def button_getStockHistory(): #存更新日期 date = myshow.date_startDate.date() str_date = str(date.year()) + '-' + str(date.month()) + '-' + str( date.day()) df.Clear_PICS() if myshow.input_stockNumber.toPlainText() == "": for key, value in get_stock_info.stock_list.items(): m_history = get_stock_history.get_stock_history(key, str_date) return elif myshow.input_stockNumber.toPlainText() == "Update": str_date = [str_date] new_thread = threading.Thread(target=Update_StockData_threading, args=str_date) new_thread.setDaemon(True) new_thread.start() return else: stock_number = myshow.input_stockNumber.toPlainText() if myshow.check_UseNewInfo.isChecked(): m_history = get_stock_history.get_stock_history(stock_number, str_date, reGetInfo=False) else: m_history = get_stock_history.get_stock_history(stock_number, str_date, reGetInfo=False, UpdateInfo=False) check_SMA_isCheck(m_history, get_stock_info.Get_stock_info(stock_number)) check_Volume_isCheck(m_history, get_stock_info.Get_stock_info(stock_number)) check_KD_isCheck(m_history, get_stock_info.Get_stock_info(stock_number)) check_BollingerBands_isCheck( m_history, get_stock_info.Get_stock_info(stock_number)) check_RSI_isCheck(m_history, get_stock_info.Get_stock_info(stock_number)) Check_ADL_isCheck() Check_ADLs_isCheck() Check_MACD_isCheck(m_history) check_price_isCheck( m_history, get_stock_info.Get_stock_info(stock_number)) #壹定要在最後面檢查
def Update_StockData_threading(str_date): #異步更新所有台股資料 lock.acquire() for key, value in get_stock_info.ts.codes.items(): if value.market == "上市" and len(value.code) == 4: if get_stock_history.check_no_use_stock(value.code) == True: print('get_stock_price: ' + str(value.code) + ' in no use') continue m_history = get_stock_history.get_stock_history( value.code, str_date) print("get " + str(value.code) + " info susess!") #存更新日期 get_stock_info.Update_date = str(datetime.today())[0:10] get_stock_info.Save_Update_date() lock.acquire()
def backtest_Regular_quota_Fast(mainParament): userInfo = get_user_info.data_user_info(0,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 buy_stock = userInfo.buy_stock for index,row in All_data.iterrows(): while(userInfo.now_day != index):#消掉假日的誤差用的 #加一天---------------------------- if add_one_day() == False: break #開始篩選-------------------------------------- #定期定額不用篩選-------------------------------------- #入場訊號篩選-------------------------------------- if userInfo.now_day.month != buy_month.month and userInfo.now_day.day >= mainParament.buy_day: Temp_price = row['Adj Close'] userInfo.now_money = userInfo.now_money + mainParament.money_start userInfo.start_money = userInfo.start_money + mainParament.money_start Temp_stockNumber = Count_Stock_Amount(mainParament.money_start,Temp_price) buy_stock(mainParament.buy_number,Temp_stockNumber) buy_month = userInfo.now_day #更新資訊-------------------------------------- Record_userInfo() Recod_tradeInfo() Temp_result_pick = Temp_result_pick.append({'date':userInfo.now_day, '選股數量':1},ignore_index = True) #加一天---------------------------- if add_one_day() == False: break #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_KD_pick(mainParament): 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']) Temp_table = get_stock_history.get_stock_history(2330, userInfo.start_day, reGetInfo=False, UpdateInfo=False) All_stock_signal = dict() for key, value in get_stock_info.ts.codes.items(): if value.market == "上市" and len(value.code) == 4: if get_stock_history.check_no_use_stock(value.code) == True: