低频，带基本面优化，带风控的，实盘模拟的小盘股策略

策略作者: 水滴

```python
# 风险及免责提示：该策略由聚宽用户在聚宽社区分享，仅供学习交流使用。
# 原文一般包含策略说明，如有疑问请到原文和作者交流讨论。
# 原文网址：https://www.joinquant.com/post/42288
# 标题：实盘模拟的小盘股策略，低频，带基本面优化以及个股风控
# 作者：强势投资

from kuanke.wizard import *
from jqdata import *
import numpy as np
import pandas as pd
import talib
import datetime
import time
import math

## 初始化函数，设定要操作的股票、基准等等
def initialize(context):
    # 设定基准
    set_benchmark('000300.XSHG')
    # 设定滑点
    set_slippage(FixedSlippage(0.01))
    # True为开启动态复权模式，使用真实价格交易
    set_option('use_real_price', True)
    # 设定成交量比例
    set_option('order_volume_ratio', 1)
    # 股票类交易手续费是：买入时佣金万分之三，卖出时佣金万分之三加千分之一印花税, 每笔交易佣金最低扣5块钱
    set_order_cost(OrderCost(open_tax=0, close_tax=0.001, open_commission=0.0003, close_commission=0.0003, min_commission=5), type='stock')

#容器初始化
    check_container_initialize()
    #动态仓位、频率、计数初始化函数
    check_dynamic_initialize()
    # 股票筛选初始化函数
    check_stocks_initialize()
    # 出场初始化函数
    sell_initialize()
    # 入场初始化函数
    buy_initialize()

# 关闭提示
    log.set_level('order', 'info')

# 运行函数
    run_daily(check_stocks, '9:15') #选股
    run_daily(main_stock_pick, '9:16') #买入卖出列表
    run_daily(sell_every_day,'open') #卖出未卖出成功的股票
    run_daily(trade, 'open') #交易
    run_daily(selled_security_list_count, 'after_close') #卖出股票日期计数
    
    
    
#######################！！！新手需要使用的地方！！！###################################################
##动态仓位、频率、计数初始化函数(持仓比例，选股频率，买入频率，卖出频率在这里设置)
def check_dynamic_initialize():
    # 个股最大持仓比重
    g.security_max_proportion = 1
    # 选股和买卖频率
    g.check_stocks_refresh_rate = 1
    # 最大建仓数量
    g.max_hold_stocknum = 7
    
    # 买入频率
    g.buy_refresh_rate = 20
    # 卖出频率
    g.sell_refresh_rate = 10

# 选股频率计数器
    g.check_stocks_days = 0
    #机器学习选股频率计数器
    g.days = 0
    # 买卖交易频率计数器
    g.buy_trade_days=0
    g.sell_trade_days=0
    
## 股票池初筛设置函数(股票初筛在这里设置)
def check_stocks_initialize():
    # 是否过滤停盘
    g.filter_paused = True
    # 是否过滤退市
    g.filter_delisted = True
    # 是否只有ST
    g.only_st = False
    # 是否过滤ST
    g.filter_st = True
    # 股票池(填指数)
    g.security_universe_index = ['all_a_securities']#这里填写指数，全部股票就填['all_a_securities']，沪深300股票就填['000300.XSHG'],中证500就填['000905.XSHG'],沪深300+中证500就填['000300.XSHG','000905.XSHG']
    # 填成分股(填成分股)
    g.security_universe_user_securities = []
    # 行业列表
    g.industry_list = ["801010","801020","801030","801040","801050","801080","801110","801120","801130","801140","801150","801160","801170","801180","801200","801210","801230","801710","801720","801730","801740","801750","801760","801770","801780","801790","801880","801890"]
    # 概念列表
    g.concept_list = []
    # 黑名单
    g.blacklist = ['300268.XSHE','600035.XSHG','300028.XSHE']
    # 买入股票成本列表
    # 待加工？？？？
    
## 买入股票，卖出股票筛选函数
def main_stock_pick(context):
    if g.days % g.check_stocks_refresh_rate != 0:
        g.days += 1
        return
    #print("深度选股第N天",g.days)
    g.sell_stock_list=[]
    g.buy_stock_list = []

####自定义编辑范围#####

#小市值轮动策略-基本面优化版
    q=query(valuation.code).filter(indicator.inc_revenue_annual>0,indicator.inc_revenue_year_on_year>20,indicator.inc_net_profit_to_shareholders_year_on_year>0,indicator.inc_net_profit_to_shareholders_annual>40,valuation.code.in_(g.check_out_lists)).order_by(valuation.market_cap.asc())
    df=get_fundamentals(q)
    
    stockset = list(df['code'])
    
    
    g.sell_stock_list1 = list(context.portfolio.positions.keys())

current_data = get_current_data()
    paused_list = [stock for stock in g.sell_stock_list1 if  current_data[stock].paused]

for stock in g.sell_stock_list1:    
    #############风  控########

buy_time = context.portfolio.positions[stock].init_time
        buy_time_s = buy_time.strftime('%Y-%m-%d')
        current_time = pd.Timestamp(context.current_dt.date())
        d_count = current_time - buy_time
        df_cost = get_price(stock, count=d_count.days + 2, end_date=buy_time_s, frequency='daily', fields=['high'])
        cost = df_cost['high'].max()
        price = context.portfolio.positions[stock].price
        YL = (price-cost)/cost
        
        if stock in paused_list:
            continue
        elif (stock not in stockset[:g.max_hold_stocknum]) or (YL < -0.14):
                g.sell_stock_list.append(stock)
                print(cost)
                print(price)
                print(YL)

for stock in stockset[:g.max_hold_stocknum]:
