def backtest_monthRP_Up(mainParament):
Temp_change = 0 #換股剩餘天數
userInfo = get_user_info.data_user_info(mainParament.money_start,
mainParament.date_start,
mainParament.date_end)
Temp_result_pick = pd.DataFrame(columns=['date', '選股數量'])
while userInfo.now_day <= userInfo.end_day:
#週末直接跳過
if userInfo.now_day.isoweekday() in [6, 7]:
print(
str(userInfo.now_day) + 'is 星期' +
str(userInfo.now_day.isoweekday()))
if userInfo.add_one_day() == False: #加一天
break
continue
#先看看台積有沒有資料，如果沒有表示這天是非週末假日跳過
if get_stock_history.get_stock_price(
2330, userInfo.now_day,
get_stock_history.stock_data_kind.AdjClose) == None:
print(str(userInfo.now_day) + "這天沒開市")
if userInfo.add_one_day() == False: #加一天
break
continue
#出場訊號篩選--------------------------------------
if Temp_change <= 0 and len(userInfo.handle_stock) > 0:
userInfo.sell_all_stock()
#開始篩選--------------------------------------
Temp_result0 = {}
Temp_result = pd.DataFrame()
if Temp_change <= 0:
if bool_check_monthRP_pick: #月營收升高篩選(月為單位)
Temp_result0['month'] = get_stock_history.get_monthRP_up(
userInfo.now_day, mainParament.smoothAVG,
mainParament.upMonth)
if bool_check_ROE_pick: #ROE
Temp_result0['ROE'] = get_stock_history.get_ROE_range(
userInfo.now_day, mainParament.ROE_start,
mainParament.ROE_end)
if bool_check_PBR_pick: #PBR
Temp_result0['PBR'] = get_stock_history.get_PBR_range(
userInfo.now_day, mainParament.PBR_start,
mainParament.PBR_end)
if bool_check_PER_pick: #PER
Temp_result0['PER'] = get_stock_history.get_PER_range(
userInfo.now_day, mainParament.PER_start,
mainParament.PER_end)
Temp_result = tools.MixDataFrames(Temp_result0)
#入場訊號篩選--------------------------------------
if Temp_change <= 0 and len(userInfo.handle_stock) <= 0 and len(
Temp_result) > mainParament.Pick_amount:
Temp_buy0 = {'result': Temp_result}
if bool_check_price_pick:
Temp_buy0['price'] = get_stock_history.get_price_range(
userInfo.now_day, mainParament.price_high,
mainParament.price_low, Temp_result)
Temp_buy0['price'] = Temp_buy0['price'].sort_values(
by='price', ascending=False)
if bool_check_volume_pick:
Temp_buy0['volume'] = get_stock_history.get_AVG_value(
userInfo.now_day, mainParament.volumeAVG,
mainParament.volumeDays, Temp_result)
Temp_buy0['volume'] = Temp_buy0['volume'].sort_values(
by='volume', ascending=False)
Temp_buy = tools.MixDataFrames(Temp_buy0)
#if Temp_buy0['price'].empty == False:
# Temp_buy = Temp_buy.sort_values(by='price', ascending=False)
if Temp_buy0['volume'].empty == False:
Temp_buy = Temp_buy.sort_values(by='volume', ascending=False)
userInfo.buy_all_stock(Temp_buy)
#更新資訊--------------------------------------
if Temp_change <= 0 and len(userInfo.handle_stock) > 0:
Temp_change = mainParament.change_days
userInfo.Record_userInfo()
userInfo.Recod_tradeInfo()
Temp_result_pick = Temp_result_pick.append(
{
'date': userInfo.now_day,
'選股數量': len(Temp_result)
},
ignore_index=True)
#加一天----------------------------
if userInfo.add_one_day() == False:
break
else:
Temp_change = Temp_change - 1
#最後總結算----------------------------
Temp_result_pick.set_index('date', inplace=True)
Temp_alldata = tools.MixDataFrames(
{
'draw': userInfo.Temp_result_draw,
'pick': Temp_result_pick
}, 'date')