print('get_stock_price: ' + str(value.code) + ' in no use') continue table = get_stock_history.get_stock_history(value.code, userInfo.start_day, reGetInfo=False, UpdateInfo=False) table_K, table_D = talib.STOCH(table['High'], table['Low'], table['Close'], fastk_period=50, slowk_period=20, slowk_matype=0, slowd_period=20, slowd_matype=0) table_sma10 = talib.SMA(np.array(table['Close']), 10) table_sma240 = talib.SMA(np.array(table['Close']), 240) signal_buy = (table_K > table_D) signal_sell = (table_K < table_D) signal_sma10 = table.Close < table_sma10 signal_sma240 = table.Close > table_sma240 signal = signal_buy.copy() signal = (signal_sma10 & signal_sma240 & signal_buy) signal[signal_sell] = -1 All_stock_signal[value.code] = signal ROE_record_day = datetime.datetime(2000, 1, 1) buy_data = pd.DataFrame(columns=['Date', '公司代號']).set_index('Date') sell_data = pd.DataFrame(columns=['Date', '公司代號']).set_index('Date') ROE_data = {} jump_day = 240 for index, row in Temp_table.iterrows(): while userInfo.now_day < index: userInfo.add_one_day() if jump_day > 0: jump_day = jump_day - 1 continue if ROE_record_day <= index: ROE_data = {} ROE_record_day = tools.changeDateMonth(index, 1) BOOK_data = get_stock_history.get_allstock_financial_statement( tools.changeDateMonth(index, -3), get_stock_history.FS_type.BS) CPL_data = get_stock_history.get_allstock_financial_statement( tools.changeDateMonth(index, -3), get_stock_history.FS_type.CPL) ROE_data["ROE_data_1"] = pd.DataFrame({ 'ROE_data_1': (CPL_data["本期綜合損益總額(稅後)"] / BOOK_data['權益總額']) * 100 }) BOOK_data = get_stock_history.get_allstock_financial_statement( tools.changeDateMonth(index, -6), get_stock_history.FS_type.BS) CPL_data = get_stock_history.get_allstock_financial_statement( tools.changeDateMonth(index, -6), get_stock_history.FS_type.CPL) ROE_data["ROE_data_2"] = pd.DataFrame({ 'ROE_data_2': (CPL_data["本期綜合損益總額(稅後)"] / BOOK_data['權益總額']) * 100 }) BOOK_data = get_stock_history.get_allstock_financial_statement( tools.changeDateMonth(index, -9), get_stock_history.FS_type.BS) CPL_data = get_stock_history.get_allstock_financial_statement( tools.changeDateMonth(index, -9), get_stock_history.FS_type.CPL) ROE_data["ROE_data_3"] = pd.DataFrame({ 'ROE_data_3': (CPL_data["本期綜合損益總額(稅後)"] / BOOK_data['權益總額']) * 100 }) BOOK_data = get_stock_history.get_allstock_financial_statement( tools.changeDateMonth(index, -12), get_stock_history.FS_type.BS) CPL_data = get_stock_history.get_allstock_financial_statement( tools.changeDateMonth(index, -12), get_stock_history.FS_type.CPL) ROE_data["ROE_data_4"] = pd.DataFrame({ 'ROE_data_4': (CPL_data["本期綜合損益總額(稅後)"] / BOOK_data['權益總額']) * 100 }) mask = tools.MixDataFrames(ROE_data) ROE_data_result = (mask["ROE_data_1"] + mask["ROE_data_2"] + mask["ROE_data_3"] + mask["ROE_data_4"]) / 4 ROE_data_result = ROE_data_result.dropna() ROE_data = mask["ROE_data_1"] > ROE_data_result buy_numbers = [] sell_numbers = [] for i, value in All_stock_signal.items(): try: if value[index] == True: if ROE_data.index.__contains__(int(i)): if ROE_data[int(i)] == True: buy_numbers.append(i) elif value[index] < 0: sell_numbers.append(i) except: #print('error:' + str(index) + ' at ' + str(i)) continue #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 sell_numbers.