# 最经典的Momentum和Contrarian在中国市场的测试-yanheven改进 > 来源：https://uqer.io/community/share/5663f369f9f06c6c8a91b3af ## Momentum 策略思路 + Momentum：业绩好的股票会继续保持其上涨的势头，业绩差的股票会保持其下跌的势头 策略实现 + Momentum：每次调仓将股票按照前一段时间的累计收益率排序并分组，买入历史累计收益 最高 的那一组 ```py start = datetime(2011, 1, 1) # 回测起始时间 end = datetime(2015, 12, 5) # 回测结束时间 benchmark = 'HS300' # 使用沪深 300 作为参考标准 universe = set_universe('HS300') # 股票池，沪深 300 capital_base = 100000 # 起始资金 refresh_rate = 10 def initialize(account): # 初始化虚拟账户状态 pass def handle_data(account): # 每个交易日的买入卖出指令 history = account.get_attribute_history('closePrice', 20) momentum = [] holding = account.valid_secpos for stk in history: if stk in account.universe: his = history[stk] change = his[-1] / his[0] momentum.append((stk, change)) momentum = sorted(momentum, key=lambda x: x[1]) momentum = momentum[:10] momentum_list = [i[0] for i in momentum] buy_list = set(momentum_list) - set(holding) sell_list = set(holding) - set(momentum_list) for i in buy_list: try: order_pct_to(i, 0.1) except Exception as e: log.warn(i + str(e)) for i in sell_list: order_to(i, 0) ```  ## Contrarian 策略思路 + Contrarian：股票在经过一段时间的上涨之后会出现回落，一段时间的下跌之后会出现反弹 策略实现 + Contrarian：每次调仓将股票按照前一段时间的累计收益率排序并分组，买入历史累计收益 最低 的那一组 ```py start = datetime(2011, 1, 1) # 回测起始时间 end = datetime(2015, 12, 5) # 回测结束时间 benchmark = 'HS300' # 使用沪深 300 作为参考标准 universe = set_universe('HS300') # 股票池，沪深 300 capital_base = 100000 # 起始资金 refresh_rate = 10 def initialize(account): # 初始化虚拟账户状态 pass def handle_data(account): # 每个交易日的买入卖出指令 history = account.get_attribute_history('closePrice', 20) momentum = [] holding = account.valid_secpos for stk in history: if stk in account.universe: his = history[stk] change = his[-1] / his[0] momentum.append((stk, change)) momentum = sorted(momentum, key=lambda x: x[1], reverse=True) # if momentum[-1][1] < 1: # log.info(holding) # for i in holding: # order_to(i, 0) # # return momentum = momentum[:10] momentum_list = [i[0] for i in momentum] buy_list = set(momentum_list) - set(holding) sell_list = set(holding) - set(momentum_list) for i in buy_list: try: order_pct_to(i, 0.1) except Exception as e: log.warn(i + str(e)) for i in sell_list: order_to(i, 0) ```