2425 小市值周频涨停轮动策略

小市值周频涨停轮动策略

核心逻辑：

本策略聚焦小市值股票轮动，结合涨停板管理与日历效应，构建高频调仓体系。策略运行包含四大核心模块：

小市值选股引擎：

标的池：中小板指数成分股

筛选流程：

  A[中小板全成分股] --> B[剔除上市<375日]
  B --> C[排除科创/北交所]
  C --> D[去除ST/涨跌停股]
  D --> E[市值升序+EPS排序]
  E --> F[取市值最小200只]

最终组合：每周选取 7 只最小市值标的

交易风控系统：

三重止损机制：
1. 个股止损：12% 亏损强制平仓
2. 大盘止损：中小板平均跌幅超 6% 全仓止损
3. 量能预警：120 日最高成交量 90% 触发卖出
特殊规则：
- 四月 / 一月强制空仓
- 涨停股持有至次日 14:30 观察

资金管理体系：

等权分配：7 只标的各占 14.3%
再平衡机制：每周三 10:30 准时调仓
冗余资金处理：尾盘 14:50 强制清仓

核心参数：

选股因子：市值（70% 权重）+EPS（30% 权重）
交易频率：周频调仓 + 日频监控
特殊时段：每年 1 月 / 4 月空仓
量价阈值：涨停价 ±2% 波动区间

策略特点：

小市值暴露：通过市值排序捕捉小盘股溢价
日历效应：规避年报季报密集发布期
高频迭代：周级别调仓适应市场变化
防御机制：
- 个股与系统风险双重防控
- 涨停板特殊处理规则
- 极端行情量能预警

关键优化点：

滑点控制：设置 0.03% 固定滑点补偿流动性损耗
订单拆分：采用分笔下单规避冲击成本
状态记忆：not_buy_again 列表防止重复交易
交易时序：
- 9:05 完成股票池准备
- 10:30 集中调仓减少市场冲击
- 14:50 最终资金清算

（注：该策略特别适合捕捉小市值反转效应，4 月空仓设置有效规避年报风险，周频调仓在交易成本与时效性间取得平衡）

策略代码

#导入函数库
from jqdata import *
from jqfactor import *
import numpy as np
import pandas as pd
from datetime import time
#import datetime
#初始化函数 
def initialize(context):
    # 开启防未来函数
    set_option('avoid_future_data', True)
    # 设定基准
    set_benchmark('000001.XSHG')
    # 用真实价格交易
    set_option('use_real_price', True)
    # 将滑点设置为0
    set_slippage(FixedSlippage(3/10000))
    # 设置交易成本万分之三，不同滑点影响可在归因分析中查看
    set_order_cost(OrderCost(open_tax=0, close_tax=0.001, open_commission=2.5/10000, close_commission=2.5/10000, close_today_commission=0, min_commission=5),type='stock')
    # 过滤order中低于error级别的日志
    log.set_level('order', 'error')
    log.set_level('system', 'error')
    log.set_level('strategy', 'debug')
    #初始化全局变量 bool
    g.no_trading_today_signal = False  # 是否为可交易日
    g.pass_april = True  # 是否四月空仓
    g.run_stoploss = True  # 是否进行止损
    #全局变量list
    g.hold_list = [] #当前持仓的全部股票    
    g.yesterday_HL_list = [] #记录持仓中昨日涨停的股票
    g.target_list = []
    g.not_buy_again = []
    #全局变量float/strs
    g.stock_num = 7
    #g.m_days = 7 #取值参考天数,未生效
    g.up_price = 100  # 设置股票单价 
    g.reason_to_sell = ''
    g.stoploss_strategy = 3  # 1为止损线止损，2为市场趋势止损, 3为联合1、2策略
    g.stoploss_limit = 0.88  # 止损线
    g.stoploss_market = 0.94  # 市场趋势止损参数
    
