JUKUAN/Lib/fund/Fund_premium_improvement_fast_001.py

# 克隆自聚宽文章：https://www.joinquant.com/post/33636
# 标题：etf基金溢价-改进版-高收益低回撤-速度已最优
# 作者：发锅
# 本策略网址：https://www.joinquant.com/algorithm/index/edit?algorithmId=2eb4f4246fdf81a56bf43c681de7278b&backtest=37

# 导入函数库
from jqdata import *
from jqlib.technical_analysis import *
import numpy as np
import pandas as pd
import statsmodels.api as sm 
import datetime as dt

# 初始化函数，设定基准等等
def initialize(context):
    # 设定沪深300作为基准
    set_benchmark('000300.XSHG')
    # 开启异步报单
    set_option('async_order', True)
    # 开启动态复权模式(真实价格)
    set_option('use_real_price', True)
    # 是否未来函数
    set_option("avoid_future_data", True)
    # 过滤掉order系列API产生的比error级别低的log
    # log.set_level('order', 'error')
    # 初始化全局变量
    g.loss_limit = 0.9 # 单基金止损比例
    g.drop_limit_days = 20 # 止损卖出后多少天不重新买入
    g.control_days = 0 # 初始化控制全局止损之后暂停的天数
    g.total_limit_days = 30 # 检查全局止损比例的天数范围
    g.total_limit_rate = 0.15 # 全局止损比例
    g.cool_days = 0 # 全局止损后多少天内不持仓，必须小于g.total_limit_days
    g.rate_list = []
    g.check_loss_list = []
    g.just_sell_list = []
    g.total_value_list = []
    g.hold_list = []
    g.holiday = ['2010-02-12','2010-04-30','2010-09-30','2011-02-01','2011-04-29','2011-09-30','2012-01-20','2012-04-27','2012-09-28','2013-02-08',
    '2013-04-26','2013-09-30','2014-01-30','2014-04-30','2014-09-30','2015-02-17','2015-04-30','2015-09-30','2016-02-05','2016-04-29','2016-09-30',
    '2017-01-26','2017-04-28','2017-09-29','2018-02-14','2018-04-27','2018-09-28','2019-02-01','2019-04-30','2019-09-30','2020-01-23','2020-04-30',
    '2020-09-30','2021-02-10','2021-04-30','2021-09-30','2022-01-28','2022-04-29','2022-09-30']
    set_order_cost(OrderCost(close_tax=0.000, open_commission=0.00025, close_commission=0.00025, min_commission=0), type='fund')
    run_daily(before_market_open, '09:20', reference_security='000300.XSHG')
    run_daily(market_open, '14:40', reference_security='000300.XSHG')
    run_daily(check_loss_up, time='14:45', reference_security='000300.XSHG')
    # run_daily(print_position_info, time='15:10', reference_security='000300.XSHG')

def before_market_open(context):
    # 获取基金
    fund_list = get_all_securities(['lof', 'etf'], context.previous_date).index.tolist()
    g.length1 = len(fund_list)
    # 过滤太新的基金
    fund_list = filter_new_fund(context,fund_list)
    # 嘉实元和事件，所以在2019年5月之后不再买入
    if context.current_dt.date() >= np.datetime64('2019-05-01') and ('505888.XSHG' in fund_list):
        fund_list.remove('505888.XSHG')
        print('remove 505888.XSHG')
    # 成交额过滤
    df = history(count=5, unit='1d', field="volume", security_list=fund_list).T
    df.columns=['volume1','volume2','volume3','volume4','volume5']
    df['volume'] = df[['volume1','volume2','volume3','volume4','volume5']].mean(axis=1)
    print('after volume check: ', df.iloc[:5,:5])
    df.drop(['volume1','volume2','volume3','volume4','volume5'],inplace=True,axis=1)
    cur_total_value = context.portfolio.total_value
    df = df[df.volume > 1e5] # 
    # print('after volume check: ', df.head())
    # 获取净值
    df = get_extras('unit_net_value', df.index.tolist(), end_date=context.previous_date, df=True, count=1).T
    df.columns=['unit_net_value']
    g.fund_list = df # 基金和净值的df
    log.info('开盘前记录净值...')

def market_open(context):
    df = g.fund_list
    length2 = len(df)
    current = get_current_data()
    fund_list = df.index.tolist()
    ## 获得基金最新价
    df['last_price'] = [current[c].last_price for c in fund_list]
    ## 计算溢价
    df['premium'] = (df.last_price / df.unit_net_value - 1) * 100 #最新价格小于净值的小于0
    ## 根据溢价大小排序
    if hasattr(df, 'sort'): # 如果有sort方法就用sort，没有用sort_values
        df = df.sort(['premium'], ascending = True)
    else:
        df = df.sort_values(['premium'], ascending = True)
    
    df = df[(df.premium < 0)]
    special_rate = len(df)/g.length1
    g.rate_list.append(special_rate)
    g.rate_list = g.rate_list[-10:]
    while len(g.rate_list) < 10:
        g.rate_list.append(g.rate_list[0])

    if g.cool_days == 0:
        if (len(g.rate_list) == 10) and (mean(g.rate_list) > 0.1): # 比例过低就不执行买入卖出的操作
            target_fund_list = df[:20].index.tolist()
            target_fund_list = [stock for stock in target_fund_list if stock not in g.just_sell_list]
            
            target_fund_list = target_fund_list[:5]
            g.max_position = len(target_fund_list)
        
