㈠ 最全集合竞价选股公式：集合竞价选股公式有哪些
集合竞价选股公式有很多，下面例举1个成功率最高的集合竞价选股公式：
ST:=STRFIND(stkname，'ST'，1)>0;
S:=STRFIND(stkname，'S'，1)>0;
停牌:=(DYNAINFO(4)=0);
附加:=CLOSE/ref(CLOSE，5)<1.2 AND CLOSE<37 AND FINANCE2(37)/10000<4;
一字板:=C/REF(C，1)>=1.09 AND O=C;
xg0:=not(ST) and not(停牌) and not(S) AND NOT(一字板);
量比:=V/REF(MA(V，5)，1);
流通盘:=FINANCE2(37)/10000<6;
D1:=ISBUYORDER AND DYNAINFO(9)*C/100>=50;{分笔买入单>50万}
D2:=(DYNAINFO(23)-DYNAINFO(22))/CAPITAL*100>=0.4;{内外盘净};
T1:=DYNAINFO(11)/DYNAINFO(4)>=1.03 AND DYNAINFO(11)/DYNAINFO(4)<=1.05;
T2:=H/DYNAINFO(3)<=1.075 AND C/DYNAINFO(3)<=1.06 AND C>=DYNAINFO(11) AND C
T3:=HOUR=9 AND MINUTE>25.99;{时间控制}
预警:=T1 AND T2 AND T3 AND D1 AND D2;
换手率:=COUNT(VOL/CAPITAL*100<3，3)=0;
现价:=DYNAINFO(7);
均价:=DYNAINFO(11)+(DYNAINFO(11)*0.021);
条件:=IF(现价>均价，1，0);
集合竞价:=量比 AND 流通盘 AND 预警 AND 条件;
选股:XG0 AND 集合竞价;CXH:=STRTONUM(STRRIGHT(DATESTR(CURRENTDATE)，1));
WARNING('http://www.cxh99.com'，CURRENTTIME>180000 and (CXH=1 OR CXH=6));
DRAWTEXTREL(10 ，10 ，'指标公式');
㈡ 求集合竞价规则选股方法的策略源码
# coding=utf-8
from __future__ import print_function, absolute_import, unicode_literals
from gm.api import *
'''
本策略基于掘金量化平台
本策略通过获取SHSE.000300沪深300的成份股数键历搭据并统计其30天内
开盘价大于前收盘价的天数,并在该天数大于阈值10的时候加入股票池
随后对不在股票池的股票平仓并等权配置股票池的标的,每次交易间隔1个月.
回测数据为:SHSE.000300在2015-01-15的成份股
回测时间为:2017-07-01 08:00:00到2017-10-01 16:00:00
'''
def init(context):
# 每月第一个交易稿拿日烂银的09:40 定时执行algo任务
schele(schele_func=algo, date_rule='1m', time_rule='09:40:00')
# context.count_bench累计天数阙值
context.count_bench = 10
# 用于对比的天数
context.count = 30
# 最大交易资金比例
context.ratio = 0.8
def algo(context):
# 获取当前时间
now = context.now
# 获取上一个交易日
last_day = get_previous_trading_date(exchange='SHSE', date=now)
# 获取沪深300成份股
context.stock300 = get_history_constituents(index='SHSE.000300', start_date=last_day,
end_date=last_day)[0]['constituents'].keys()
# 获取当天有交易的股票
not_suspended_info = get_history_instruments(symbols=context.stock300, start_date=now, end_date=now)
not_suspended_symbols = [item['symbol'] for item in not_suspended_info if not item['is_suspended']]
trade_symbols = []
if not not_suspended_symbols:
print('没有当日交易的待选股票')
return
for stock in not_suspended_symbols:
recent_data = history_n(symbol=stock, frequency='1d', count=context.count, fields='pre_close,open',
fill_missing='Last', adjust=ADJUST_PREV, end_time=now, df=True)
diff = recent_data['open'] - recent_data['pre_close']
# 获取累计天数超过阙值的标的池.并剔除当天没有交易的股票
if len(diff[diff > 0]) >= context.count_bench:
trade_symbols.append(stock)
print('本次股票池有股票数目: ', len(trade_symbols))
# 计算权重
percent = 1.0 / len(trade_symbols) * context.ratio
# 获取当前所有仓位
positions = context.account().positions()
# 如标的池有仓位,平不在标的池的仓位
for position in positions:
symbol = position['symbol']
if symbol not in trade_symbols:
order_target_percent(symbol=symbol, percent=0, order_type=OrderType_Market,
position_side=PositionSide_Long)
print('市价单平不在标的池的', symbol)
# 对标的池进行操作
for symbol in trade_symbols:
order_target_percent(symbol=symbol, percent=percent, order_type=OrderType_Market,
position_side=PositionSide_Long)
print(symbol, '以市价单调整至权重', percent)
if __name__ == '__main__':
'''
strategy_id策略ID,由系统生成
filename文件名,请与本文件名保持一致
mode实时模式:MODE_LIVE回测模式:MODE_BACKTEST
token绑定计算机的ID,可在系统设置-密钥管理中生成
backtest_start_time回测开始时间
backtest_end_time回测结束时间
backtest_adjust股票复权方式不复权:ADJUST_NONE前复权:ADJUST_PREV后复权:ADJUST_POST
backtest_initial_cash回测初始资金
backtest_commission_ratio回测佣金比例
backtest_slippage_ratio回测滑点比例
'''
run(strategy_id='strategy_id',
filename='main.py',
mode=MODE_BACKTEST,
token='token_id',
backtest_start_time='2017-07-01 08:00:00',
backtest_end_time='2017-10-01 16:00:00',
backtest_adjust=ADJUST_PREV,
backtest_initial_cash=10000000,
backtest_commission_ratio=0.0001,
backtest_slippage_ratio=0.0001)