# Porfolio（現金比率+負債現金+現金保障倍數）+市盈率 > 來源：https://uqer.io/community/share/566a896bf9f06c6c8a91cae7 ```py ?DataAPI.MktStockFactorsOneDayGet ``` ```py import numpy as np import pandas as pd start = '2015-01-01' # 回測起始時間 end = '2015-11-30' # 回測結束時間 benchmark = 'HS300' # 策略參考標準 universe = set_universe('HS300') # 證券池，支持股票和基金 capital_base = 100000 # 起始資金 freq = 'd' # 策略類型，'d'表示日間策略使用日線回測，'m'表示日內策略使用分鐘線回測 refresh_rate = 1 # 調倉頻率，表示執行handle_data的時間間隔，若freq = 'd'時間間隔的單位為交易日，若freq = 'm'時間間隔為分鐘 def initialize(account): # 初始化虛擬賬戶狀態 pass def handle_data(account): # 每個交易日的買入賣出指令 market_val = DataAPI.MktEqudGet(tradeDate=account.current_date,field=u"secID,negMarketValue",pandas="1") #獲取所有股票的市值 factor = DataAPI.MktStockFactorsOneDayGet(tradeDate=account.current_date,field='secID,ROE,ROA,CashRateOfSales,FinancialExpenseRate,CashToCurrentLiability,OperCashInToCurrentLiability,GrossIncomeRatio,NetProfitRatio,PE,PB',pandas="1") #獲取所有股票的相關因子 # print factor factor.set_index('secID',inplace=True); sec_val_mkt = {'symbol':[], 'factor_value':[], 'market_value':[]} x='CashToCurrentLiability' y='OperCashInToCurrentLiability' z='PE' for stock in account.universe: sec_val_mkt['symbol'].append(stock) factor_va=float(1/3*factor.ix[stock][x]+1/3*factor.ix[stock][y]+1/3*factor.ix[stock][z]); sec_val_mkt['factor_value'].append(factor_va) sec_val_mkt['market_value'].append(float(market_val.negMarketValue[market_val.secID==stock])) sec_val_mkt = pd.DataFrame(sec_val_mkt).sort(columns='factor_value',ascending=True).reset_index() sec_val_mkt = sec_val_mkt[:int(len(sec_val_mkt)*0.1)] #排序并選擇前10% buylist = list(sec_val_mkt.symbol) #買入股票列表 sum_market_val = sum(sec_val_mkt.market_value) position = np.array(sec_val_mkt.market_value)/sum_market_val*account.cash for stock in account.valid_secpos: if stock not in buylist: order_to(stock, 0) for stock in buylist: if stock not in account.valid_secpos: order(stock, position[buylist.index(stock)]) return ```  ```py bt.blotter None ```