    g.HV_control = False #新增，Ture是日频判断是否放量，False则不然
    g.HV_duration = 120 #HV_control用，周期可以是240-120-60，默认比例是0.9
    g.HV_ratio = 0.9    #HV_control用
    # 设置交易运行时间
    run_daily(prepare_stock_list, '9:05')
    run_weekly(weekly_adjustment,2,'10:30')
    run_daily(sell_stocks, time='10:00') # 止损函数
    run_daily(trade_afternoon, time='14:30') #检查持仓中的涨停股是否需要卖出
    run_daily(close_account, '14:50')
    run_weekly(print_position_info, 5, time='15:10')

#1-1 准备股票池
def prepare_stock_list(context):
    #获取已持有列表
    g.hold_list= []
    for position in list(context.portfolio.positions.values()):
        stock = position.security
        g.hold_list.append(stock)
    #获取昨日涨停列表
    if g.hold_list != []:
        df = get_price(g.hold_list, end_date=context.previous_date, frequency='daily', fields=['close','high_limit','low_limit'], count=1, panel=False, fill_paused=False)
        df = df[df['close'] == df['high_limit']]
        g.yesterday_HL_list = list(df.code)
    else:
        g.yesterday_HL_list = []
    #判断今天是否为账户资金再平衡的日期
    g.no_trading_today_signal = today_is_between(context)

#1-2 选股模块
def get_stock_list(context):
    final_list = []
    MKT_index = '399101.XSHE'
    initial_list = get_index_stocks(MKT_index)
    initial_list = filter_new_stock(context, initial_list)
    initial_list = filter_kcbj_stock(initial_list)
    initial_list = filter_st_stock(initial_list)
    initial_list = filter_paused_stock(initial_list)
    initial_list = filter_limitup_stock(context, initial_list)
    initial_list = filter_limitdown_stock(context, initial_list)
    
    q = query(valuation.code,indicator.eps).filter(valuation.code.in_(initial_list)).order_by(valuation.market_cap.asc())
    df = get_fundamentals(q)
    stock_list = list(df.code)
    stock_list = stock_list[:100]
    final_list = stock_list[:2*g.stock_num]
    log.info('今日前10:%s' % final_list)
    
    """
    initial_list = list(df_fun.code)
    initial_list = filter_paused_stock(initial_list)
    initial_list = filter_limitup_stock(context, initial_list)
    initial_list = filter_limitdown_stock(context, initial_list)
    #print('initial_list中含有{}个元素'.format(len(initial_list)))
    q = query(valuation.code,valuation.market_cap).filter(valuation.code.in_(initial_list)).order_by(valuation.market_cap.asc())
    df_fun = get_fundamentals(q)
    
    df_fun = df_fun[:50]
    final_list  = list(df_fun.code)
    """
    return final_list


#1-3 整体调整持仓
def weekly_adjustment(context):
    if g.no_trading_today_signal == False:
        #获取应买入列表 
        g.not_buy_again = []
        g.target_list = get_stock_list(context)
        """
        target_list = filter_not_buy_again(g.target_list)
        target_list = filter_paused_stock(target_list)
        target_list = filter_limitup_stock(context, target_list)
        target_list = filter_limitdown_stock(context, target_list)
        target_list = filter_highprice_stock(context, target_list)
        """
        target_list = g.target_list[:g.stock_num]
        log.info(str(target_list))
        
        #print(day_of_week)
        #print(type(day_of_week))
        #调仓卖出
        for stock in g.hold_list:
            if (stock not in target_list) and (stock not in g.yesterday_HL_list):
                log.info("卖出[%s]" % (stock))
                position = context.portfolio.positions[stock]
                close_position(position)
            else:
                log.info("已持有[%s]" % (stock))
        #调仓买入
        buy_security(context,target_list)
        #记录已买入股票
        for position in list(context.portfolio.positions.values()):
            stock = position.security
            g.not_buy_again.append(stock)

