对复权因子的介绍可参考

通过计算复权因子求得当日前一天收盘价，并存储在MongoDB数据库中
代码实现

def fill_au_factor_pre_close(begin_date,end_date): """ 为daily数据集填充 1、复权因子au_factor，复权因子计算方式：au_factor= hfq_close/close 2、pre_close = close(-1) * au_factor(-1)/au_factor :param begin_date:开始日期 :param end_date:结束日期 """ all_codes = get_all_codes() for code in all_codes: hfq_daily_cursor = DB_CONN['daily_hfq'].find( {'code':code,'date':{'$gte':begin_date,'$lte':end_date},'index':False}, sort=[('date',ASCENDING)], projection={'date':True,'close':True} ) date_hfq_close_dict = dict([(x['date'],x['close']) for x in hfq_daily_cursor]) daily_cursor = DB_CONN['daily'].find( {'code':code,'date':{'$gte':begin_date,'$lte':end_date},'index':False}, sort=[('date',ASCENDING)], projection={'date':True,'close':True} ) last_close = -1 last_au_factor = -1 update_requests = [] for daily in daily_cursor: date = daily['date'] try: close = daily['close'] doc = dict() #复权因子 = 当日后复权价格/当日的实际价格 au_factor = round(date_hfq_close_dict['date']/close,2) doc['au_factor'] = au_factor #当日前收价=前一日实际收盘价 * 前一日复权因子/当日复权因子 if last_au_factor != -1 and last_close != -1: pre_close = last_close * last_au_factor / au_factor doc['pre_close'] = round(pre_close,2) last_close = close last_au_factor = au_factor update_requests.append( UpdateOne( {'code':code,'date':date,'index':False}, {'$set':doc} ) ) except: print('计算复权因子时发生错误，股票代码：%s，日期：%s' %(code,date),flush=True) #恢复成初始值，防止出错 last_close = -1 last_au_factor = -1 if len(update_requests)>0: update_result = DB_CONN['daily'].bulk_write(update_requests,ordered=False) print('填充复权因子和前收，股票：%s ，更新：%4d条'%(code,update_result.modified_count),flush=False)