# 羊駝反轉策略 > 來源：https://uqer.io/community/share/566982a4f9f06c6c8a91b7a2 ```py # 第一步：設置基本參數 start = '2011-04-01' # 回測起始時間 end = '2015-12-01' # 回測結束時間 capital_base = 1000000 # 起始資金 refresh_rate = 10 # 調倉頻率 benchmark = 'HS300' # 策略參考標準 freq = 'd' # 策略類型，'d'表示日間策略使用日線回測 # 第二步：選擇主題，設置股票池 universe = set_universe('HS300') # 股票池 import numpy as np import pandas as pd data=DataAPI.MktStockFactorsOneDayGet(tradeDate='20110331',secID=universe,ticker=u"",field=['secID','REVS10'],pandas="1") #獲取start前一日股票池中十日收益 buylist=data.dropna().sort(columns='REVS10',ascending=False).tail(10)['secID'].values.tolist() #將十日收益最差的十只股票組成list def initialize(account): # 初始化虛擬賬戶狀態 account.stocks_num=10 def handle_data(account): # 每個交易日的買入賣出指令 if account.stocks_num==10: #第一天交易使用buylist global buylist account.universe=buylist hist_prices = account.get_attribute_history('closePrice', 1) for i in account.universe: order(i,100000/hist_prices[i][0]) account.stocks_num=1 #之后為非第一天交易策略 sellist=[] replacelist=[] sell=DataAPI.MktStockFactorsOneDayGet(tradeDate=account.current_date,secID=account.universe,ticker=u"",field=['secID','REVS10'],pandas="1") #獲得十日以來賬戶中所有股票的收益 sellist.append(sell.min()['secID']) #找出收益最差的股票加入sellist replace=DataAPI.MktStockFactorsOneDayGet(tradeDate=account.current_date,secID=universe,ticker=u"",field=['secID','REVS10'],pandas="1") #獲得股票池中十日以來所有股票的收益 replace=replace.set_index('secID').drop(buylist) replace=replace.dropna().sort(columns='REVS10',ascending=False).tail(1).reset_index()['secID'].values.tolist() #獲得收益最差的股票作為賬戶中新的代替股票 replacelist.append(replace) account.universe.remove(sell.min()['secID']) account.universe=account.universe+replacelist[0] hist_prices = account.get_attribute_history('closePrice', 1) #獲取前一個交易日賬戶股票價格 for stk in sellist: order_to(stk,0) for stk in account.universe: order(stk,account.cash/10/hist_prices[stk][0]) ```