策略代码
# 回测条件：2012-01-01 到 2024-07-11, ￥100000, 每天
from jqdata import *
from jqfactor import *
import numpy as np
import pandas as pd
import pickle
from six import StringIO,BytesIO # py3的环境，使用BytesIO
import talib
# 初始化函数
def initialize(context):
# 设定基准
set_benchmark('000985.XSHG')
# 用真实价格交易
set_option('use_real_price', True)
# 打开防未来函数
set_option("avoid_future_data", True)
# 将滑点设置为0
set_slippage(FixedSlippage(0))
# 设置交易成本万分之三，不同滑点影响可在归因分析中查看
set_order_cost(OrderCost(open_tax=0, close_tax=0.001, open_commission=0.0003, close_commission=0.0003,
close_today_commission=0, min_commission=5), type='stock')
# 过滤order中低于error级别的日志
log.set_level('order', 'error')
# 初始化全局变量
g.stock_num = 10
g.hold_list = [] # 当前持仓的全部股票
g.yesterday_HL_list = [] # 记录持仓中昨日涨停的股票
g.num=1
# 设置交易运行时间
run_daily(prepare_stock_list, '9:05')
run_weekly(weekly_adjustment, 1, '9:30')
run_daily(check_limit_up, '14:00') # 检查持仓中的涨停股是否需要卖出
SW1 = {
'801010': '农林牧渔I',
'801020': '采掘I',
'801030': '化工I',
'801040': '钢铁I',
'801050': '有色金属I',
'801060': '建筑建材I',
'801070': '机械设备I',
'801080': '电子I',
'801090': '交运设备I',
'801100': '信息设备I',
'801110': '家用电器I',
'801120': '食品饮料I',
'801130': '纺织服装I',
'801140': '轻工制造I',
'801150': '医药生物I',
'801160': '公用事业I',
'801170': '交通运输I',
'801180': '房地产I',
'801190': '金融服务I',
'801200': '商业贸易I',
'801210': '休闲服务I',
'801220': '信息服务I',
'801230': '综合I',
'801710': '建筑材料I',
'801720': '建筑装饰I',
'801730': '电气设备I',
'801740': '国防军工I',
'801750': '计算机I',
'801760': '传媒I',
'801770': '通信I',
'801780': '银行I',
'801790': '非银金融I',
'801880': '汽车I',
'801890': '机械设备I',
'801950': '煤炭I',
'801960': '石油石化I',
'801970': '环保I',
'801980': '美容护理I'
}
# 1-1 准备股票池
def prepare_stock_list(context):
# 获取已持有列表
g.hold_list = []
for position in list(context.portfolio.positions.values()):
stock = position.security
g.hold_list.append(stock)
# 获取昨日涨停列表
if g.hold_list != []:
df = get_price(g.hold_list, end_date=context.previous_date, frequency='daily', fields=['close', 'high_limit'],
count=1, panel=False, fill_paused=False)
df = df[df['close'] == df['high_limit']]
g.yesterday_HL_list = list(df.code)
else:
g.yesterday_HL_list = []
industry_code = ['801010','801020','801030','801040','801050','801080','801110','801120','801130','801140','801150',\
'801160','801170','801180','801200','801210','801230','801710','801720','801730','801740','801750',\
'801760','801770','801780','801790','801880','801890']
def industry(stockList,industry_code,date):
i_Constituent_Stocks={}
for i in industry_code:
temp = get_industry_stocks(i, date)
i_Constituent_Stocks[i] = list(set(temp).intersection(set(stockList)))
count_dict = {}
for name, content_list in i_Constituent_Stocks.items():
count = len(content_list)
count_dict[name] = count
return count_dict
def getStockIndustry(p_stocks, p_industries_type, p_day):
dict_stk_2_ind = {}
stocks_industry_dict = get_industry(p_stocks, date=p_day)
for stock in stocks_industry_dict:
if p_industries_type in stocks_industry_dict[stock]:
dict_stk_2_ind[stock] = stocks_industry_dict[stock][p_industries_type]['industry_code']
return pd.Series(dict_stk_2_ind)
选股模块函数解锁后查看：
def check_limit_up(context):
now_time = context.current_dt
if g.yesterday_HL_list != []:
# 对昨日涨停股票观察到尾盘如不涨停则提前卖出，如果涨停即使不在应买入列表仍暂时持有
for stock in g.yesterday_HL_list:
current_data = get_price(stock, end_date=now_time, frequency='1m', fields=['close', 'high_limit'],
skip_paused=False, fq='pre', count=1, panel=False, fill_paused=True)
if current_data.iloc[0, 0] < current_data.iloc[0, 1]: log.info("[%s]涨停打开，卖出" % (stock)) position = context.portfolio.positions[stock] close_position(position) else: log.info("[%s]涨停，继续持有" % (stock)) # 3-1 交易模块-自定义下单 def order_target_value_(security, value): if value == 0: log.debug("Selling out %s" % (security)) else: log.debug("Order %s to value %f" % (security, value)) return order_target_value(security, value) # 3-2 交易模块-开仓 def open_position(security, value): order = order_target_value_(security, value) if order != None and order.filled > 0:
return True
return False
# 3-3 交易模块-平仓
def close_position(position):
security = position.security
order = order_target_value_(security, 0) # 可能会因停牌失败
if order != None:
if order.status == OrderStatus.held and order.filled == order.amount:
return True
return False
# 2-1 过滤停牌股票
def filter_paused_stock(stock_list):
current_data = get_current_data()
return [stock for stock in stock_list if not current_data[stock].paused]
# 2-2 过滤ST及其他具有退市标签的股票
def filter_st_stock(stock_list):
current_data = get_current_data()
return [stock for stock in stock_list
if not current_data[stock].is_st
and 'ST' not in current_data[stock].name
and '*' not in current_data[stock].name
and '退' not in current_data[stock].name]
# 2-3 过滤科创北交股票
def filter_kcbj_stock(stock_list):
for stock in stock_list[:]:
if stock[0] == '4' or stock[0] == '8' or stock[:2] == '68' or stock[0] == '3':
stock_list.remove(stock)
return stock_list
# 2-4 过滤涨停的股票
def filter_limitup_stock(context, stock_list):
last_prices = history(1, unit='1m', field='close', security_list=stock_list)
current_data = get_current_data()
return [stock for stock in stock_list if stock in context.portfolio.positions.keys()
or last_prices[stock][-1] < current_data[stock].high_limit] # 2-5 过滤跌停的股票 def filter_limitdown_stock(context, stock_list): last_prices = history(1, unit='1m', field='close', security_list=stock_list) current_data = get_current_data() return [stock for stock in stock_list if stock in context.portfolio.positions.keys() or last_prices[stock][-1] > current_data[stock].low_limit]
# 2-6 过滤次新股
def filter_new_stock(context, stock_list):
yesterday = context.previous_date
return [stock for stock in stock_list if
not yesterday - get_security_info(stock).start_date < datetime.timedelta(days=375)]
最后更新： 2025-09-3 06:17
