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02-分钟级量价信号
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from jqdata import *
import numpy as np
import pandas as pd
import warnings
warnings.filterwarnings('ignore') # 忽略警告提示
def initialize(context):
set_option('use_real_price', True) # 真实价格交易
set_order_cost(OrderCost(close_tax=0.001, open_commission=0.0003, close_commission=0.0003, min_commission=5), type='stock')
log.set_level('system','error') # 取消日志
g.stocks = ['600111.XSHG','000553.XSHE','601066.XSHG','601162.XSHG',
'002939.XSHE','601828.XSHG','000876.XSHE','600703.XSHG'] # 聚宽4、5级沪深300股票池
set_universe(g.stocks)
g.num = len(g.stocks)
set_benchmark({'002939.XSHE':1/g.num/2,'000553.XSHE':1/g.num/2,'600111.XSHG':1/g.num/2,'600703.XSHG':1/g.num/2,
'601066.XSHG':1/g.num/2,'601162.XSHG':1/g.num/2,'000876.XSHE':1/g.num/2,'601828.XSHG':1/g.num/2})
data = {'win':np.zeros(g.num),'equal':np.zeros(g.num),'lose':np.zeros(g.num),'times':np.zeros(g.num)}
g.df = pd.DataFrame(data,index = g.stocks)
g.days,g.minutes = 0,0 # 建仓日，分钟计时
g.win,g.equal,g.lose = 0,0,0 # 交易胜负次数
g.times,g.times_cul,g.cost,g.amount = np.zeros(g.num),np.zeros(g.num),np.zeros(g.num),np.zeros(g.num)
# 每日交易次数，累计交易次数，交易成本，每次交易股票数
g.status = np.zeros(g.num)
# 股票交易状态：未交易(0)，可交易(1)，持有待平仓(2)，需马上平仓(3）
run_daily(trade, time='every_bar')
run_daily(cover, time='14:50')
run_daily(after_trade, time='15:30')
def trade(context):
if g.days > 0 and g.minutes < 230:
g.minutes += 1
# current_d = context.current_dt.strftime('%Y-%m-%d %H:%M:%S')
# 计算买入信号
count = max(g.minutes,56)
close = history(count, '1m', 'close')
volume = history(count, '1m', 'volume')
high = history(count, '1m', 'high')
low = history(count, '1m', 'low')
buy_signal(close,volume,high)
sell_signal(close,volume)
# 买卖股票，并更改其交易状态
for i in range(g.num):
stock = g.stocks[i]
if g.status[i] == 1 and g.times[i] <= 1: # 每日最多交易两次
orders = order(stock,g.amount[i])
if orders is None:
print(str(stock)+' 下单未成功')
else:
g.times[i] += 1
g.df.loc[stock].times += 1
g.cost[i] = orders.price
print('买入股票:'+str(stock)+'，交易成本价为：'+str(orders.price)+'，买入数量为：'+str(orders.amount))
g.status[i] = 2 # 需要平仓的股票状态
elif g.status[i] == 2:
# 止损止盈
current_data = get_current_data()
new_price = current_data[stock].last_price # 获取当前市价
if g.cost[i]*1.02 < new_price or g.cost[i]*0.98 > new_price:
orders = order(stock,-1 * g.amount[i])
if orders is None:
print(str(stock)+' 未平仓成功')
else:
g.status[i] = 0
if orders.price > g.cost[i]:
g.win += 1
g.df.loc[stock].win += 1
print('平仓股票（赚）:'+str(stock)+'，平仓价为：'+str(orders.price)+'，成本价为：'+str(g.cost[i]))
else:
g.lose += 1
g.df.loc[stock].lose += 1
print('平仓股票（亏）:'+str(stock)+'，平仓价为：'+str(orders.price)+'，成本价为：'+str(g.cost[i]))
elif g.status[i] == 3:
# 离场信号
orders = order(stock,-1 * g.amount[i])
if orders is None:
print(str(stock)+' 未平仓成功')
else:
g.status[i] = 0
if orders.price*1.0015 > g.cost[i]:
g.win += 1
g.df.loc[stock].win += 1
