def algo(context):
global candidate_stock, selected_stock
date_now = context.now.strftime('%Y-%m-%d')
date_previous = get_trading_date_from_now(date_now, -1,
ql.Days) # 前一个交易日，用于获取因子数据的日期
print(date_now + '日回测程序执行中...')
if date_now not in trading_date_list: # 非调仓日
pass # 预留非调仓日的微调空间
else: # 调仓日执行算法
# 根据指数获取股票候选池的代码
code_list = SelectedStockPoolFromListV1(
INCLUDED_INDEX, EXCLUDED_INDEX, date_previous).get_stock_pool()
strategy = STRATEGY(code_list, date_previous)
candidate_stock = strategy.select_code() # 调仓日定期调节候选的股票池更新，非调仓日使用旧股票池
sw1_industry = get_SW1_industry(date_now, candidate_stock)
industry_wm_result = industry_wheel_movement[date_now]
candidate_selected_stock = [
stock for stock in candidate_stock if sw1_industry[stock] is not None
and industry_wm_result[sw1_industry[stock]] == 1
] # 忽略无行业信息的股票并根据行业择时信号选择候选股票
if candidate_selected_stock == selected_stock: # 候选股状态与之前一样，不用任何操作
pass
else:
selected_stock = candidate_selected_stock # 更新已持股池的信息
if candidate_selected_stock == []: # 空仓信号
stock_dict[date_now] = {}
else:
candidate_selected_stock = list_wind2jq(candidate_selected_stock)
stock_now = WEIGHTS(candidate_selected_stock,
date_previous).get_weights()
stock_dict[date_now] = stock_now
def algo(context):
global position_now, position_target
date_now = context.now.strftime('%Y-%m-%d')
date_previous = get_trading_date_from_now(date_now, -1,
ql.Days) # 前一个交易日，用于获取因子数据的日期
select_time_value = select_time_model[date_now] # 择时信号计算
print(date_now + ('日回测程序执行中...，择时值：%.2f' % select_time_value))
if date_now not in trading_date_list: # 非调仓日
pass
else: # 调仓日执行算法，更新position_target
position_now = False # 虚拟上，调仓日需要提前清仓
stock_dict[date_now] = {}
# 根据指数获取股票候选池的代码
code_list = SelectedStockPoolFromListV1(
INCLUDED_INDEX, EXCLUDED_INDEX, date_previous).get_stock_pool()
strategy = STRATEGY(code_list, date_previous, 0.9)
select_code_list = list_wind2jq(strategy.select_code())
if len(select_code_list) > 0: # 有可选股票时记录下可选股票
stock_now = WEIGHTS(select_code_list, date_previous).get_weights()
position_target = stock_now
else:
position_target = {}
# LLT择时判定
if select_time_value >= 0 and not position_now and position_target != {}: # LLT择时信号为正,空仓且有目标持仓状态
stock_dict[date_now] = position_target
position_now = True
elif select_time_value < 0 and position_now and position_target != {}: # LLT择时信号为负且持仓状态:
stock_dict[date_now] = {}
position_now = False
def algo(context):
date_now = context.now.strftime('%Y-%m-%d')
date_previous = get_trading_date_from_now(date_now, -1,
ql.Days) # 前一个交易日，用于获取因子数据的日期
if date_now not in trading_date_list: # 非调仓日
pass # 预留非调仓日的微调空间
else: # 调仓日执行算法
print(date_now + '日回测程序执行中...')
try:
code_list = list_gm2wind(
list(
get_history_constituents(
INDEX,
start_date=date_previous,
end_date=date_previous)[0]['constituents'].keys()))
except IndexError:
code_list = w.wset("sectorconstituent", "date=" + date_previous +
";windcode=" + INDEX).Data[1]
strategy = STRATEGY(code_list, date_previous)
select_code_list = list_wind2jq(strategy.select_code())
if len(select_code_list) > 0: # 有可选股票时选取合适的股票
stock_now = {}
for code in select_code_list:
stock_now[code] = 1.0 / len(select_code_list)
stock_dict[date_now] = stock_now
else:
stock_dict[date_now] = {}
def algo(context):
date_now = context.now.strftime('%Y-%m-%d')
date_previous = get_trading_date_from_now(date_now, -1, ql.Days) # 前一个交易日，用于获取因子数据的日期
if date_now not in trading_date_list: # 非调仓日
pass # 预留非调仓日的微调空间
else: # 调仓日执行算法
print(date_now+'日回测程序执行中...')
# 根据指数获取股票候选池的代码
code_list = SelectedStockPoolFromListV1(INCLUDED_INDEX, EXCLUDED_INDEX, date_previous).get_stock_pool()
strategy = STRATEGY(code_list, date_previous, 0.9)
select_code_list = list_wind2jq(strategy.select_code())
if len(select_code_list) > 0: # 有可选股票时选取合适的股票
stock_now = WEIGHTS(select_code_list, date_previous).get_weights()
stock_dict[date_now] = stock_now
else:
stock_dict[date_now] = {}
def algo(context):
global position_now, position_target
date_now = context.now.strftime('%Y-%m-%d')
date_previous = get_trading_date_from_now(date_now, -1,
ql.Days) # 前一个交易日，用于获取因子数据的日期
select_time_value = select_time_model[date_now] # 择时信号计算
if date_now not in trading_date_list: # 非调仓日
pass
else: # 调仓日执行算法，更新position_target
position_now = False # 虚拟上，调仓日需要提前清仓
stock_dict[date_now] = {}
# 根据指数获取股票候选池的代码
all_code_set = set()
for index in INDEX:
code_set = set(
w.wset("sectorconstituent",
"date=" + date_previous + ";windcode=" + index).Data[1])
all_code_set = all_code_set | code_set
code_list = list(all_code_set) # 股票候选池
strategy = STRATEGY(code_list, date_previous, 0.9)
select_code_list = list_wind2jq(strategy.select_code())
if len(select_code_list) > 0: # 有可选股票时记录下可选股票
stock_now = WEIGHTS(select_code_list, date_previous).get_weights()
position_target = stock_now
else:
position_target = {}
# 择时判定
if select_time_value >= 0 and not position_now and position_target != {}: # LLT择时信号为正,空仓且有目标持仓状态
stock_dict[date_now] = position_target
position_now = True
elif select_time_value < 0 and position_now and position_target != {}: # LLT择时信号为负且持仓状态:
stock_dict[date_now] = {}
position_now = False
# 打印择时信号和仓位配置信息
print(date_now + ('日回测程序执行中...，择时值：%.2f' % select_time_value))
print(date_now + '日回测程序执行中...，选股：')
print(position_target)