draw_figur.draw_backtest(userInfo.Temp_result_draw)
Temp_alldata = tools.MixDataFrames(
{
'all': Temp_alldata,
'userinfo': userInfo.Temp_result_All
}, 'date')
userInfo.Temp_result_draw.to_csv('backtestdata.csv')
userInfo.Temp_trade_info.to_csv('backtesttrade.csv')
Temp_alldata.to_csv('backtestAll.csv')
def backtest_PEG_pick_Fast(mainParament):
userInfo = get_user_info.data_user_info(mainParament.money_start,mainParament.date_start,mainParament.date_end)
buy_month = mainParament.date_start
Temp_result_pick = pd.DataFrame(columns=['date','選股數量'])
All_data = get_stock_history.get_stock_history(mainParament.buy_number,mainParament.date_start)
add_one_day = userInfo.add_one_day
Record_userInfo = userInfo.Record_userInfo
Recod_tradeInfo = userInfo.Recod_tradeInfo
sell_stock = userInfo.sell_stock
buy_all_stock = userInfo.buy_all_stock
for index,row in All_data.iterrows():
has_trade = False
while(userInfo.now_day != index):
#加一天----------------------------
if add_one_day() == False:
break
#出場訊號篩選-----------------------------------
if len(userInfo.handle_stock) > 0:
Temp_data = userInfo.handle_stock
for key,value in list(Temp_data.items()):
if get_stock_history.get_stock_price(key,userInfo.now_day,get_stock_history.stock_data_kind.AdjClose) < get_stock_history.get_stock_MA(key,userInfo.now_day,20):
sell_stock(key,value.amount)
has_trade = True
#開始篩選--------------------------------------
#入場訊號篩選--------------------------------------
Temp_buy = pd.DataFrame()
if userInfo.now_day.day >= mainParament.buy_day:
if userInfo.now_day.month != buy_month.month or userInfo.now_day.year != buy_month.year:
Temp_result0 = {}
if bool_check_monthRP_pick:
Temp_result0['month'] = get_stock_history.get_monthRP_up(userInfo.now_day,mainParament.smoothAVG,mainParament.upMonth)
Temp_result0['PEG'] = get_stock_history.get_PEG_range(userInfo.now_day,0.66,1)
Temp_result0['result'] = MixDataFrames(Temp_result0)
Temp_buy = Temp_result0['result']
if Temp_buy.empty == False:
Temp_buy = Temp_buy.sort_values(by='PEG')
Temp_buy = Temp_buy.head(10)
buy_all_stock(Temp_buy)
has_trade = True
buy_month = userInfo.now_day
#更新資訊--------------------------------------
if len(userInfo.handle_stock) > 0 or has_trade:
Record_userInfo()
Recod_tradeInfo()
Temp_result_pick = Temp_result_pick.append({'date':userInfo.now_day,
'選股數量':len(Temp_buy)},ignore_index = True)
#加一天----------------------------
if userInfo.add_one_day() == False:
break
else:
continue
#最後總結算----------------------------
Temp_result_pick.set_index('date',inplace=True)
Temp_alldata = MixDataFrames({'draw':userInfo.Temp_result_draw,'pick':Temp_result_pick},'date')
Temp_alldata = MixDataFrames({'all':Temp_alldata,'userinfo':userInfo.Temp_result_All},'date')
userInfo.Temp_result_draw.to_csv('backtestdata.csv')
userInfo.Temp_trade_info.to_csv('backtesttrade.csv')
Temp_alldata.to_csv('backtestAll.csv')
return userInfo.Temp_result_draw
def backtest_monthRP_Up_Fast(mainParament):
Temp_change = 0#換股剩餘天數
userInfo = get_user_info.data_user_info(mainParament.money_start,mainParament.date_start,mainParament.date_end)
Temp_result_pick = pd.DataFrame(columns=['date','選股數量'])
All_data = get_stock_history.get_stock_history(mainParament.buy_number,mainParament.date_start)