print('平仓股票（赚）:'+str(stock)+'，平仓价为：'+str(orders.price)+'，成本价为：'+str(g.cost[i]))
elif orders.price*1.0015 == g.cost[i]:
g.equal += 1
g.df.loc[stock].equal += 1
print('平仓股票（平）:'+str(stock)+'，平仓价为：'+str(orders.price)+'，成本价为：'+str(g.cost[i]))
else:
g.lose += 1
g.df.loc[stock].lose += 1
print('平仓股票（输）:'+str(stock)+'，平仓价为：'+str(orders.price)+'，成本价为：'+str(g.cost[i]))
def cover(context):
# 首日建仓
if g.days == 0:
W = np.ones(g.num)/g.num/2 # get_weight(g.stocks)
cash_list = context.portfolio.cash * W # 可以考虑留部分闲置资金
for i in range(g.num):
stock = g.stocks[i]
orders = order_value(stock,cash_list[i])
if orders is None:
print(str(stock)+' 下单未成功')
else:
g.amount[i] = int(orders.amount/200)*100 # 向下取整
print(str(stock)+' 下单手数 '+str(orders.amount))
elif g.days > 0:
for i in range(g.num):
stock = g.stocks[i]
if g.status[i] == 2:
orders = order(stock,-1*g.amount[i])
if orders is None:
print(str(stock)+' 未平仓成功')
else:
g.status[i] = 0
if orders.price*1.0015 == g.cost[i]:
g.equal += 1
g.df.loc[stock].equal += 1
print('平仓股票（平）:'+str(stock)+'，平仓价为：'+str(orders.price)+'，成本价为：'+str(g.cost[i]))
elif orders.price*1.0015 < g.cost[i]:
g.lose += 1
g.df.loc[stock].lose += 1
print('平仓股票（输）:'+str(stock)+'，平仓价为：'+str(orders.price)+'，成本价为：'+str(g.cost[i]))
elif orders.price*1.0015 > g.cost[i]:
g.win += 1
g.df.loc[stock].win += 1
print('平仓股票（输）:'+str(stock)+'，平仓价为：'+str(orders.price)+'，成本价为：'+str(g.cost[i]))
g.times_cul[i] += g.times[i]
def after_trade(context):
print('累计胜负情况：赢'+str(g.win)+'，平'+str(g.equal)+'，输'+str(g.lose))
# 每日参数清零
g.minutes = 0
g.times = np.zeros(g.num)
print(g.df)
print('='*75)
g.days += 1
# 入场信号
def buy_signal(close,volume,high):
for i in range(g.num):
if g.status[i] == 0:
stock = g.stocks[i]
p1 = close[stock].iloc[-1:].values[0]
v1 = volume[stock].iloc[-1:].values[0]
p20_max = high[stock].iloc[-21:-1].max()
p20_mean = close[stock].iloc[-21:-1].mean()
p10_mean = close[stock].iloc[-11:-1].mean()
p55_mean = close[stock].iloc[-56:-1].mean()
v10 = volume[stock].iloc[-6:-1].mean()
v10_max = volume[stock].iloc[-6:-1].max()
bool_1 = p1 > p20_max and p10_mean > p20_mean > p55_mean
bool_2 = v1 > v10 * 2 and v1 < v10 * 4 and v1 > v10_max
if len(close) > 30:
highest = high[stock].max() # 低于当日前N分钟最高价
if p1 <= highest and bool_1 and bool_2:
g.status[i] += 1
elif bool_1 and bool_2:
g.status[i] += 1
# 平仓信号
def sell_signal(close,volume):
for i in range(g.num):
if g.status[i] == 2:
stock = g.stocks[i]
p1 = close[stock].iloc[-1:].values[0]
v1 = volume[stock].iloc[-1:].values[0]
v20_max = close[stock].iloc[-21:-1].max()
p20_mean = close[stock].iloc[-21:-1].mean()
p10_mean = close[stock].iloc[-11:-1].mean()
bool1 = p10_mean < p20_mean
# bool2 = v1 > v20_max and p1 < p10_mean
if bool1:# or bool2:
g.status[i] = 3
# 按市值分配股票池资金权重
def get_weight(stocks):
cap = get_fundamentals(query(valuation).filter(valuation.code.in_(stocks)))['market_cap']
weight = []
for i in range(len(stocks)):
weight.append(cap[i]/cap.sum())
return np.array(weight)