        if stock in g.sell_stock_list:
            pass
        else:
            g.buy_stock_list.append(stock)
            
####自定义编辑范围#####

#log.info('卖出列表:',g.sell_stock_list)
    #log.info('购买列表:',g.buy_stock_list)
    g.days =1
    return g.sell_stock_list,g.buy_stock_list    
#######################！！！新手需要使用的地方！！！###################################################

##容器初始化(有新的全局容器可以加到这里)(新手忽略这里)
def check_container_initialize():
    #卖出股票列表
    g.sell_stock_list=[]
    #买入股票列表
    g.buy_stock_list = []
    # 获取未卖出的股票
    g.open_sell_securities = []
    # 卖出股票的dict
    g.selled_security_list={}
    #涨停股票列表
    g.ZT=[]

## 出场初始化函数(新手忽略这里)
def sell_initialize():
    # 设定是否卖出buy_lists中的股票
    g.sell_will_buy = True

# 固定出仓的数量或者百分比
    g.sell_by_amount = None
    g.sell_by_percent = None

## 入场初始化函数(新手忽略这里)
def buy_initialize():
    # 是否可重复买入
    g.filter_holded = False

# 委托类型
    g.order_style_str = 'by_cap_mean'
    g.order_style_value = 100

## 股票初筛(新手忽略这里)
def check_stocks(context):
    if g.check_stocks_days % g.check_stocks_refresh_rate != 0:
        # 计数器加一
        g.check_stocks_days += 1
        return
    # 股票池赋值
    g.check_out_lists = get_security_universe(context, g.security_universe_index, g.security_universe_user_securities)
    # 行业过滤
    g.check_out_lists = industry_filter(context, g.check_out_lists, g.industry_list)
    # 概念过滤
    g.check_out_lists = concept_filter(context, g.check_out_lists, g.concept_list)
    # 过滤ST股票
    g.check_out_lists = st_filter(context, g.check_out_lists)
    # 过滤停牌股票
    g.check_out_lists = paused_filter(context, g.check_out_lists)
    # 过滤退市股票
    g.check_out_lists = delisted_filter(context, g.check_out_lists)
    # 过滤黑名单股票
    g.check_out_lists = [s for s in g.check_out_lists if s not in g.blacklist]
    # 计数器归一
    g.check_stocks_days = 1
    return

## 卖出未卖出成功的股票(新手忽略这里)
def sell_every_day(context):
    g.open_sell_securities = list(set(g.open_sell_securities))
    open_sell_securities = [s for s in context.portfolio.positions.keys() if s in g.open_sell_securities]
    if len(open_sell_securities)>0:
        for stock in open_sell_securities:
            order_target_value(stock, 0)
    g.open_sell_securities = [s for s in g.open_sell_securities if s in context.portfolio.positions.keys()]
    return

## 交易函数(新手忽略这里)
def trade(context):

# 获取 buy_lists 列表
    buy_lists = g.buy_stock_list

# 买入股票筛选
    if g.buy_trade_days % g.buy_refresh_rate == 0:

# 过滤涨停股票
        buy_lists = high_limit_filter(context, buy_lists)
        log.info('购买列表最终',buy_lists)

# 卖出操作
    if g.sell_trade_days % g.sell_refresh_rate != 0:
        # 计数器加一
        g.sell_trade_days += 1
    else:
        print("执行卖出第N天",g.sell_trade_days)
        # 卖出股票
        sell(context, buy_lists)
        # 计数器归一
        g.sell_trade_days = 1

# 买入操作
    if g.buy_trade_days % g.buy_refresh_rate != 0:
        # 计数器加一
        g.buy_trade_days += 1
    else:
        print("执行买入第N天",g.buy_trade_days)
        # 买入股票
        buy(context, buy_lists)
        # 计数器归一
        g.buy_trade_days = 1

##################################  交易函数群 ##################################(新手忽略)

# 交易函数 - 出场
def sell(context, buy_lists):
    # 获取 sell_lists 列表
    init_sl = context.portfolio.positions.keys()
    sell_lists = context.portfolio.positions.keys()

# 判断是否卖出buy_lists中的股票
    if not g.sell_will_buy:
        sell_lists = [security for security in sell_lists if security not in buy_lists]

### _出场函数筛选-开始 ###
    sell_lists = g.sell_stock_list
    ### _出场函数筛选-结束 ###

# 卖出股票
    if len(sell_lists)>0:
        for stock in sell_lists:
            sell_by_amount_or_percent_or_none(context,stock, g.sell_by_amount, g.sell_by_percent, g.open_sell_securities)

# 获取卖出的股票, 并加入到 g.selled_security_list中
    selled_security_list_dict(context,init_sl)

return

# 交易函数 - 入场
def buy(context, buy_lists):

# 判断是否可重复买入
    buy_lists = holded_filter(context,buy_lists)

# 获取最终的 buy_lists 列表
    Num = g.max_hold_stocknum - len(context.portfolio.positions)
    buy_lists = buy_lists[:Num]

# 买入股票
    if len(buy_lists)>0:
        # 分配资金
        result = order_style(context,buy_lists,g.max_hold_stocknum, g.order_style_str, g.order_style_value)
        for stock in buy_lists:
            if len(context.portfolio.positions) < g.max_hold_stocknum:
                # 获取资金
                Cash = result[stock]