add_one_day = userInfo.add_one_day
sell_all_stock = userInfo.sell_all_stock
buy_all_stock = userInfo.buy_all_stock
for index,row in All_data.iterrows():
has_trade = False
while(userInfo.now_day != index):
#加一天----------------------------
if add_one_day() == False:
break
#出場訊號篩選--------------------------------------
if Temp_change <= 0 and len(userInfo.handle_stock) > 0:
sell_all_stock()
has_trade = True
#開始篩選--------------------------------------
Temp_result0 = {}
Temp_result = pd.DataFrame()
if Temp_change <= 0:
if bool_check_monthRP_pick:#月營收升高篩選(月為單位)
Temp_result0['month'] = get_stock_history.get_monthRP_up(userInfo.now_day,mainParament.smoothAVG,mainParament.upMonth)
if bool_check_ROE_pick:#ROE
Temp_result0['ROE'] = get_stock_history.get_ROE_range(userInfo.now_day,mainParament.ROE_start,mainParament.ROE_end)
if bool_check_PBR_pick:#PBR
Temp_result0['PBR'] = get_stock_history.get_PBR_range(userInfo.now_day,mainParament.PBR_start,mainParament.PBR_end)
if bool_check_PER_pick:#PER
Temp_result0['PER'] = get_stock_history.get_PER_range(userInfo.now_day,mainParament.PER_start,mainParament.PER_end)
Temp_result = tools.MixDataFrames(Temp_result0)
#入場訊號篩選--------------------------------------
if Temp_change <= 0 and len(userInfo.handle_stock) <= 0 and len(Temp_result) > mainParament.Pick_amount:
Temp_buy0 = {'result':Temp_result}
if bool_check_price_pick:
Temp_buy0['price'] = get_stock_history.get_price_range(userInfo.now_day,mainParament.price_high,mainParament.price_low,Temp_result)
Temp_buy0['price'] = Temp_buy0['price'].sort_values(by='price', ascending=False)
if bool_check_volume_pick:
Temp_buy0['volume'] = get_stock_history.get_AVG_value(userInfo.now_day,mainParament.volumeAVG,mainParament.volumeDays,Temp_result)
Temp_buy0['volume'] = Temp_buy0['volume'].sort_values(by='volume', ascending=False)
Temp_buy = tools.MixDataFrames(Temp_buy0)
if Temp_buy0.__contains__('price') and Temp_buy0['price'].empty == False:
Temp_buy = Temp_buy.sort_values(by='price', ascending=False)
if Temp_buy0.__contains__('volume') and Temp_buy0['volume'].empty == False:
Temp_buy = Temp_buy.sort_values(by='volume', ascending=False)
buy_all_stock(Temp_buy)
has_trade = True
#更新資訊--------------------------------------
if Temp_change <= 0:
Temp_change = mainParament.change_days
if has_trade or len(userInfo.handle_stock) > 0:
userInfo.Record_userInfo()
userInfo.Recod_tradeInfo()
Temp_result_pick = Temp_result_pick.append({'date':userInfo.now_day,
'選股數量':len(Temp_result)},ignore_index = True)
#加一天----------------------------
if add_one_day() == False:
break
else:
Temp_change = Temp_change - 1
#最後總結算----------------------------
Temp_result_pick.set_index('date',inplace=True)
Temp_alldata = tools.MixDataFrames({'draw':userInfo.Temp_result_draw,'pick':Temp_result_pick},'date')
Temp_alldata = tools.MixDataFrames({'all':Temp_alldata,'userinfo':userInfo.Temp_result_All},'date')
userInfo.Temp_result_draw.to_csv('backtestdata.csv')
userInfo.Temp_trade_info.to_csv('backtesttrade.csv')
Temp_alldata.to_csv('backtestAll.csv')
return userInfo.Temp_result_draw
def button_monthRP_Up_click(): #月營收逐步升高篩選
date = tools.QtDate2DateTime(myshow.date_endDate.date())
