```
# 修改后代码已贴出，策略回测起来比较慢。@孤舟
code
# 克隆自聚宽文章：https://www.joinquant.com/post/36786
# 标题：14个月200%，超短线实盘交易策略！无未来函数
# 作者：随波逐浪9
'''原策略有未来函数，已修改'''
# 导入函数库
import datetime
from jqdata import *
from jqlib.technical_analysis import *
import numpy as np
# 初始化函数，设定基准等等
def initialize(context):
enable_profile()
# log.set_level('order', 'error')
# 设定沪深300作为基准
set_benchmark('000300.XSHG')
# 开启动态复权模式(真实价格)
set_option('use_real_price', True)
# 关闭未来函数
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
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='fund')
# 股票购买限制
g.buy_stock_limit = 1
run_daily(trade, time='9:30')
## 开盘前运行函数
def before_trading_start(context):
# 初始化参数
initHandleParam() # buy_list股票清单初始化
prev_trade_day = context.previous_date
# 获取过滤股票
stock_pool = get_all_securities(['stock'], date=prev_trade_day)
stock_list = filter_stock(stock_pool)
# 取昨天，前天的MA5,MA10,MA20,MA30数据
p1_ma5 = get_stock_price(stock_list,prev_trade_day,5).groupby('code').mean()
p1_ma10 = get_stock_price(stock_list,prev_trade_day,10).groupby('code').mean()
p1_ma20 = get_stock_price(stock_list,prev_trade_day,20).groupby('code').mean()
p1_ma30 = get_stock_price(stock_list,prev_trade_day,30).groupby('code').mean()
p2_ma5 = get_stock_price(stock_list,getday3(prev_trade_day,-1),5).groupby('code').mean()
p2_ma10 = get_stock_price(stock_list,getday3(prev_trade_day,-1),10).groupby('code').mean()
p2_ma20 = get_stock_price(stock_list,getday3(prev_trade_day,-1),20).groupby('code').mean()
p2_ma30 = get_stock_price(stock_list,getday3(prev_trade_day,-1),30).groupby('code').mean()
'''
昨日MA5下穿MA10
昨日成交量MA5的1.2倍大于昨日成交量MA10（昨日不能缩量太多）
MA20、MA30要保持上升趋势
'''
dx1 = []
for stock in stock_list:
p1_ma5_close = p1_ma5['close'][stock]
p1_ma10_close = p1_ma10['close'][stock]
p1_ma20_close = p1_ma20['close'][stock]
p1_ma30_close = p1_ma30['close'][stock]
p2_ma5_close = p2_ma5['close'][stock]
p2_ma10_close = p2_ma10['close'][stock]
p2_ma20_close = p2_ma20['close'][stock]
p2_ma30_close = p2_ma30['close'][stock]
p1_ma5_volume = p1_ma5['volume'][stock]
p1_ma10_volume = p1_ma10['volume'][stock]
p2_ma5_volume = p2_ma5['volume'][stock]
p2_ma10_volume = p2_ma10['volume'][stock]
# MA5下穿MA10
# MA5,MA10交易量纠错
# MA20,MA30上升
if p1_ma5_close < p1_ma10_close \
and p2_ma5_close > p2_ma10_close \
and p2_ma5_volume > p2_ma10_volume \
and (p1_ma5_volume * 1.2) > p1_ma10_volume \
and p1_ma20_close > p2_ma20_close \
and p1_ma30_close > p2_ma30_close \
:
dx1.append(stock)
print('dx1可选股票%s支.' %(len(dx1)))
'''
DIF快线在0轴上，DEA慢线在0轴上
MACD在0~0.2之前（不能跌的太凶）
'''
dx2 = []
macd_dif, macd_dea, macd_macd = MACD(security_list = dx1, check_date = prev_trade_day, SHORT = 12, LONG = 26, MID = 9, unit = '1d')
macd_dif2, macd_dea2, macd_macd2 = MACD(security_list = dx1, check_date = getday(prev_trade_day,-1), SHORT = 12, LONG = 26, MID = 9, unit = '1d')
for stock in dx1:
# MACD 0到0.2之间
if macd_dif[stock] > 0 and macd_dea[stock] > 0 \
and 0.2 > macd_macd[stock] > 0 \
:
dx2.append(stock)
print('dx2可选股票%s支' %(len(dx2)))
dx3 = []
current_data = get_current_data()
for stock in dx2:
p1_flow = get_money_flow(security_list=stock, end_date=prev_trade_day, count=1, fields=['change_pct'])
p2_flow = get_money_flow(security_list=stock, end_date=getday3(prev_trade_day,-1), count=1, fields=['change_pct'])
if len(p1_flow['change_pct']) == 0 or len(p2_flow['change_pct']) == 0:
continue
# 死叉前后两天收盘价必须一跌一涨
if (p1_flow['change_pct'][0] > 0 and p2_flow['change_pct'][0] < 0) \
or (p1_flow['change_pct'][0] < 0 and p2_flow['change_pct'][0] > 0) \
:
dx3.append(stock)
print('dx3可选股票%s支' %(len(dx3)))
g.dx4 = dx3
## 开盘时运行函数
def trade(context):
current_data = get_current_data()
prev_trade_day = context.previous_date
'''
昨日收盘价 > 今日开盘价，低开
'''
dx5 = []
for stock in g.dx4:
p1_1 = get_price(security=stock, end_date=prev_trade_day, frequency='1d', fields=['close'],
panel=False, count=1, skip_paused=True)
if p1_1['close'][0] < = current_data[stock].day_open:
continue
dx5.append(stock)
print('dx5可选股票%s支' %(len(dx5)))
g.buy_list = dx5
g.buy_list.sort()
print('%s:共找到%d只股票可以购买.%s'%(context.current_dt,len(g.buy_list),g.buy_list))
# 卖出
for stock in context.portfolio.positions.keys():
price = current_data[stock].last_price
if context.portfolio.positions[stock].closeable_amount == 0 \
or current_data[stock].low_limit == price \
or current_data[stock].high_limit == price \
:
continue
print('%s卖出(自动):自动卖出:成本价:%s,当前价:%s'%(stock,context.portfolio.positions[stock].avg_cost,price))
sell_stock(stock,0)
# 判断是否买满
if g.buy_stock_limit < = len(context.portfolio.positions.keys()):
return
# 买入
for stock in g.buy_list:
price = current_data[stock].last_price
if context.portfolio.available_cash < (price * 100) \
or current_data[stock].low_limit == price \
or current_data[stock].high_limit == price \
or stock in context.portfolio.positions.keys() \
:
continue
print('%s买入(自动):自动买入:当前价:%s'%(stock,price))
buy_stock(context,stock)
break
####################################公共函数######################################
def initHandleParam():
g.buy_list = []
def get_stock_price(stock_list,ed,days):
stock_price = get_price(security=stock_list, end_date=ed, frequency='1d', fields=['close','volume'],
panel=False, count=days, skip_paused=True)
return stock_price
def getday(ed,count):
dates = get_trade_days(end_date=ed, count=(-count+1))
return dates[0]
def getday2(date,n):
yesterday = datetime.datetime.strptime(date,'%Y-%m-%d') + datetime.timedelta(n)
return yesterday
def getday3(d,step):
day = d + datetime.timedelta(step)
return day
# 购买股票
def buy_stock(context,stock):
# 计算今天还需要买入的股票数量
need_count = g.buy_stock_limit - len(context.portfolio.positions.keys())
if need_count == 0:
return
# 把现金分成几份,
buy_cash = context.portfolio.available_cash / need_count
# 买入这么多现金的股票
order_value(stock, buy_cash)
# 记录这次买入
# log.info("购买： %s" % (stock))
#出售股票
def sell_stock(stock,value):
# 全部卖出
order_target(stock, value)
# 记录这次卖出
# log.info("卖出： %s" % (stock))
def filter_stock(stock_pool):
return list(stock for stock in stock_pool.index
if not stock.startswith('30') and not stock.startswith('688')
and not 'ST' in stock_pool['display_name']
and not '*' in stock_pool['display_name']
and not '退' in stock_pool['display_name']
)
```
2023-03-19
雪球
