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yutiansut / QUANTAXIS

QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
https://yutiansut.github.io/QUANTAXIS/
MIT License
8.25k stars 2.98k forks source link

一次性全市场回测报错问题和portfolio使用方法的咨询 #969

Open Wier123 opened 5 years ago

Wier123 commented 5 years ago

问题反馈

第一个问题 .一次性全市场回测报错问题： 回测时，在backtest_code_list = 里导入全部深市沪市的一千多个股票时必定报错： 03990', '603991', '603993', '603996', '603997', '603998', '603999', '603348', '603596', '603733', '603773', '603876'] , start=2013-01-01, end=2018-10-01 call QA_fetch_stock_day return None Traceback (most recent call last): File "new_backtest_core_biz.py", line 127, in backtest_func(AC, backtest_code_list, backtest_start_date, backtest_end_date) File "new_backtest_core_biz.py", line 19, in backtest_func DATA = QA.QA_fetch_stock_day_adv(code, start, end).to_qfq() AttributeError: 'NoneType' object has no attribute 'to_qfq' PS D:\quant_strategy\QADEMO\QADemo-master\backtest\example>

但只要把同样这些股票分成小部分（每部分几百个股票吧）来回测就完全没问题。请问是我机能有限？还是？QA的这个某个对象空间有限？（后面会贴回测配置信息）

第二个问题： 群里讨论上个问题的时候说到portofolio和portfolioView 两种模式 我要的模式就是最贴近实际小散的实盘模式。回测时也就是一个资金账户，用一个策略backtest_code_list里的所有股票都测试。每一天看哪个股票符合策略要求了就买入（不管有几个），每一天看哪个股票符合策略的退出要求了就退出（不管几个）。最后回测完在看这个账户的情况。和pnl。 我目前的配置应该就是吧？还是说

组合cookie

portfolio_cookie = 'win300' 这里要为none？

以下为 配置信息： import math import csv import QUANTAXIS as QA import time from core_biz import * from QUANTAXIS.QAApplication.QAAnalysis import QA_backtest_analysis_backtest

def backtest_func(AC:QA.QA_Account, code, start:str, end:str): ''' :param AC: QA_Account :param code: 股票代码，字符串或列表 :param start: 回测开始时间字符串 :param end: 回测结束时间字符串 '''

取数并前复权

DATA = QA.QA_fetch_stock_day_adv(code, start, end).to_qfq()

map_strategy = {}
map_action = {}
map_do_sell = {}
map_do_buy = {}

for code in backtest_code_list:
    map_strategy[code] = Strategy()
    map_action[code] = Action(0)
    map_do_buy[code] = False
    map_do_sell[code] = False

for peroid_item in DATA.panel_gen:
    for stock_item in peroid_item.security_gen:
        code = stock_item.code[0]
        date = stock_item.date[0]
        price_close = stock_item.close[0]
        day_vol = stock_item.volume[0]
        price_open = stock_item.open[0]
        sell_available_amount = AC.sell_available.get(code, 0)

        order = None
        if map_do_sell[code]:
            map_do_sell[code] = False
            if sell_available_amount <= 0:
                print("nothing to sell for:", code)
            else:
                print("-------->>>>>>>>>>>>------", date, "--------<<<<<<<<<<<<<<------")
                print('CODE:', code, "SELL", " amount: ", map_action[code].amount)
                order_data = {}
                order_data['bid_model'] = 1

                order = AC.send_order(
                code=code, 
                time=date, 
                towards=map_action[code].towards,
                order_model=QA.ORDER_MODEL.MARKET, 
                amount_model=QA.AMOUNT_MODEL.BY_AMOUNT,
                amount=map_action[code].amount,
                price=0)

        if map_do_buy[code]:
            map_do_buy[code] = False
            print("-------->>>>>>>>>>>>------", date, "--------<<<<<<<<<<<<<<------")
            print('CODE:', code, "BUY", " amount: ", map_action[code].amount)
            order = {}
            order['bid_model'] = 1

            order = AC.send_order(
            code=code, 
            time=date, 
            towards=map_action[code].towards,
            order_model=QA.ORDER_MODEL.MARKET,
            amount_model=QA.AMOUNT_MODEL.BY_AMOUNT,
            amount=map_action[code].amount,
            price=price_open)

        if order is not None and order:
            Broker.receive_order(QA.QA_Event(order=order, market_data=stock_item))
            trade_mes = Broker.query_orders(AC.account_cookie, 'filled')
            res = trade_mes.loc[order.account_cookie, order.realorder_id]
            order.trade(res.trade_id, res.trade_price,
            res.trade_amount, res.trade_time)

