@Kaka.Luo 就这么多 就76行
# 克隆自聚宽文章：https://www.joinquant.com/post/51024
# 标题：社区策略汇总分类
# 作者：策略评价官
# 克隆自聚宽文章：https://www.joinquant.com/post/48975
# 标题：推荐一个根据ETF溢价的交易策略
# 作者：ljf1888
# 导入函数库
from jqdata import *
# 初始化函数，设定基准等等
def initialize(context):
# 设定沪深300作为基准
set_benchmark('000300.XSHG')
# 开启异步报单
set_option('async_order', True)
# 打开防未来函数
set_option("avoid_future_data", True)
# 将滑点设置为0
set_slippage(FixedSlippage(0.002))
# 开启动态复权模式(真实价格)
set_option('use_real_price', True)
set_order_cost(OrderCost(close_tax=0.000, open_commission=0.00025, close_commission=0.00025, min_commission=5), type='fund')
#run_daily(before_market_open, '09:20', reference_security='000300.XSHG')
run_daily(before_market_open, '09:02', reference_security='000300.XSHG')
#run_daily(weekly_adjustment0,'9:06')
run_daily(market_open, '09:30', reference_security='000300.XSHG')
run_daily(after_market_close, '15:00', reference_security='000300.XSHG')
def before_market_open(context):
# 获取基金
fund_list = get_all_securities(['etf'], context.previous_date).index.tolist()
# 成交额过滤
df = history(count=1, unit='1d', field="volume", security_list=fund_list).T
df.columns=['volume']
df = df[df.volume > 2e6]
# 获取净值
df = get_extras('unit_net_value',df.index.tolist(),end_date=context.previous_date, df=True, count=1).T
df.columns=['unit_net_value']
g.fund_list = df
def market_open(context):
df = g.fund_list
current = get_current_data()
## 获得基金最新价
df['last_price'] = [current[c].last_price for c in df.index.tolist()]
## 计算溢价
df['premium'] = (df.last_price / df.unit_net_value - 1) * 100
## 根据溢价大小排序
df = df.sort_values(['premium'], ascending = True)
df = df[(df.premium < 0)]
order_fund = df[:5].index.tolist()
g.max_position = len(order_fund)
log.info(order_fund)
# 卖出
for fund in context.portfolio.positions.keys():
# 卖出不在股票池或节假日前清仓
if fund not in order_fund:
#if fund not in order_fund :
order_target_value(fund, 0)
for fund in order_fund:
now_position = g.max_position - len(context.portfolio.positions)
if now_position == 0:
continue
if fund not in context.portfolio.positions.keys():
position = context.portfolio.available_cash / now_position
order_target_value(fund, position)
## 收盘后运行函数
def after_market_close(context):
pass
2025-07-22
雪球
