@freemars
```
#导入函数库
from jqdata import *
from jqfactor import get_factor_values
import numpy as np
import pandas as pd
#初始化函数
def initialize(context):
set_benchmark('000905.XSHG')
# 用真实价格交易
set_option('use_real_price', True)
# 打开防未来函数
set_option("avoid_future_data", True)
# 将滑点设置为0
set_slippage(FixedSlippage(0))
# 设置交易成本万分之三
set_order_cost(OrderCost(open_tax=0, close_tax=0.001, open_commission=0.0003, close_commission=0.0003, close_today_commission=0, min_commission=5),type='fund')
# 过滤order中低于error级别的日志
log.set_level('order', 'error')
#选股参数
g.stock_num = 5 #持仓数
# 设置交易时间，每天运行
run_weekly(print_stock_list_before_open, weekday=1, time='9:15', reference_security='000300.XSHG')
run_weekly(my_trade, weekday=1, time='9:30', reference_security='000300.XSHG')
run_daily(print_position_info, time='15:10', reference_security='000300.XSHG')
#1-1 选股模块
def get_factor_filter_list(context,stock_list,jqfactor,sort,p1,p2):
yesterday = context.previous_date
score_list = get_factor_values(stock_list, jqfactor, end_date=yesterday, count=1)[jqfactor].iloc[0].tolist()
df = pd.DataFrame(columns=['code','score'])
df['code'] = stock_list
df['score'] = score_list
df = df.dropna()
df.sort_values(by='score', ascending=sort, inplace=True)
filter_list = list(df.code)[int(p1*len(stock_list)):int(p2*len(stock_list))]
return filter_list
#1-2 选股模块
def get_stock_list(context):
initial_list = get_all_securities().index.tolist()
initial_list = filter_new_stock(context,initial_list)
initial_list = filter_kcb_stock(context, initial_list)
initial_list = filter_st_stock(initial_list)
x_list = get_factor_filter_list(context, initial_list, 'cube_of_size', True, 0, 0.1)
q = query(valuation.code,valuation.circulating_market_cap,indicator.eps).filter(valuation.code.in_(x_list)).order_by(valuation.circulating_market_cap.asc())
df = get_fundamentals(q)
df = df[df['eps']>0]
final_list = list(df.code)
return final_list
#1-3 开盘前打印自选股
def print_stock_list_before_open(context):
stock_list = get_stock_list(context)
stock_list = filter_paused_stock(stock_list)
stock_list = stock_list[:g.stock_num]
print('今日自选股:{}'.format(stock_list))
#2-1 过滤模块-过滤停牌股票
#输入选股列表，返回剔除停牌股票后的列表
def filter_paused_stock(stock_list):
current_data = get_current_data()
return [stock for stock in stock_list if not current_data[stock].paused]
#2-2 过滤模块-过滤ST及其他具有退市标签的股票
#输入选股列表，返回剔除ST及其他具有退市标签股票后的列表
def filter_st_stock(stock_list):
current_data = get_current_data()
return [stock for stock in stock_list
if not current_data[stock].is_st
and 'ST' not in current_data[stock].name
and '*' not in current_data[stock].name
and '退' not in current_data[stock].name]
#2-3 过滤模块-过滤涨停的股票
#输入选股列表，返回剔除未持有且已涨停股票后的列表
def filter_limitup_stock(context, stock_list):
last_prices = history(1, unit='1m', field='close', security_list=stock_list)
current_data = get_current_data()
# 已存在于持仓的股票即使涨停也不过滤，避免此股票再次可买，但因被过滤而导致选择别的股票
return [stock for stock in stock_list if stock in context.portfolio.positions.keys()
or last_prices[stock][-1] < current_data[stock].high_limit]
#2-4 过滤模块-过滤跌停的股票
#输入股票列表，返回剔除已跌停股票后的列表
def filter_limitdown_stock(context, stock_list):
last_prices = history(1, unit='1m', field='close', security_list=stock_list)
current_data = get_current_data()