        (map_action[code], status) = map_strategy[code].updateByToDayClose(price_close, day_vol)
        print(date, code, price_close)
        if map_action[code].towards != 0:
            if map_action[code].towards == -1:
                map_do_sell[code] = True
            elif map_action[code].towards == 1:
                map_do_buy[code] = True

    # 当天结算
    AC.settle()

if name == 'main':

策略名称

strategy_name = 'default'
# 用户cookie
user_cookie = 'user1'
# 组合cookie
portfolio_cookie = 'win300'
# 账户cookie
account_cookie = 'bba'
benchmark_code = '000300'
initial_cash = 200000
initial_hold = {}
commission_coeff = 0.00025 # 交易佣金
tax_coeff = 0.0015# 印花税
backtest_code_list = ['600000','600004','600006','600007','600008','600009','600010','600011','600012','600015','600016','600017','600018','600019','600020','600021','600022','600023','600025','600026','600027','600028','600029','600030','600031','600033','600035','600036','600037','600038','600039','600048','600050','600051','600052','600053','600054','600055','600056','600057','600058','600059','600060','600061','600062','600063','600064','600066','600067','600068','600069','600070','600071','600072','600073','600074','600075','600076','600077','600078','600079','600080','600081','600082','600083','600084','600085','600086','600088','600089','600090','600091','600093','600094','600095','600096','600097','600098','600099','600100','600101','600103','600104','600105','600106','600107','600108','600109','600110','600111','600112','600113','600114','600115','600116','600117','600118','600119','600120','600121','600122','600123','600125','600126','600127','600128','600129','600130','600131','600132','600133','600136','600137','600138','600139','600141','600143','600145','600146','600148','600149','600150','600151','600152','600153','600155','600156','600158','600159','600160','600161','600162','600163','600165','600166','600167','600168','600169','600170','600171','600172','600173','600175','600176','600177','600178','600179','600180','600182','600183','600184','600185','600186','600187','600188','600189','600190','600191','600192','600193','600195','600196','600197','600198','600199','600200','600201','600202','600203','600206','600207','600208','600209','600210','600211','600212','600213','600215','600216','600217','600218','600219','600220','600221','600222','600223','600225','600226','600227','600228','600229','600230','600231','600232','600233','600234','600235','600236','600237','600238','600239','600240','600241','600242','600243','600247','600248','600249','600250','600251','600252','600255','600256','600257','600258','600259','600260','600261','600262','600265','600266','600267','600268','600269','600270','600271','600272','600273','600275','600276','600277','600278','600279','600280','600281','600282','600283','600284','600287','600288','600289','600290','600291','600292','600293','600295','600297','600298','600299','600300','600301','600302','600303','600305','600306','600307','600308','600309','600310','600311','600312','600313','600315','600316','600317','600318','600319','600320','600321','600322','600323','600325','600326','600327','600328','600329','600330','600331','600332','600333','600335','600336','600337','600338','600339','600340','600343','600345','600346','600348','600350','600351','600352','600353','600354','600355','600356','600358','600359','600360','600361','600362','600363','600365','600366','600367','600368','600369','600370','600371','600372','600373','600375','600376','600377','600378','600379','600380','600381','600382','600383','600385','600386','600387','600388','600389','600390','600391','600392','600393','600395','600396','600397','600398','600399','600400','600403','600405','600406','600408','600409','600410','600415','600416','600418','600419','600420','600421','600422','600423','600425','600426','600428','600429','600433','600435','600436','600439','600444','600446','600448','600449','600452','600455','600456','600458','600459','600460','600461','600462','600463','600466','600467','600468','600469','600470','600475','600476','600477','600478','600479','600480','600481','600482','600483','600485','600486','600487','600488','600489','600491','600493','600495','600496','600497','600498','600499','600500','600501','600502','600503','600505','600506','600507','600508','600509','600510','600511','600512','600513','600515','600516','600517','600518','600519','600520','600521','600522','600523','600525','600526','600527','600528','600529','600530','600531','600532','600533','600535','600536','600537','600538','600539','600540','600543','600545','600546','600547','600548','600549','600550','600551','600552','600555','600556','600557','600558','600559','600560','600561','600562','600563','600565','600566','600567','600568','600569','600570','600571','600572','600573','600575','600576','600577','600578','600579','600580','600581','600582','600583','600584','600585','600586','600587','600588','600589','600590','600592','600593','600594','600595','600596','600597','600598','600599','600600','600601','600602','600603','600604','600605','600606','600608','600609','600610','600611','600612','600613','600614','600615','600616','600617','600618','600619','600620','600621','600622','600623','600624','600626','600628','600629','600630','600633','600634','600635','600636','600637','600638','600639','600641','600642','600643','600644','600645','600647','600648','600649','600650','600651','600652','600653','600654','600655','600657','600658','600660','600661','600662','600663','600664','600665','600666','600667','600668','600671','600673','600674','600675','600676','600677','600678','600679','600681','600682','600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backtest_start_date = '2013-01-01'
backtest_end_date = '2018-10-01'
Broker = QA.QA_BacktestBroker()
AC = QA.QA_Account(
    strategy_name=strategy_name,
    user_cookie=user_cookie,
    portfolio_cookie=portfolio_cookie,
    account_cookie=account_cookie,
    init_hold=initial_hold,
    init_cash=initial_cash,
    commission_coeff=commission_coeff,
    tax_coeff=tax_coeff,
    market_type=QA.MARKET_TYPE.STOCK_CN,
    frequence=QA.FREQUENCE.DAY
    )
backtest_func(AC, backtest_code_list, backtest_start_date, backtest_end_date)