                # 判断个股最大持仓比重
                value = judge_security_max_proportion(context,stock,Cash,g.security_max_proportion)
                # 判断单只最大买入股数或金额
                amount = max_buy_value_or_amount(stock,value,None,None)
                # 下单
                order(stock, amount, MarketOrderStyle())
    return

###################################  公用函数群 ##################################(新手忽略)

## 过滤同一标的继上次卖出N天不再买入
def filter_n_tradeday_not_buy(security, n=0):
    try:
        if (security in g.selled_security_list.keys()) and (g.selled_security_list[security]<n):
            return False
        return True
    except:
        return True

## 是否可重复买入
def holded_filter(context,security_list):
    if not g.filter_holded:
        security_list = [stock for stock in security_list if stock not in context.portfolio.positions.keys()]
    # 返回结果
    return security_list

## 卖出股票加入dict
def selled_security_list_dict(context,security_list):
    selled_sl = [s for s in security_list if s not in context.portfolio.positions.keys()]
    if len(selled_sl)>0:
        for stock in selled_sl:
            g.selled_security_list[stock] = 0

## 过滤停牌股票
def paused_filter(context, security_list):
    if g.filter_paused:
        current_data = get_current_data()
        security_list = [stock for stock in security_list if not current_data[stock].paused]
    # 返回结果
    return security_list

## 过滤退市股票
def delisted_filter(context, security_list):
    if g.filter_delisted:
        current_data = get_current_data()
        security_list = [stock for stock in security_list if not (('退' in current_data[stock].name) or ('*' in current_data[stock].name))]
    # 返回结果
    return security_list

## 过滤ST股票
def st_filter(context, security_list):
    if g.only_st:
        current_data = get_current_data()
        security_list = [stock for stock in security_list if current_data[stock].is_st]
    else:
        if g.filter_st:
            current_data = get_current_data()
            security_list = [stock for stock in security_list if not current_data[stock].is_st]
    # 返回结果
    return security_list

# 过滤涨停股票
def high_limit_filter(context, security_list):
    current_data = get_current_data()
    security_list = [stock for stock in security_list if not (current_data[stock].day_open >= current_data[stock].high_limit)]
    # 返回结果
    return security_list

# 获取股票股票池
def get_security_universe(context, security_universe_index, security_universe_user_securities):
    temp_index = []
    for s in security_universe_index:
        if s == 'all_a_securities':
            temp_index += list(get_all_securities(['stock'], context.current_dt.date()).index)
        else:
            temp_index += get_index_stocks(s)
    for x in security_universe_user_securities:
        temp_index += x
    return  sorted(list(set(temp_index)))

# 行业过滤
def industry_filter(context, security_list, industry_list):
    if len(industry_list) == 0:
        # 返回股票列表
        return security_list
    else:
        securities = []
        for s in industry_list:
            temp_securities = get_industry_stocks(s)
            securities += temp_securities
        security_list = [stock for stock in security_list if stock in securities]
        # 返回股票列表
        return security_list

# 概念过滤
def concept_filter(context, security_list, concept_list):
    if len(concept_list) == 0:
        return security_list
    else:
        securities = []
        for s in concept_list:
            temp_securities = get_concept_stocks(s)
            securities += temp_securities
        security_list = [stock for stock in security_list if stock in securities]
        # 返回股票列表
        return security_list
        
## 卖出股票日期计数
def selled_security_list_count(context):
    #g.daily_risk_management = True
    if len(g.selled_security_list)>0:
        for stock in g.selled_security_list.keys():
            g.selled_security_list[stock] += 1
            
#获取交易日
def shifttradingday(date,shift):
    #获取N天前的交易日日期
    # 获取所有的交易日，返回一个包含所有交易日的 list,元素值为 datetime.date 类型.
    tradingday = get_all_trade_days()
    # 得到date之后shift天那一天在列表中的行标号 返回一个数
    shiftday_index = list(tradingday).index(date)+shift
    # 根据行号返回该日日期 为datetime.date类型
    return tradingday[shiftday_index]   
```

发布时间: 2025-02-26 20:58:19

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