date_5 = date + timedelta(days=-14) #加一天
if date.isoweekday() == 6:
date = date + timedelta(days=-1) #加一天
elif date.isoweekday() == 7:
date = date + timedelta(days=-2) #加2天
else:
pass
GPM = mypick.input_GPM.toPlainText()
OPR = mypick.input_OPR.toPlainText()
EPS = mypick.input_EPS.toPlainText()
RPS = mypick.input_RPS.toPlainText()
FS_data = pd.DataFrame()
result_data = pd.DataFrame()
BOOK_data = pd.DataFrame()
PER_data = pd.DataFrame()
yield_data = pd.DataFrame()
FS_data = get_financial_statement(date, GPM, OPR, EPS, RPS)
result_data = get_stock_history.get_monthRP_up(
tools.changeDateMonth(date, 0),
int(mypick.input_monthRP_smoothAVG.toPlainText()),
int(mypick.input_monthRP_UpMpnth.toPlainText()))
BOOK_data = get_stock_history.get_PBR_range(
tools.changeDateMonth(date, 0),
float(mypick.input_PBR_low.toPlainText()),
float(mypick.input_PBR_high.toPlainText()))
PER_data = get_stock_history.get_PER_range(
tools.changeDateMonth(date, 0),
float(mypick.input_PER_low.toPlainText()),
float(mypick.input_PER_high.toPlainText()))
ROE_data = get_stock_history.get_ROE_range(
tools.changeDateMonth(date, 0),
float(mypick.input_ROE_low.toPlainText()),
float(mypick.input_ROE_high.toPlainText()))
yield_data = get_stock_history.get_yield_range(
tools.changeDateMonth(date, 0),
float(mypick.input_yiled_high.toPlainText()),
float(mypick.input_yiled_low.toPlainText()))
pick_data = FS_data
if result_data.empty == False:
pick_data = pd.merge(pick_data,
result_data,
left_index=True,
right_index=True,
how='left')
pick_data = pick_data.dropna(axis=0, how='any')
if BOOK_data.empty == False:
pick_data = pd.merge(pick_data,
BOOK_data,
left_index=True,
right_index=True,
how='left')
pick_data = pick_data.dropna(axis=0, how='any')
if PER_data.empty == False:
pick_data = pd.merge(pick_data,
PER_data,
left_index=True,
right_index=True,
how='left')
pick_data = pick_data.dropna(axis=0, how='any')
if ROE_data.empty == False:
pick_data = pd.merge(pick_data,
ROE_data,
left_index=True,
right_index=True,
how='left')
pick_data = pick_data.dropna(axis=0, how='any')
if yield_data.empty == False:
pick_data = pd.merge(pick_data,
yield_data,
left_index=True,
right_index=True,
how='left')
pick_data = pick_data.dropna(axis=0, how='any')
price_data = get_stock_history.get_price_range(
date, int(mypick.input_price_high.toPlainText()),
int(mypick.input_price_low.toPlainText()), pick_data)
if price_data.empty == False:
pick_data = tools.MixDataFrames({
'pick': pick_data,
'price': price_data
})
pick_data = pick_data.dropna(axis=0, how='any')
record_data = get_stock_history.get_RecordHigh_range(
date, int(mypick.input_flash_Day.toPlainText()),
int(mypick.input_record_Day.toPlainText()), pick_data)
if record_data.empty == False:
pick_data = tools.MixDataFrames({
'pick': pick_data,
'recordHigh': record_data
})
pick_data = pick_data.dropna(axis=0, how='any')
pick_data = get_volume(int(mypick.input_volum.toPlainText()),
tools.changeDateMonth(date_5, 0), pick_data)
pick_data = pick_data.dropna(axis=0, how='any')
print("總挑選數量:" + str(len(pick_data)))
mypick.treeView_pick.setModel(
creat_treeView_model(mypick.treeView_pick,
pick_titalList)) #設定treeView功能
set_treeView2(mypick.treeView_pick.model(), pick_data)