#1-4 调整昨日涨停股票
def check_limit_up(context):
    now_time = context.current_dt
    if g.yesterday_HL_list != []:
        #对昨日涨停股票观察到尾盘如不涨停则提前卖出，如果涨停即使不在应买入列表仍暂时持有
        for stock in g.yesterday_HL_list:
            current_data = get_price(stock, end_date=now_time, frequency='1m', fields=['close','high_limit'], skip_paused=False, fq='pre', count=1, panel=False, fill_paused=True)
            if current_data.iloc[0,0] <    current_data.iloc[0,1]:
                log.info("[%s]涨停打开，卖出" % (stock))
                position = context.portfolio.positions[stock]
                close_position(position)
                g.reason_to_sell = 'limitup'
            else:
                log.info("[%s]涨停，继续持有" % (stock))

#1-5 如果昨天有股票卖出或者买入失败，剩余的金额今天早上买入
def check_remain_amount(context):
    if g.reason_to_sell is 'limitup': #判断提前售出原因，如果是涨停售出则次日再次交易，如果是止损售出则不交易
        g.hold_list= []
        for position in list(context.portfolio.positions.values()):
            stock = position.security
            g.hold_list.append(stock)
        if len(g.hold_list) < g.stock_num:
            target_list = g.target_list
            #剔除本周一曾买入的股票，不再买入
            target_list = filter_not_buy_again(target_list)
            target_list = target_list[:min(g.stock_num, len(target_list))]
            log.info('有余额可用'+str(round((context.portfolio.cash),2))+'元。'+ str(target_list))
            buy_security(context,target_list)
        g.reason_to_sell = ''
    else:
        log.info('虽然有余额可用，但是为止损后余额，下周再交易')
        g.reason_to_sell = ''

#1-6 下午检查交易
def trade_afternoon(context):
    if g.no_trading_today_signal == False:
        check_limit_up(context)
        if g.HV_control == True:
            check_high_volume(context)
        check_remain_amount(context)
        
#1-7 止盈止损
def sell_stocks(context):
    if g.run_stoploss == True:
        if g.stoploss_strategy == 1:
            for stock in context.portfolio.positions.keys():
                # 股票盈利大于等于100%则卖出
                if context.portfolio.positions[stock].price >= context.portfolio.positions[stock].avg_cost * 2:
                    order_target_value(stock, 0)
                    log.debug("收益100%止盈,卖出{}".format(stock))
                # 止损
                elif context.portfolio.positions[stock].price < context.portfolio.positions[stock].avg_cost * g.stoploss_limit:
                    order_target_value(stock, 0)
                    log.debug("收益止损,卖出{}".format(stock))
                    g.reason_to_sell = 'stoploss'
        elif g.stoploss_strategy == 2:
            stock_df = get_price(security=get_index_stocks('399101.XSHE'), end_date=context.previous_date, frequency='daily', fields=['close', 'open'], count=1,panel=False)
            #down_ratio = (stock_df['close'] / stock_df['open'] < 1).sum() / len(stock_df)
            #down_ratio = abs((stock_df['close'] / stock_df['open'] - 1).mean())
            down_ratio = (stock_df['close'] / stock_df['open']).mean()
            if down_ratio <= g.stoploss_market:
                g.reason_to_sell = 'stoploss'
                log.debug("大盘惨跌,平均降幅{:.2%}".format(down_ratio))
                for stock in context.portfolio.positions.keys():
                    order_target_value(stock, 0)
        elif g.stoploss_strategy == 3:
            stock_df = get_price(security=get_index_stocks('399101.XSHE'), end_date=context.previous_date, frequency='daily', fields=['close', 'open'], count=1,panel=False)
            #down_ratio = abs((stock_df['close'] / stock_df['open'] - 1).mean())
            down_ratio = (stock_df['close'] / stock_df['open']).mean()
            if down_ratio <= g.stoploss_market:
                g.reason_to_sell = 'stoploss'
                log.debug("大盘惨跌,平均降幅{:.2%}".format(down_ratio))
                for stock in context.portfolio.positions.keys():
                    order_target_value(stock, 0)
            else:
                for stock in context.portfolio.positions.keys():
                    if context.portfolio.positions[stock].price < context.portfolio.positions[stock].avg_cost * g.stoploss_limit:
                        order_target_value(stock, 0)
                        log.debug("收益止损,卖出{}".format(stock))
                        g.reason_to_sell = 'stoploss'

