‘TradingAlgorithm’ object has no attribute ‘stock_list’ 错误什么原因
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问题
‘TradingAlgorithm’ object has no attribute ‘stock_list’ 错误什么原因
解答
回测引擎：每日数据处理函数，每天执行一次
def m19_handle_data_bigquant_run(context, data):
bought_stock = []
positions = context.portfolio.positions
for equity in positions:
position = positions[equity]
bought_stock = bought_stock.append(position)
for bought in bought_stock:
import datetime
import time
tt = time.strftime("%y-%m-%d") #获取今日日期
to_day = datetime.datetime.strptime(tt, "%y-%m-%d") #将获取的今日日期调整格式
start_date = datetime.datetime.now()+datetime.timedelta(days=-200) #从今日往前计算120个交易日期作为start_date
stock_data = DataSource('bar1d_CN_STOCK_A').read(bought,start_date=start_date,end_date=to_day,fields=["date","close","high","low","adjust_factor"])
stock_data['high'] = stock_data['high']/stock_data['adjust_factor']
stock_data['low'] = stock_data['low']/stock_data['adjust_factor']
stock_data['close'] = stock_data['close']/stock_data['adjust_factor']
for i in range(0,len(stock_data)-100):
stock_data = stock_data.drop(index=i)
stock_data = stock_data.reset_index(drop=True)
stock_data['date']=stock_data['date'].astype('str')
stock_data['date']=pd.to_datetime(stock_data['date'])
stock_data.set_index('date', inplace=True)
stock_data["H"] = 0
stock_data["L"] = 0
stock_data["RSV"] = 0
stock_data["K"] = 50
stock_data["D"] = 50
stock_data["J"] = 0
stock_data = stock_data.dropna()
stock_data.reset_index(inplace=True)
for i in range(0,len(stock_data)-1,1):
data_h = stock_data.loc[i:i+8,stock_data.columns=="high"]
data_h_h = data_h.loc[:,"high"].max()
data_l = stock_data.loc[i:i+8,stock_data.columns=="low"]
data_l_l = data_l.loc[:,"low"].min()
stock_data.loc[i+8,stock_data.columns=="H"] = data_h_h
stock_data.loc[i+8,stock_data.columns=="L"] = data_l_l
if pd.isnull(stock_data.loc[i+8,stock_data.columns=="close"].values[-1]):
break
c = stock_data.loc[i+8,stock_data.columns=="close"].values[-1]
h = stock_data.loc[i+8,stock_data.columns=="H"].values[-1]
l = stock_data.loc[i+8,stock_data.columns=="L"].values[-1]
rsv = ((c - l)/(h - l)) * 100
stock_data.loc[i+8,stock_data.columns=="RSV"] = rsv
k_1 = stock_data.loc[i+7,stock_data.columns=="K"].values[-1]
stock_data.loc[i+8,stock_data.columns=="K"] = (2/3) * k_1 + (1/3) * rsv
d_1 = stock_data.loc[i+7,stock_data.columns=="D"].values[-1]
k = stock_data.loc[i+8,stock_data.columns=="K"].values[-1]
stock_data.loc[i+8,stock_data.columns=="D"] = (2/3) * d_1 + (1/3) * k
d = stock_data.loc[i+8,stock_data.columns=="D"].values[-1]
stock_data.loc[i+8,stock_data.columns=="J"] = 3*k - 2*d
j_1 = stock_data.loc[i+7,stock_data.columns=="J"].values[-1]
j = stock_data.loc[i+8,stock_data.columns=="J"].values[-1]
stock_data = stock_data.round(2)
stock_data = stock_data.drop(index=100)
current_quantity = context.portfolio.positions[context.symbol(bought)].amount
if j_1 > j:
context.order(context.symbol(bought), current_quantity* (-1))
stocks = ["000060.SZA","600030.SHA","000758.SZA"]
stock_list = []
for stock in stocks:
import datetime
import time
tt = time.strftime("%y-%m-%d") #获取今日日期
to_day = datetime.datetime.strptime(tt, "%y-%m-%d") #将获取的今日日期调整格式
start_date = datetime.datetime.now()+datetime.timedelta(days=-150) #从今日往前计算120个交易日期作为start_date
stock_data = DataSource('bar1d_CN_STOCK_A').read(stock,start_date=start_date,end_date=to_day,fields=["date","close","high","low","adjust_factor"])
