选股策略.zip

import numpy as np import pandas as pd start = '2009-01-01' end = '2018-12-31' # 回测结束时间 universe = DynamicUniverse('HS300') + DynamicUniverse('ZZ500') benchmark = 'HS300' # 策略参考标准 freq = 'd' # 策略类型，'d'表示日间策略使用日线回测，'m'表示日内策略使用分钟线回测 refresh_rate = 20 # 调仓频率 accounts = { 'fantasy_account': AccountConfig(account_type='security', capital_base=10000000) } def initialize(context): # 初始化虚拟账户状态 context.signal_generator = SignalGenerator(Signal('ROE'), Signal('PE'), Signal('OperatingRevenueGrowRate'), Signal('PB'),Signal('NPParentCompanyGrowRate'),Signal('CurrentRatio'), Signal('CTOP'),Signal('REVS60'),Signal('REVS20')) def handle_data(context): # 每个交易日的买入卖出指令 account = context.get_account('fantasy_account') current_universe = context.get_universe(exclude_halt=True) yesterday = context.previous_date.strftime('%Y-%m-%d') signals = context.history(current_universe, ['PE', 'ROE', 'OperatingRevenueGrowRate', 'PB', 'NPParentCompanyGrowRate', 'CurrentRatio', 'CTOP', 'REVS60', 'REVS20'], 1, freq='1d', rtype='frame',style='tas')[yesterday] signal1 = standardize((1.0 / winsorize(signals['PE'])).replace([np.inf, -np.inf], 0.0)) signal2 = standardize(winsorize(signals['ROE'].dropna())) signal3 = standardize(winsorize(signals['OperatingRevenueGrowRate'])) signal4 = standardize((1.0 / winsorize(signals['PB'])).replace([np.inf, -np.inf], 0.0)) signal5 = standardize(winsorize(signals['NPParentCompanyGrowRate'])) signal6 = standardize(winsorize(signals['CurrentRatio'].dropna())) signal7 = standardize(winsorize(signals['CTOP'].dropna())) signal8 = -standardize(winsorize(signals['REVS60'])) signal9 = -standardize(winsorize(signals['REVS20'])) signal = (0.2178*signal1).add(0.2149*signal2, fill_value=0.0).add(0.1273*signal3, fill_value=0.0).add(0.1535*signal4, fill_value=0.0).add(0.0328*signal5, fill_value=0.0).add(0.0753*signal6, fill_value=0.0).add(0.1328*signal7, fill_value=0.0).add(0.0218*signal8, fill_value=0.0).add(0.0239*signal9, fill_value=0.0) wts = long_only(signal.to_dict(), select_type=1, top_ratio=0.02, weight_type=1, target_date=yesterday) # 交易部分 positions = account.get_positions() sell_list = [stk for stk in positions if stk not in wts] for stk in sell_list: account.order_to(stk,0) c = account.portfolio_value change = {} for stock, w in wts.iteritems(): p = context.current_price(stock) if not np.isnan(p) and p > 0: if stock in positions: change[stock] = int(c * w / p) - positions[stock].amount else: change[stock] = int(c * w / p) - 0 for stock in sorted(change, key=change.get): account.order(stock, change[stock])