双均线策略加上MACD指标过滤（附:量化策略源码）

# -*- coding: utf-8 -*-# 简便起见，可以直接用 from gm.api import *from gm.api import runfrom gm.api import ADJUST_PREVfrom gm.api import MODE_BACKTESTfrom gm.api import subscribefrom gm.api import history_nfrom gm.api import order_percentfrom gm.api import order_volumefrom gm.api import (OrderSide_Buy, OrderSide_Sell)from gm.api import (PositionEffect_Open, PositionEffect_Close)from gm.api import OrderType_Marketfrom datetime import datetimefrom datetime import timedeltaimport talibimport numpy as npfrom collections import deque#本策略基于掘金量化交易平台网址：www.myquant.cn# 常用参量设置DATE_STR = "%Y-%m-%d"TIME_STR = "%Y-%m-%d %H:%M:%S"HIST_WINDOW = 40SHORT_PERIOD = 5LONG_PERIOD = 20def init(context): # 全局变量设置 context.dict_stock_price = dict() # 以 50 EFT作为交易标的 context.stock_pool = ['SHSE.600000'] # 订阅日线行情 subscribe(symbols=context.stock_pool, frequency='1d', wait_group=True) # 日期设定，避免出现未来函数，将起始日往前取一日 start_date = datetime.strptime(context.backtest_start_time, TIME_STR) context.start_date = datetime.strftime(start_date - timedelta(days=1), TIME_STR) # 获取起始日之前行情，便于计算指标 deque_close = deque(maxlen=HIST_WINDOW) for stock in context.stock_pool: history_info = history_n(symbol=stock, frequency='1d', count=HIST_WINDOW, adjust=ADJUST_PREV, adjust_end_time=context.backtest_end_time, end_time=context.start_date, fields='close') for bar in history_info: deque_close.append(bar['close']) context.dict_stock_price.setdefault(stock, deque_close) print('finish initialization') def on_bar(context, bars): for bar in bars: if bar.symbol not in context.dict_stock_price.keys(): print('Warning: cannot obtain price of stock {} at date {}'.format( bar.symbol, context.now)) # 数据填充 context.dict_stock_price[bar.symbol].append(bar.close) # 计算指标，这里以双均线为例 closes = np.array(context.dict_stock_price[bar.symbol]) short_ma = talib.SMA(closes, SHORT_PERIOD) long_ma = talib.SMA(closes, LONG_PERIOD) macd, macd_signal, macd_hist = talib.MACD(closes, fastperiod=12, slowperiod=26, signalperiod=9) # 金叉，满仓买入 if short_ma[-2] <= long_ma[-2] and short_ma[-1] > long_ma[-1]: order_percent(symbol=bar.symbol, percent=1.0, side=OrderSide_Buy, order_type=OrderType_Market, position_effect=PositionEffect_Open, price=0) print(context.now) # 死叉或者 MACD 绿柱，全部卖出 pos = context.account().position(symbol=bar.symbol, side=OrderSide_Buy) if (short_ma[-2] >= long_ma[-2] and short_ma[-1] < long_ma[-1]) or macd_hist[-1] < 0: if pos is None: continue order_volume(symbol=bar.symbol, volume=pos.volume, side=OrderSide_Sell, order_type=OrderType_Market, position_effect=PositionEffect_Close, price=0)if __name__ == "__main__": run(strategy_id='569b4ffc-6d44-11e8-bd88-80ce62334e41', filename='demo_05.py', mode=MODE_BACKTEST, backtest_adjust=ADJUST_PREV, token='64c33fc82f334e11e1138eefea8ffc241db4a2a0', backtest_start_time='2017-01-17 09:00:00', backtest_end_time='2018-06-21 15:00:00')

来源：掘金量化 myquant.cn