__contains__(key): userInfo.sell_stock(key, value.amount) #入場訊號篩選-------------------------------------- if len(buy_numbers) > 0: Temp_buy = pd.DataFrame(columns={'公司代號', 'volume'}) for number in buy_numbers: volume = get_stock_history.get_stock_price( number, tools.DateTime2String(userInfo.now_day), get_stock_history.stock_data_kind.Volume) Temp_buy = Temp_buy.append({ '公司代號': number, 'volume': volume }, ignore_index=True) Temp_buy = Temp_buy.sort_values(by='volume', ascending=False).set_index('公司代號') userInfo.buy_all_stock(Temp_buy) if len(buy_numbers) != 0: buy_data = buy_data.append({ 'Date': index, '公司代號': buy_numbers }, ignore_index=True) if len(sell_numbers) != 0: sell_data = sell_data.append({ 'Date': index, '公司代號': sell_numbers }, ignore_index=True) #更新資訊-------------------------------------- userInfo.Record_userInfo() userInfo.Recod_tradeInfo() Temp_result_pick = Temp_result_pick.append( { 'date': userInfo.now_day, '選股數量': len(buy_numbers) }, ignore_index=True) buy_data = buy_data.set_index('Date') buy_data.to_csv('buy.csv') sell_data = sell_data.set_index('Date') sell_data.to_csv('sell.csv') #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.set_index('date')) Temp_alldata = tools.MixDataFrames( { 'all': Temp_alldata, 'userinfo': userInfo.Temp_result_All }, 'date') userInfo.Temp_result_draw.set_index('date').to_csv('backtestdata.csv') userInfo.Temp_trade_info.set_index('date').to_csv('backtesttrade.csv') Temp_alldata.set_index('date').to_csv('backtestAll.csv')
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 backtest_PERandPBR_Fast(mainParament): Temp_reset = 0#休息日剩餘天數 Temp_changeDays = 0#換股剩餘天數 Temp_result_pick = pd.DataFrame(columns=['date','選股數量']) userInfo = get_user_info.data_user_info(mainParament.money_start,mainParament.date_start,mainParament.date_end) 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 #休息日直接跳過 if Temp_reset > 0 and len(userInfo.handle_stock) == 0: print(str(userInfo.now_day) + ' is reset time:第' + str(Temp_reset) + '天') if add_one_day() == False:#加一天 break Temp_reset = Temp_reset - 1 continue #開始篩選-------------------------------------- Temp_result0 = {} Temp_result = pd.DataFrame() if bool_check_PER_pick:#PER pick Temp_result0['PER'] = get_stock_history.get_PER_range(userInfo.now_day,mainParament.PER_start,mainParament.PER_end) if bool_check_PBR_pick:#PBR pick Temp_result0['PBR'] = get_stock_history.get_PBR_range(userInfo.now_day,mainParament.PBR_start,mainParament.PBR_end) Temp_result = tools.MixDataFrames(Temp_result0) #出場訊號篩選-------------------------------------- if len(Temp_result) < mainParament.Pick_amount and len(userInfo.handle_stock) > 0: sell_all_stock() Temp_reset = 120 has_trade = True #出場訊號篩選-------------------------------------- if Temp_changeDays <= 0 and len(userInfo.handle_stock) > 0: sell_all_stock() has_trade = True #入場訊號篩選-------------------------------------- if len(Temp_result) >= mainParament.Pick_amount and Temp_reset == 0 and len(userInfo.handle_stock) == 0: 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) Temp_changeDays = mainParament.change_days has_trade = True #更新資訊-------------------------------------- if len(userInfo.handle_stock) > 0 or has_trade == True: 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_changeDays = Temp_changeDays - 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 backtest_Record_high_Fast(mainParament): Temp_reset = 0#休息日剩餘天數 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 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-------------------------------------- Temp_result = pd.DataFrame() Temp_result0 = {} if Temp_reset <= 0: if bool_check_ROE_pick == True: Temp_result0['ROE'] = get_stock_history.get_ROE_range(userInfo.now_day,mainParament.ROE_start,mainParament.ROE_end) if bool_check_ROE_pick == True: Temp_result0['ROE_last_seson'] = get_stock_history.get_ROE_range(userInfo.now_day - timedelta(weeks = 4),1,10000) if bool_check_PBR_pick: Temp_result0['PBR'] = get_stock_history.get_PBR_range(userInfo.now_day,mainParament.PBR_start,mainParament.PBR_end) Temp_result = MixDataFrames(Temp_result0) #入場訊號篩選-------------------------------------- if Temp_reset <= 0 and len(Temp_result) > 0: Temp_buy0 = {'result':Temp_result} # if bool_check_PBR_pick: # Temp_buy0['PBR'] = get_stock_history.get_PBR_range(userInfo.now_day,mainParament.PBR_start,mainParament.PBR_end,Temp_result) # Temp_buy0['result'] = MixDataFrames(Temp_buy0) 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['result'] = MixDataFrames(Temp_buy0) 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['result'] = MixDataFrames(Temp_buy0) Temp_buy0['result']['point'] = (Temp_result['ROE'] / Temp_result['ROE_R']) / Temp_result['PBR'] # for index,row in Temp_result.iterrows(): # try: # temp = Temp_buy0['PBR'].at[index,'PBR'] # except: # continue # if get_stock_history.check_no_use_stock(index): # continue # Temp_point = (row['ROE'] / row['ROE_R']) / Temp_buy0['PBR'].at[index,'PBR'] # Temp_buy0['point'] = Temp_buy0['point'].append({'code':index,'point':Temp_point},ignore_index=True) # Temp_buy0['point'] = Temp_buy0['point'].astype({'code':'int','point':'float'}) # Temp_buy0['point'] = Temp_buy0['point'].set_index('code') Temp_buy = MixDataFrames(Temp_buy0) Temp_buy = Temp_buy.sort_values(by='point', ascending=False) Temp_buy1 = {'result':Temp_buy} Temp_buy1['high'] = get_stock_history.get_RecordHigh_range(userInfo.now_day,mainParament.change_days,mainParament.Record_high_day,Temp_buy) Temp_buy = MixDataFrames(Temp_buy1) if Temp_buy.empty == False: Temp_buy = Temp_buy.sort_values(by='point', ascending=False) Temp_buy = Temp_buy.head(3) buy_all_stock(Temp_buy) has_trade = True #更新資訊-------------------------------------- if Temp_reset <= 0: Temp_reset = mainParament.change_days 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_result)},ignore_index = True) #加一天---------------------------- if add_one_day() == False: break else: Temp_reset = Temp_reset - 1 #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_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_KD_pick(mainParament): 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']) Temp_table = get_stock_history.get_stock_history(2330,"2005-01-01",reGetInfo = False,UpdateInfo = False) All_stock_signal = dict() ROE_record_day = datetime.strptime("2000-01-01","%Y-%m-%d") buy_data = pd.DataFrame(columns = ['Date','code']).set_index('Date') sell_data = pd.DataFrame(columns = ['Date','code']).set_index('Date') ROE_data = {} add_one_day = userInfo.add_one_day changeDateMonth = tools.changeDateMonth get_ROE_range = get_stock_history.get_ROE_range MixDataFrames = tools.MixDataFrames sell_stock = userInfo.sell_stock buy_all_stock = userInfo.buy_all_stock for index,row in Temp_table.iterrows(): if index < userInfo.now_day: continue while userInfo.now_day != index: if add_one_day() == False: break has_trade = False #ROE篩選 if ROE_record_day <= index: ROE_data = {} ROE_record_day = changeDateMonth(index,1) ROE_data["ROE_data_1"] = pd.DataFrame(get_ROE_range(changeDateMonth(index,-3),0,999)) ROE_data["ROE_data_1"].rename(columns={'ROE':'ROE_data_1'},inplace=True) ROE_data["ROE_data_2"] = pd.DataFrame(get_ROE_range(changeDateMonth(index,-6),0,999)) ROE_data["ROE_data_2"].rename(columns={'ROE':'ROE_data_2'},inplace=True) ROE_data["ROE_data_3"] = pd.DataFrame(get_ROE_range(changeDateMonth(index,-9),0,999)) ROE_data["ROE_data_3"].rename(columns={'ROE':'ROE_data_3'},inplace=True) ROE_data["ROE_data_4"] = pd.DataFrame(get_ROE_range(changeDateMonth(index,-12),0,999)) ROE_data["ROE_data_4"].rename(columns={'ROE':'ROE_data_4'},inplace=True) mask = MixDataFrames(ROE_data) ROE_data_result =(mask["ROE_data_1"]+mask["ROE_data_2"]+mask["ROE_data_3"]+mask["ROE_data_4"])/4 ROE_data_result = ROE_data_result.dropna() ROE_data_mask = mask["ROE_data_1"]> ROE_data_result ROE_data = ROE_data_mask[ROE_data_mask] for key,value in ROE_data.iteritems():#先算出股票的買賣訊號 if get_stock_history.check_no_use_stock(key) == True: print('get_stock_price: ' + str(key) + ' in no use') continue if All_stock_signal.__contains__(key): continue table = get_stock_history.get_stock_history(key,"2005-01-01",reGetInfo = False,UpdateInfo = False) table_K,table_D = talib.STOCH(table['High'],table['Low'],table['Close'],fastk_period=50, slowk_period=20, slowk_matype=0, slowd_period=20, slowd_matype=0) table_sma10 = talib.SMA(np.array(table['Close']), 10) table_sma240 = talib.SMA(np.array(table['Close']), 240) signal_buy = (table_K > table_D) signal_sell = (table_K < table_D) signal_sma10 = table.Close < table_sma10 signal_sma240 = table.Close > table_sma240 signal = signal_buy.copy() signal = (signal_sma10 & signal_sma240 & signal_buy) signal[signal_sell] = -1 All_stock_signal[key] = signal #找出買入訊號跟賣出訊號------------------------- buy_numbers = [] sell_numbers = [] for i,value in All_stock_signal.items(): try: if value[index] == True: if ROE_data.index.__contains__(int(i)): if ROE_data[int(i)] == True: buy_numbers.append(i) elif value[index] < 0 : sell_numbers.append(i) except: #print('error:' + str(index) + ' at ' + str(i)) continue #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 sell_numbers.__contains__(int(key)): sell_stock(key,value.amount) has_trade = True #入場訊號篩選-------------------------------------- if len(buy_numbers) > 0 : Temp_buy = pd.DataFrame(columns={'code','volume'}) for number in buy_numbers: volume = get_stock_history.get_stock_price(number,tools.DateTime2String(userInfo.now_day),get_stock_history.stock_data_kind.Volume) Temp_buy = Temp_buy.append({'code':str(number),'volume':volume},ignore_index = True) Temp_buy = Temp_buy.sort_values(by='volume', ascending=False).set_index('code') buy_all_stock(Temp_buy) has_trade = True #更新資訊-------------------------------------- if has_trade: if len(buy_numbers) != 0: buy_data = buy_data.append({'Date':index,'code':buy_numbers},ignore_index = True) if len(sell_numbers) != 0: sell_data = sell_data.append({'Date':index,'code':sell_numbers},ignore_index = True) userInfo.Record_userInfo() userInfo.Recod_tradeInfo() Temp_result_pick = Temp_result_pick.append({'date':userInfo.now_day, '選股數量':len(buy_numbers)},ignore_index = True) buy_data = buy_data.set_index('Date') buy_data.to_csv('buy.csv') sell_data = sell_data.set_index('Date') sell_data.to_csv('sell.csv') #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.set_index('date').to_csv('backtestdata.csv') userInfo.Temp_trade_info.set_index('date').to_csv('backtesttrade.csv') Temp_alldata.set_index('date').to_csv('backtestAll.csv') return userInfo.Temp_result_draw.set_index('date')