            # 卖出
            for fund in context.portfolio.positions.keys():
                # 卖出不在股票池或节假日前清仓
                if fund not in target_fund_list or str(context.current_dt.date()) in g.holiday:
                    order_target_value(fund, 0)
        
            # 买入, 节假日前不开仓
            if str(context.current_dt.date()) not in g.holiday:
                for fund in target_fund_list:
                    now_position = g.max_position - len(context.portfolio.positions)
                    if now_position == 0:
                        continue
                    if fund not in context.portfolio.positions.keys():
                        position = context.portfolio.available_cash / now_position
                        order_target_value(fund, position)
                
        elif (len(g.rate_list) == 10) and (mean(g.rate_list) <= 0.1):
            if g.hold_list:
                clear_position(context)
    else:
        g.cool_days -= 1
        
        # 更新持有的基金池
    g.hold_list= []
    for position in list(context.portfolio.positions.values()):
        fund = position.security
        g.hold_list.append(fund)

## 收盘后运行函数
def after_market_close(context):
    pass

# 1-6 调整亏损比例过大的股票
def check_loss_up(context):
    if g.hold_list:
        check_loss_list = []
        for stock in g.hold_list:
            position = context.portfolio.positions[stock]
            price = position.price
            avg_cost = position.avg_cost
            # print('check %s, price: %2f, avg_cost: %2f' % (stock, price, avg_cost))
            if price < g.loss_limit * avg_cost:
                log.info("[%s]损失比例过高，卖出" % stock)
                close_position(position)
                check_loss_list.append(stock)
                
        if check_loss_list:        
            g.check_loss_list.append(check_loss_list)
        else:
            g.check_loss_list.append(['nothing'])
        if len(g.check_loss_list) > g.drop_limit_days:
            g.check_loss_list = g.check_loss_list[-g.drop_limit_days:]
        
        temp_set = set()
        for check_loss_list in g.check_loss_list:
            temp_set = temp_set.union(set(check_loss_list))
        # 不要购买的股票列表，过往20天因为止损而卖出的股票
        g.just_sell_list = list(temp_set)
        check_total_value(context)

# 1-7 检查整体资金比例
def check_total_value(context):
    total_money_today = context.portfolio.total_value
    g.total_value_list.append(total_money_today)
    print('检查整体资金比例g.total_value_list: ', len(g.total_value_list))
    print(g.total_value_list)
    if len(g.total_value_list) >= g.total_limit_days:
        g.total_value_list = g.total_value_list[-g.total_limit_days:] # 只考虑最近20天的跌幅来判断是否清仓
        biggest_pullback = (total_money_today - max(g.total_value_list))/max(g.total_value_list)
        print('检查近 %d 的最大损失为 %2f' % (g.total_limit_days, biggest_pullback * 100))
        if biggest_pullback < - g.total_limit_rate: # 当跌幅超过最大限制，则清空仓位
            clear_position(context)
            if g.control_days == 0: # 设定空仓天数
                print('清仓后，未修正的g.control_days为: ', g.control_days)
                g.control_days = g.cool_days
                print('清仓后，修正g.control_days为: ', g.control_days)
            print('持仓情况为: ', g.hold_list)
            print('判断标准为: ', (not g.hold_list))
            if not g.hold_list: # 如果卖光了，那么调整检查全盘资金的数据量，保留10天的数据，因为检查是最近20天，暂停10天
                g.total_value_list = g.total_value_list[-(g.total_limit_days-g.cool_days):]
                

#3-1 交易模块-自定义下单
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))
	return order_target_value(security, value)

#3-3 交易模块-平仓
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

#3-5 交易模块 - 清仓
def clear_position(context):
    if context.portfolio.positions:
        g.cool_days = 5 # 清仓后5天不进行买入操作
        log.info("==> 清仓，卖出所有股票")
        for stock in context.portfolio.positions.keys():
            position = context.portfolio.positions[stock]
            close_position(position)

#2-7 过滤次新股
def filter_new_fund(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=5)]

# 清理list里nan的模块	
def clean_List_nan(List):
    Myarray=np.array(List)
    x = float('nan')
    for elem in Myarray:
        if math.isnan(x):
            x = 0.0
    return Myarray
    
#4-1 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('———————————————————————————————————')