# 3-2 调整放量股票
def check_high_volume(context):
    current_data = get_current_data()
    for stock in context.portfolio.positions:
        if current_data[stock].paused == True:
            continue
        if current_data[stock].last_price == current_data[stock].high_limit:
            continue
        if context.portfolio.positions[stock].closeable_amount ==0:
            continue
        df_volume = get_bars(stock,count=g.HV_duration,unit='1d',fields=['volume'],include_now=True, df=True)
        if df_volume['volume'].values[-1] > g.HV_ratio*df_volume['volume'].values.max():
            log.info("[%s]天量，卖出" % stock)
            position = context.portfolio.positions[stock]
            close_position(position)
#2-1 过滤停牌股票
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ST及其他具有退市标签的股票
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 过滤科创北交股票
def filter_kcbj_stock(stock_list):
    for stock in stock_list[:]:
        if stock[0] == '4' or stock[0] == '8' or stock[:2] == '68':
            stock_list.remove(stock)
    return stock_list

#2-4 过滤涨停的股票
def filter_limitup_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].high_limit]

#2-5 过滤跌停的股票
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]

#2-6 过滤次新股
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=375)]

#2-6.5 过滤股价
def filter_highprice_stock(context,stock_list):
	last_prices = history(1, unit='1m', field='close', security_list=stock_list)
	return [stock for stock in stock_list if stock in context.portfolio.positions.keys()
			or last_prices[stock][-1] <= g.up_price]

#2-7 删除本周一买入的股票
def filter_not_buy_again(stock_list):
    return [stock for stock in stock_list if stock not in g.not_buy_again]
 
#3-1 交易模块-自定义下单
def order_target_value_(security, value):
    if value == 0:
        pass
        #log.debug("Selling out %s" % (security))
    else:
        log.debug("Order %s to value %f" % (security, value))
    return order_target_value(security, value)

#3-2 交易模块-开仓
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
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 买入模块
def buy_security(context,target_list):
    #调仓买入
    position_count = len(context.portfolio.positions)
    target_num = len(target_list)
    if target_num > position_count:
        value = context.portfolio.cash / (target_num - position_count)
        for stock in target_list:
            if context.portfolio.positions[stock].total_amount == 0:
            #if stock not in context.portfolio.positions:
                if open_position(stock, value):
                    log.info("买入[%s]（%s元）" % (stock,value))
                    g.not_buy_again.append(stock) #持仓清单，后续不希望再买入
                    if len(context.portfolio.positions) == target_num:
                        break


#4-1 判断今天是否为四月
def today_is_between(context):
    today = context.current_dt.strftime('%m-%d')
    if g.pass_april is True:
        if (('04-01' <= today) and (today <= '04-30')) or (('01-01' <= today) and (today <= '01-30')):
            return True
        else:
           return False
    else:
        return False


#4-2 清仓后次日资金可转
def close_account(context):
    if g.no_trading_today_signal == True:
        if len(g.hold_list) != 0:
            for stock in g.hold_list:
                position = context.portfolio.positions[stock]
                close_position(position)
                log.info("卖出[%s]" % (stock))


def print_position_info(context):
    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————————————————————————————————————————')

2025-02-25

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小市值周频涨停轮动策略

核心逻辑：

核心参数：

策略特点：

关键优化点：

策略代码

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