一、策略思路

在股票池里选取过去60个交易日累积收益率最高的一只股票买入，同时清仓一只已买入的股票，换仓频率为60天一次。

二、策略代码

import pandas as pd

start = '2020-01-01' # 回测开始时间

end = '2020-09-14' # 回测结束时间

benchmark = 'HS300' # 策略参考标准为沪深300

universe = ['000425.XSHE', '603881.XSHG'] # 证券池，

# capital_base = 100000

freq = 'd'

refresh_rate = 60 # 策略运行频率

max_history_window = 60

accounts = {

    'fantasy_account':AccountConfig(account_type='security', capital_base = 100000) # 账户，初始模拟资金

}

def initialize(context):

    pass

def handle_data(context):  # 核心策略逻辑

    account = context.get_account('fantasy_account')

    hist = context.history(universe, 'closePrice', 60)

    momentum = {'symbol': [], 'c_ret': []}

    for stk in hist.keys():

        momentum['symbol'].append(stk)

        momentum['c_ret'].append(hist[stk]['closePrice'][-1]/hist[stk]['closePrice'][0])

    momentum = pd.DataFrame(momentum).sort(columns='c_ret', ascending=False).reset_index()

    momentum = momentum[0:1] # 获取累计收益率最高的一只股票

    buylist = momentum['symbol'].tolist()

    # print(buylist)

    for stk in account.get_positions():

        if stk not in buylist:

            account.order_to(stk, 0) # 清仓

    portfolio_value = account.portfolio_value

    for stk in buylist:

        account.order_pct_to(stk, 1.0/len(buylist)) # 买入

    print(portfolio_value)

三、策略效果

image

四、策略总结

年化收益率126.4%，效果还行，主要还是取决于股票池股票的质量，股票池不同的股票，年化收益率相差比较大。