stock_data['high'] = stock_data['high']/stock_data['adjust_factor']
stock_data['low'] = stock_data['low']/stock_data['adjust_factor']
stock_data['close'] = stock_data['close']/stock_data['adjust_factor']
for i in range(0,len(stock_data)-80):
stock_data = stock_data.drop(index=i)
stock_data = stock_data.reset_index(drop=True)
stock_data['date']=stock_data['date'].astype('str')
stock_data['date']=pd.to_datetime(stock_data['date'])
stock_data.set_index('date', inplace=True)
stock_data["H"] = 0
stock_data["L"] = 0
stock_data["RSV"] = 0
stock_data["K"] = 50
stock_data["D"] = 50
stock_data["J"] = 0
stock_data = stock_data.dropna()
stock_data.reset_index(inplace=True)
for i in range(0,len(stock_data)-1,1):
data_h = stock_data.loc[i:i+8,stock_data.columns=="high"]
data_h_h = data_h.loc[:,"high"].max()
data_l = stock_data.loc[i:i+8,stock_data.columns=="low"]
data_l_l = data_l.loc[:,"low"].min()
stock_data.loc[i+8,stock_data.columns=="H"] = data_h_h
stock_data.loc[i+8,stock_data.columns=="L"] = data_l_l
if pd.isnull(stock_data.loc[i+8,stock_data.columns=="close"].values[-1]):
break
c = stock_data.loc[i+8,stock_data.columns=="close"].values[-1]
h = stock_data.loc[i+8,stock_data.columns=="H"].values[-1]
l = stock_data.loc[i+8,stock_data.columns=="L"].values[-1]
rsv = ((c - l)/(h - l)) * 100
stock_data.loc[i+8,stock_data.columns=="RSV"] = rsv
k_1 = stock_data.loc[i+7,stock_data.columns=="K"].values[-1]
stock_data.loc[i+8,stock_data.columns=="K"] = (2/3) * k_1 + (1/3) * rsv
d_1 = stock_data.loc[i+7,stock_data.columns=="D"].values[-1]
k = stock_data.loc[i+8,stock_data.columns=="K"].values[-1]
stock_data.loc[i+8,stock_data.columns=="D"] = (2/3) * d_1 + (1/3) * k
d = stock_data.loc[i+8,stock_data.columns=="D"].values[-1]
stock_data.loc[i+8,stock_data.columns=="J"] = 3*k - 2*d
j_1 = stock_data.loc[i+7,stock_data.columns=="J"].values[-1]
j = stock_data.loc[i+8,stock_data.columns=="J"].values[-1]
c_2 = stock_data.loc[i+7,stock_data.columns=="close"].values[-1]
c_1 = stock_data.loc[i+8,stock_data.columns=="close"].values[-1]
stock_data = stock_data.dropna(axis=0)
stock_data = stock_data.round(2)
if c_2 <= c_1 :
if stock not in bought_stock:
stock_list = stock_list.append(stock)
if len(context.stock_list) >= 2:
weights = round(1/len(context.stock_list),2)
else:
weights = 0.25
for stock in context.stock_list:
if stock not in bought_stock:
if len(context.stock_list) < 10:
context.order_target_percent(context.symbol(stock), 0.2)
else:
context.order_target_value(context.symbol(stock), context.portfolio.cash * weights)
回测引擎：初始化函数，只执行一次
def m19_initialize_bigquant_run(context):
系统已经设置了默认的交易手续费和滑点，要修改手续费可使用如下函数
context.set_commission(PerOrder(buy_cost=0.0003, sell_cost=0.0013, min_cost=5))
m1 = M.instruments.v2(
start_date=‘2019-01-01’,
end_date=‘2021-08-01’,
market=‘CN_STOCK_A’,
instrument_list=’’,
max_count=0
)
m19 = M.trade.v4(
instruments=[“000060.SZA”,“600030.SHA”,“000758.SZA”],
start_date=‘2019-01-01’,
end_date=‘2021-08-01’,
handle_data=m19_handle_data_bigquant_run,
initialize=m19_initialize_bigquant_run,
volume_limit=0.025,
order_price_field_buy=‘open’,
order_price_field_sell=‘close’,
capital_base=1000000,
auto_cancel_non_tradable_orders=True,
data_frequency=‘daily’,
price_type=‘真实价格’,
product_type=‘股票’,
plot_charts=True,
backtest_only=False,
benchmark=‘000300.SHA’
)
stock_list是你自己定义的一个变量，不是context对象里面的，不需要加context这个前缀
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