Value Investing/Indicator Stock Picking (akshare)

Using akshare's data source, you can obtain all stock data and public financial data, and you can perform conditional screening to obtain stocks that meet the conditions.

This set of templates can be used for value investing and index stock selection. The stock selection cycle is at the daily level. The results can then be emailed.

import time
import akshare as ak
## A 股上市公司的实时行情数据
stock_zh_a_spot_df = ak.stock_zh_a_spot()
#print(stock_zh_a_spot_df)
##取前300测试
##取前300测试
df_stock = stock_zh_a_spot_df[['代码','名称']][:20]
anyData = {'stock':'00','name':'name_test','指标1':'var1','指标1':'var1','指标2':'var2','指标3':'var3','指标4':'var4','综合评估':'varAll'}
dfResult = pd.DataFrame(anyData,index=[0])
 
for row_index, row in df_stock.iterrows():
    try:
    # print(row['code'])
    # print(row['name'])
        r_code = row['代码'][2:]
        r_name = row['名称']

        print(r_code)
        ##指标1 - 过去5年来平均净资产收益率高于14%
        df = ak.stock_financial_analysis_indicator(r_code)# 财务指标数据 工行财报
        # print(df.head())
        df = df.set_index(df['日期'])
        print(df.head())
        df1 = df[df.index>'2015-01-01']['净资产收益率(%)']
        df1_sum = df1.replace('--',0).astype(float).sum(axis = 0, skipna = True)
        df1_count = df1.count()
        var1 = (df1_sum / df1_count)>14

        ##指标2- 市盈率低于30 并且大于 0 
        day = (datetime.datetime.now()- datetime.timedelta(days=30))
        dateStart = datetime.datetime(day.year, day.month, day.day, 0, 0, 0)##过去30天的数据
        dateStart = datetime.datetime.strptime(str(dateStart),'%Y-%m-%d %H:%M:%S')
        dateStart = datetime.datetime.date(dateStart) 
        df2 = ak.stock_a_lg_indicator("601398")
        df2_mean = df2[df2.trade_date >dateStart ].pe.mean()
        var2 = df2_mean >0 and df2_mean < 30


        #指标3：经营现金流为正

        df3 = df#财务指标数据
        var3 = float( df3['每股经营性现金流(元)'].iat[1] ) > 0
        # print(var3)

        #指标4：新期的净利润大于前5年的净利润 取万元

        var4_1 = float(df3['扣除非经常性损益后的净利润(元)'].iat[1])/ 10000 
        var4_2 =  df3['扣除非经常性损益后的净利润(元)'].iloc[2:8].astype(np.float).max()/10000 

        var4 = var4_1 > var4_2

        ##综合评估

        varAll = var1 and var2 and var3 and var4
        if varAll == True:
            print(row)
        anyData = {'stock':r_code,'name':r_name,'指标1':var1,'指标1':var1,'指标2':var2,'指标3':var3,'指标4':var4,'综合评估':varAll}
        df_idex = row_index+1
        dfResult.loc[df_idex] = anyData
        print(dfResult)
    except:
        continue
    #time.sleep(7)

The indicators here can be rewritten, re-added. Get used to it.

Value Investing/Indicator Stock Picking (akshare)

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