魔改版小市值策略-编程知识

策略思路

最近几年，小市值策略一直都收益不错（当然，不包含17年和18年）。小市值因子对收益的影响是很大的。特别是行情不好的时候，大家都忙着炒作热点，那么这时候符合题材的小市值更加符合炒作标准了。

为什么说是魔改版的小市值策略呢，因为最终选取小市值的方法真的很玄学。

上收益效果图：
在这里插入图片描述
三年多，有7.45倍的收益，实属夸张了哈。有这个收益，还要什么自行车啊。

那么，这个策略玄学在哪里呢。

核心想法：

1、选取100个市值最小的股票，剔除ST股、次新股、科创板、北交所股票等等。

2、从剩下的股票中对证券代码进行排序，这就是最玄学的地方。然后选取排序靠前的5只股票。

3、每周第一个交易日早上进行轮换。

核心代码

def monthly_filter(context):today = context.current_dtyesterday = today -  datetime.timedelta(days=1)start_day = today -  datetime.timedelta(days=375)yesterday = yesterday.strftime('%Y-%m-%d')# 选出小市值的股票q = query(valuation.code,valuation.circulating_market_cap).filter(valuation.circulating_market_cap.between(0,1000)).order_by(valuation.circulating_market_cap.asc()).limit(100)codes = get_fundamentals(q).code.tolist()# 筛选出主板、创业板股票codes = [code for code in codes if code[:2] in ('60','00','30')]# log.info("Top 10 小市值:" + str(codes[:10]))# 过滤ST股票df = get_extras('is_st', codes, end_date=yesterday,count=1)df = df.Tdf.columns = ['is_st']df=df[df['is_st']==0]codes = df.index.tolist()# 过滤次新股q = query(finance.STK_LIST.code).filter(finance.STK_LIST.start_date <=start_day,finance.STK_LIST.code.in_(codes))codes = list(finance.run_query(q).code)g.pools = set(codes)def weekly_filter(context):today = context.current_dtyesterday = today -  datetime.timedelta(days=1)start_day = today -  datetime.timedelta(days=375)yesterday = yesterday.strftime('%Y-%m-%d')codes = list(g.pools)if codes != []:# 过滤ST股票df = get_extras('is_st', codes, end_date=yesterday,count=1)df = df.Tdf.columns = ['is_st']df=df[df['is_st']==0]codes = df.index.tolist()# codes = filter_st_stock(codes)g.pools = set(codes)else:# 选出小市值的股票q = query(valuation.code,valuation.circulating_market_cap).filter(valuation.circulating_market_cap.between(0,1000)).order_by(valuation.circulating_market_cap.asc()).limit(100)codes = get_fundamentals(q).code.tolist()# 筛选出主板、创业板股票codes = [code for code in codes if code[:2] in ('60','00','30')]# 过滤ST股票df = get_extras('is_st', codes, end_date=yesterday,count=1)df = df.Tdf.columns = ['is_st']df=df[df['is_st']==0]codes = df.index.tolist()# 过滤次新股q = query(finance.STK_LIST.code).filter(finance.STK_LIST.start_date <= start_day,finance.STK_LIST.code.in_(codes))codes = list(finance.run_query(q).code)g.pools = set(codes)# log.info('每周五选定的股票:', g.pools)#1-1 准备股票池
def prepare_stock_list(context):#获取已持有列表g.hold_list= list(context.portfolio.positions.keys())#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'], 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 = []# 获取今天的日期today = context.current_dttoday_Year = today.strftime('%Y')NewYears = {'2010': '02-14', '2011': '02-03', '2012': '01-23', '2013': '02-10', '2014': '01-31', '2015': '02-19', '2016': '02-08', '2017': '01-28', '2018': '02-16', '2019': '02-05', '2020': '01-25', '2021': '02-12', '2022': '02-01', '2023': '01-22', '2024': '02-10', '2025': '01-29', '2026': '02-17', '2027': '02-06', '2028': '01-26', '2029': '02-13', '2030': '02-03'}spring_festival_date = NewYears[today_Year]#判断今天是否为账户资金再平衡的日期 或者 元旦到春节之间的日期g.no_trading_today_signal = today_is_between(context, '04-05', '04-30') or today_is_between(context, '01-01', spring_festival_date)def get_stock_list(context):final_list = set()initial_list = list(g.pools)if len(initial_list) == 0:return []initial_list = filter_paused_stock(initial_list)initial_list = filter_st_stock(initial_list)today = context.current_dt# 通过timedelta算出前一天的日期delta = datetime.timedelta(days=1)yesterday = today - deltayesterday = yesterday.strftime('%Y-%m-%d')q = query(valuation.code, valuation.circulating_market_cap).filter(valuation.code.in_(initial_list)).limit(g.stock_num)codes = get_fundamentals(q).code.tolist()circulating_market_cap_list = get_fundamentals(q).circulating_market_cap.tolist()log.info('数据库拉取的股票数量：{}'.format(len(codes)))log.info('最小市值：{}， 最大市值：{}'.format(min(circulating_market_cap_list), max(circulating_market_cap_list)))final_list = codes.copy()print('final_list数量:{}'.format(len(final_list)))final_list = filter_paused_stock(final_list)print('过滤停牌后的股票数量:{}'.format(len(final_list)))final_list = filter_st_stock(final_list)log.info('每周一买入的股票数量:'.format(len(final_list)))return final_list#1-3 整体调整持仓
def weekly_adjustment(context):if g.no_trading_today_signal:return#获取应买入列表 target_list = get_stock_list(context)#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))order_target(stock, 0)else:log.info("已持有[%s]" % (stock))#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 open_position(stock, value):if len(context.portfolio.positions) == target_num:break