
float(test._df[len(test._df) - 1:len(test._df)]['return'][0] - 1) *
100)
drawback.append(str(max(test._df.drawdown) * 100))
Beta.append(
(test._df[len(test._df) - 1:len(test._df)]['beta'][0] - 1) * 100)
position.append(test._df.position[len(test._df) - 1])
# test._df.to_csv('1234.csv')
test = hs_300_strategy(df)
return pd.DataFrame({
'MA': comb,
'return': return_,
'Beta': Beta,
'drawback': drawback,
'start': test._df.index[0],
'end': test._df.index[len(test._df) - 1],
'position': position
}).set_index('MA')
if __name__ == '__main__':
# df = get_his_data('hs300',ma = [5,12,13,18,20,30,60,120])
# print(df)
i = 60
ma = [1, i]
df_all = get_his_data('hs300', ma=ma)
result = test_(ma, df_all)
print(result)
self._df.loc[i:i + 1, 'short'] = 1
return True,1,1
# 熊市---------->
elif self._df.bear[i] ==1 and \
self._df.ma_5_close[i] < self._df.ma_5_close[i - 1] and \
self._df.ma_5_close[i - 1] > self._df.ma_5_close[i - 2]:
self._df.loc[i:i + 1, 'short'] = 1
return True,1,1
# 猴市---------->
elif self._df.monkey[i] ==1 and \
self._df.ma_5_close[i] < self._df.ma_13_close[i] and \
self._df.ma_5_close[i-1] > self._df.ma_13_close[i-1]:
self._df.loc[i:i + 1, 'short'] = 1
return True,1,1
else:
return False,1,1
if __name__=='__main__':
df = get_his_data('hs300',start='2014-01-01',ma = [5,12,13,18,20,30,60,120],index=True)
#print(df)
#df = read_csv_excel('/Users/leotao/Downloads/沪深300回测.xlsx', '择时分析-创')
#df = MA_CALCULATOR(df)
#df = df.get_ma(ll = [5,12,13,18,20,30,60,120])
test = hs_300_strategy(df)
pgraph = test.backtest()
print('start date: ' + test.start_date)
#test._df.to_csv('test2.csv')
#test.coef_find()
pgraph = get_rid_unchanged_equity(pgraph)
plot_return_beta(pgraph)
all_return[str(ma[i]) + ',' + str(ma[k])] = test.backtest(ma_1=str(ma[k]), ma_2=str(ma[i]))
#test._df.to_csv('test!!!'+str(i)+'.csv')
comb.append(str(ma[i]) + ',' + str(ma[k]))
return_.append(str((test._df[len(test._df)-1:len(test._df)]['return'][0]-1)*100)+'%')
drawback.append(str(max(test._df.drawdown)*100)+'%')
Beta.append(test._df[len(test._df)-1:len(test._df)]['beta'][0])
test = hs_300_strategy(df)
#print('Get result of (' + str(ma[i]) + ',' + str(ma[k]) + '):', end='')
#print(all_return[str(ma[i]) + ',' + str(ma[k])])
return pd.DataFrame({'comb':comb,'return':return_,'Beta':Beta,'drawback':drawback,
'start':test._df.index[0],'end':test._df.index[len(test._df)-1]})
if __name__=='__main__':
ma = [5, 7, 10, 20, 30, 60, 120, 240]
df = get_his_data('hs300',ma=ma,start='2014-08-01',end='2014-12-31')
test_1 = hs_300_strategy(df)
all_return_1 = {}
resu = test_(ma,all_return_1,test_1)
resu.to_csv('ma_test_result.csv',mode='a')
#
df = get_his_data('hs300', ma=ma, start='2015-01-01', end='2015-03-31')
test_2 = hs_300_strategy(df)
all_return_2 = {}
resu = test_(ma, all_return_2, test_2)
resu.to_csv('ma_test_result.csv', mode='a')
#
df = get_his_data('hs300', ma=ma, start='2015-04-01', end='2015-06-31')
test_3 = hs_300_strategy(df)
all_return_3 = {}
resu = test_(ma, all_return_3, test_3)