MACD均线择时策略是十分基础的策略，适合咱们这种新手学习，这篇博客就分享一下基于聚宽实现MACD均线择时策略。
代码：
注：需要到聚宽的量化平台去运行。
# MACD均线择时策略
'''
筛选出符合：
10<市盈率（pe_ratio）<40, 市净率（pb_ratio)<3, 净利润环比增长率(inc_net_profit_annual)>0.3，净资产收益率(roe)>15的股票，按照销售毛利率进行降序排列，选取前50只
买入：DIF从下而上穿过DEA，即形成金叉
卖出：DIF从上往下穿过DEA，即形成死叉
十天一次调仓
'''
import pandas as pd
import numpy as np
import talib ## 使用talib计算MACD的参数
def initialize(context):
g.days=0#计算持有天数
g.refresh_rate=10#调仓的频率
set_benchmark('000300.XSHG')#设置参考指数
set_option('use_real_price', True)
log.set_level('order', 'error')#过滤日志错误
run_daily(trade, 'every_bar')
def before_trading_start(context):
set_slip_fee(context)
#设置下滑，交易费率
def set_slip_fee(context):
set_slippage(FixedSlippage(0.02))
dt=context.current_dt
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')
# if dt>datetime.datetime(2013,1, 1):
# 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')
# else:
# set_order_cost(OrderCost(open_tax=0, open_commission=0.003,close_commission=0.003, close_tax=0.001,min_commission=5), type='stock')
#过滤停牌股票
def paused_filter(security_list):
current_data=get_current_data()
security_list = [stock for stock in security_list if not current_data[stock].paused]
return security_list
#过滤退市股票
def delisted_filter(security_list):
current_data = get_current_data()
security_list = [stock for stock in security_list if not '退' in current_data[stock].name]
return security_list
#过滤ST
def st_filter(security_list):
current_data = get_current_data()
security_list = [stock for stock in security_list if not current_data[stock].is_st]
return security_list
#对持仓股票每日进行检查，死叉卖出
def zy_zs(context):
dqhold = list(context.portfolio.positions.keys())
for stock in dqhold:
prices=attribute_history(stock,300,'1d',['close'])
price=array(prices['close'])
MACD_tmp=talib.MACD(price,fastperiod=12,slowperiod=26,signalperiod=20)
DIF=MACD_tmp[0]
DEA=MACD_tmp[1]
MACD=MACD_tmp[2]
if MACD[-1]<0 and MACD[-4]>0:
order_target_value(stock, 0)
def trade(context):
zy_zs(context)#卖出死叉个股
#如果手中不持有股票，则立即进行选股
if len(context.portfolio.positions.keys())==0:
g.days=0
#10<市盈率(pe_ratio)<40，每股盈余(eps)>0.3，净资产收益率(roe)>15，净利润环比增长率>0.3，并按照市净率进行升序排列，取前五十只。
if g.days%g.refresh_rate==0:
stock_to_choose=get_fundamentals(query(
valuation.code,valuation.pe_ratio,valuation.market_cap,
indicator.eps,indicator.inc_net_profit_annual
).filter(
valuation.pe_ratio<40,
valuation.pe_ratio>10,
indicator.eps>0.3,
indicator.inc_net_profit_annual>0.3,
indicator.roe>15
).order_by(valuation.pb_ratio.asc()
).limit(
50),date=None)
#过滤停牌、退市、ST个股
stockpool = list(stock_to_choose['code'])
stockpool = paused_filter(stockpool)
stockpool = delisted_filter(stockpool)
stockpool = st_filter(stockpool)
jx_list=[]#MACD金叉列表
sx_list=[]#MACD死叉列表
hold=[]#持有列表
for stock in stockpool:
prices=attribute_history(stock,300,'1d',['close'])
price=array(prices['close'])
MACD_tmp=talib.MACD(price,fastperiod=12,slowperiod=26,signalperiod=20)
DIF=MACD_tmp[0]
DEA=MACD_tmp[1]
MACD=MACD_tmp[2]
if MACD[-1]>0 and MACD[-4]<0:
jx_list.append(stock)
elif MACD[-1]<0 and MACD[-4]>0:
sx_list.append(stock)
#卖出手中死叉个股
stockset = list(context.portfolio.positions.keys())
for stock in stockset:
if stock in jx_list:
hold.append(stock)#如果金叉则持有
else:
order_target_value(stock, 0) #卖出非金叉个股
#构建买入列表
buy_list = []
for stock in jx_list:
if stock not in hold:
buy_list.append(stock)#新增的买入股票
#分配资金，购买股票
if len(buy_list)==0:
Cash=context.portfolio.available_cash
else:
Cash = context.portfolio.available_cash/len(buy_list)
for stock in buy_list:
order_target_value(stock, Cash)
g.days = 1
else:
g.days += 1回测结果：