print('-------------------------done---------------------')
print(AC.message)
print(AC.history_table)

performance=QA.QA_Performance(AC)
print(performance.pnl_fifo)

performance.pnl_fifo.to_csv('./result.csv')

__file_name_2 = 'D:\\quant_strategy\QUANTAXIS_RESULT\pnl-' + strategy_name + str(time.time()) + '.csv'
performance.pnl_fifo.to_csv(__file_name_2)

#评价csv

您使用的QUANTAXIS版本号是什么?

您的系统信息(包括系统版本,系统架构(32/64),内存大小等等)

x64   8g

您的系统环境是什么?

- monodb
- nodejs(V9以下版本)
- python3.5/3.6
- docker(无)

您需要反馈的问题

感谢您的反馈 如有意见和建议,请在此说明:

您的联系方式(QQ/EMAIL)

QQ.87532775

THANKS by yutiansut 2017.12

Wier123 commented 5 years ago

关于portofolio和portfolioView 两种模式的文档 https://book.yutiansut.com/Documents/QUANTAXIS%E5%9B%9E%E6%B5%8B%E5%88%86%E6%9E%90%E5%85%A8%E8%BF%87%E7%A8%8B%E8%AE%B2%E8%A7%A3.html 我看了也找了。代码里的account.md readme.me。。。没看到具体说明。。但我是不要组合的方法。应该就是这样吧？

yutiansut commented 5 years ago

欸? 我才看到 你记得at我下 @Wier123 类似这样 我研究下

Wier123 commented 5 years ago

哦哦还可以at的啊。。@yutiansut。ok。你看看是什么问题。谢谢。

zhangshoug commented 5 years ago

@Wier123 我要的模式就是最贴近实际小散的实盘模式。回测时也就是一个资金账户，用一个策略backtest_code_list里的所有股票都测试。每一天看哪个股票符合策略要求了就买入（不管有几个），每一天看哪个股票符合策略的退出要求了就退出（不管几个）。 你这个实现了吗? 我的实盘模式与你这个有点小差别: 1、我每天更新backtest_code_list,每天根据设定的条件往里面加股票和清除股票. 2、每一天看哪个股票符合策略要求了就买入（不管有几个），每一天看哪个股票符合策略的退出要求了就退出（不管几个）。 这个还是要限制买入数量：最多持有几支股。（小散资金有限，不可能无限买） 主要是第一个每天更新backtest_code_list，更新股池。第二个自己打分排序和根据已有持仓实现。 整个过程我已在rqalpha上实现，只用QA还没有实现这样的过程。

yutiansut commented 5 years ago

@zhangshoug 你的backtest_code_list 更新逻辑是要全市场选的吗

选出来以后 account.send_order就可以了