return [stock for stock in stock_list if stock in context.portfolio.positions.keys()
or last_prices[stock][-1] > current_data[stock].low_limit]
#2-5 过滤模块-过滤科创板
#输入股票列表，返回剔除科创板后的列表
def filter_kcb_stock(context, stock_list):
return [stock for stock in stock_list if stock[0:3] != '688']
#2-6 过滤次新股
#输入股票列表，返回剔除上市日期不足250日股票后的列表
def filter_new_stock(context,stock_list):
yesterday = context.previous_date
return [stock for stock in stock_list if not yesterday - get_security_info(stock).start_date < datetime.timedelta(days=250)]
#3-1 交易模块-自定义下单
#报单成功返回报单(不代表一定会成交),否则返回None,应用于
def order_target_value_(security, value):
if value == 0:
log.debug("Selling out %s" % (security))
else:
log.debug("Order %s to value %f" % (security, value))
# 如果股票停牌，创建报单会失败，order_target_value 返回None
# 如果股票涨跌停，创建报单会成功，order_target_value 返回Order，但是报单会取消
# 部成部撤的报单，聚宽状态是已撤，此时成交量>0，可通过成交量判断是否有成交
return order_target_value(security, value)
#3-2 交易模块-开仓
#买入指定价值的证券,报单成功并成交(包括全部成交或部分成交,此时成交量大于0)返回True,报单失败或者报单成功但被取消(此时成交量等于0),返回False
def open_position(security, value):
order = order_target_value_(security, value)
if order != None and order.filled > 0:
return True
return False
#3-3 交易模块-平仓
#卖出指定持仓,报单成功并全部成交返回True，报单失败或者报单成功但被取消(此时成交量等于0),或者报单非全部成交,返回False
def close_position(position):
security = position.security
order = order_target_value_(security, 0) # 可能会因停牌失败
if order != None:
if order.status == OrderStatus.held and order.filled == order.amount:
return True
return False
#3-4 交易模块-调仓
#当择时信号为买入时开始调仓，输入过滤模块处理后的股票列表，执行交易模块中的开平仓操作
def adjust_position(context, buy_stocks):
for stock in context.portfolio.positions:
if stock not in buy_stocks:
log.info("[%s]不在应买入列表中" % (stock))
position = context.portfolio.positions[stock]
close_position(position)
else:
log.info("[%s]已经持有无需重复买入" % (stock))
# 根据股票数量分仓
# 此处只根据可用金额平均分配购买，不能保证每个仓位平均分配
position_count = len(context.portfolio.positions)
if g.stock_num > position_count:
value = context.portfolio.cash / (g.stock_num - position_count)
for stock in buy_stocks:
if context.portfolio.positions[stock].total_amount == 0:
if open_position(stock, value):
if len(context.portfolio.positions) == g.stock_num:
break
#3-5 交易模块-择时交易
#结合择时模块综合信号进行交易
def my_trade(context):
#获取选股列表并过滤掉:st,st*,退市,涨停,跌停,停牌
check_out_list = get_stock_list(context)
check_out_list = filter_limitup_stock(context, check_out_list)
check_out_list = filter_limitdown_stock(context, check_out_list)
check_out_list = filter_paused_stock(check_out_list)
check_out_list = check_out_list[:g.stock_num]
adjust_position(context, check_out_list)
#4-1 复盘模块-打印
#打印每日持仓信息
def print_position_info(context):
#打印当天成交记录
trades = get_trades()
for _trade in trades.values():
print('成交记录：'+str(_trade))
#打印账户信息
for position in list(context.portfolio.positions.values()):
securities=position.security
cost=position.avg_cost
price=position.price
ret=100*(price/cost-1)
value=position.value
amount=position.total_amount
print('代码:{}'.format(securities))
print('成本价:{}'.format(format(cost,'.2f')))
print('现价:{}'.format(price))
print('收益率:{}%'.format(format(ret,'.2f')))
print('持仓(股):{}'.format(amount))
print('市值:{}'.format(format(value,'.2f')))
print('———————————————————————————————————')
print('———————————————————————————————————————分割线————————————————————————————————————————')
```
2022-01-03
雪球
