我最近开发了一个策略，基本思想强者恒强，弱者恒弱的动量原理。大神勿拍:
克隆策略
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instruments = D.instruments()
start_date = '2015-01-01' # 起始日期
end_date = '2017-02-13' # 结束日期
stock_num = 30 # 股票数量
In [10]:
def initialize_0(context):
context.set_commission(PerOrder(buy_cost=0.0003, sell_cost=0.0013, min_cost=5))
context.date_index = 0
context.schedule_function(rebalance,date_rule=date_rules.month_start(days_offset=0)) # 换仓规则
def handle_data_0(context,data):
pass
# 换仓
def rebalance(context, data):
context.date_index += 1
# 目前持仓的股票列表
pos_list = [i.symbol for i in context.portfolio.positions]
# 数据获取和动量因子计算处理
current_dt = data.current_dt.strftime('%Y-%m-%d')
dic = {}
for j in instruments:
try:
df = data.history(context.symbol(j),'close',30,'1d')
momentum = df[0] / df[-1]
dic[j] = momentum
except Exception as e:
continue
# 获取换仓买入股票列表
dic = {v:k for v,k in dic.items() if not np.isnan(k)}
dic_sorted = sorted(dic.items(),key = lambda d:d[1],reverse = True)
symbol_lst = [i[0] for i in dic_sorted]
sym_top = symbol_lst[:stock_num] # 买入的股票列表
to_sell = [k for k in pos_list if k not in sym_top] # 需要卖出的股票列表
# 如果持有仓位 先把仓位平掉
for j in to_sell:
if data.can_trade(context.symbol(j)):
context.order_target(context.symbol(j), 0)
# 落单买入
weight = 1. / stock_num
for cp in sym_top:
if data.can_trade(context.symbol(cp)):
context.order_target_percent(context.symbol(cp), weight)
# 打印信息
print('date = ', data.current_dt.strftime('%Y-%m-%d'),'该交易日已经结束')
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m=M.backtest.v4( # 测试接口
instruments=instruments,
start_date=start_date,
end_date=end_date,
initialize=initialize_0,
handle_data=handle_data_0,
order_price_field='close',
order_price_field_buy='open',
order_price_field_sell='open',
capital_base=float("1.0e6"),
benchmark='000300.INDX',
)
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