Simple MACD
MACD 公式算法:
- 短期EMA: 短期(例如12日)的收盘价指数移动平均值(Exponential Moving Average)
- 长期EMA: 长期(例如26日)的收盘价指数移动平均值(Exponential Moving Average)
- DIF线: (Difference)短期EMA和长期EMA的离差值
- DEA线: (Difference Exponential Average)DIF线的M日指数平滑移动平均线
- MACD线: DIF线与DEA线的差
策略实现:
- DIF从下而上穿过DEA,买进;
- 相反,如DIF从上往下穿过DEA,卖出。
策略中使用talib
计算MACD
import pandas as pd
import numpy as np
import talib
start = '2012-01-01'
end = '2015-09-28'
benchmark = 'HS300'
universe = set_universe('HS300')
capital_base = 1000000
refresh_rate = 5
## 使用talib计算MACD的参数
short_win = 12 # 短期EMA平滑天数
long_win = 26 # 长期EMA平滑天数
macd_win = 20 # DEA线平滑天数
stk_num = 20 # 持仓股票数量
longest_history = 100
def initialize(account):
account.universe = universe
def handle_data(account):
all_close_prices = account.get_attribute_history('closePrice', longest_history)
long_bucket = []
short_bucket = []
for stk in account.universe:
prices = all_close_prices[stk]
if prices is None:
continue
try:
# talib计算MACD
macd_tmp = talib.MACD(prices, fastperiod=short_win, slowperiod=long_win, signalperiod=macd_win)
DIF = macd_tmp[0]
DEA = macd_tmp[1]
MACD = macd_tmp[2]
except:
continue
# 判断MACD走向
if MACD[-1] > 0 and MACD[-4] < 0:
long_bucket.append(stk)
elif MACD[-1] < 0 and MACD[-4] > 0:
short_bucket.append(stk)
hold = []
# 处理持仓中的股票
for stk in account.valid_secpos:
# 在short_bucket中的,卖出
if stk in short_bucket:
order_to(stk, 0)
# 不在short_bucket中的,留着
else:
hold.append(stk)
buy_list = hold
for stk in long_bucket:
if stk not in hold:
buy_list.append(stk)
if len(buy_list) > 0:
# 无论buy_list中有多少只股票,都将仓位分成stk_num份,每份买入一只股票
amount_per_stk = account.referencePortfolioValue/stk_num
for stk in buy_list:
amount = int(amount_per_stk/account.referencePrice[stk] / 100.0) * 100
order_to(stk, amount)