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价值投资+期货对冲V4.0,无惧市场大跌
策略
作者: 水滴
```python # 风险及免责提示：该策略由聚宽用户在聚宽社区分享，仅供学习交流使用。 # 原文一般包含策略说明，如有疑问请到原文和作者交流讨论。 # 原文网址：https://www.joinquant.com/view/community/detail/42256 # 标题：[原创]价值投资+期货对冲V4.0,无惧市场大跌 # 作者：Eddie79163 # 引入库函数 import numpy as np import pandas as pd import datetime as dt from jqdata import * # 导入函数库 #from jqdata import * from jqlib.technical_analysis import * #import pandas as pd from jqfactor import get_factor_values import numpy as np import warnings def initialize(context): # 设置系统 set_option('use_real_price', True) set_option("avoid_future_data", True) g.benchmark = '000905.XSHG' set_benchmark(g.benchmark) # 设置信息格式 log.set_level('order', 'error') pd.set_option('display.max_rows', 100) pd.set_option('display.max_columns', 10) pd.set_option('display.width', 500) #设置初始账户资金分配 g.stock_share = 0.7#指增子账户占总账户资金比例 g.future_share = 0.3#期货子账户占总账户资金比例 g.future_position = 0.35 #期货持仓所需保证金占用的期货子账户资金比例 set_subportfolios([SubPortfolioConfig(cash=context.portfolio.starting_cash * g.stock_share, type='stock'), SubPortfolioConfig(cash=context.portfolio.starting_cash * g.future_share, type='futures')]) # 设置策略 run_daily(handle_trader,time='13:45')# weekday=1,,force=True) #weekday=1, # 设置参数 g.index = '399317.XSHE' #投资指数 g.num = 5 #选股数 g.stocks = [] #股票池 ### 期货相关设定 ###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ g.future_type = 'IC' g.futures_margin_rate = 0.15#保证金比例(现在好像是14%，懒得改了) g.unitprice = 200 g.long_days = 5 # 几日均线以下开空 g.short_days = 2 # 几日以上均线开多 #ATR止损模块参数 g.ATRdays = 20 #计算ATR的时间区间长度 g.boundrydays = 5#计算最高最低价格的区间长度 g.stop = 5 # ATR止损倍数 #根据短期ATR和长期ATR的差确定波动率volatility。如果 短ATR-para*长ATR，表明即将变盘，可适当仓位重 g.shortdays = 20 g.longdays = 50 g.para = 1 # 期货类每笔交易时的手续费是：买入时万分之0.23,卖出时万分之0.23,平今仓为万分之0.23 set_order_cost(OrderCost(open_commission=0.000023, close_commission=0.000023,close_today_commission=0.0023), type='index_futures') # 设定保证金比例 set_option('futures_margin_rate', g.futures_margin_rate) # 设置期货交易的滑点 set_slippage(StepRelatedSlippage(2)) # 设置样本序列长度、模型占位、拟合模型时间间隔、时间计数 g.day = 20#每个月期货到期，20日为一个周期 g.day_count = int(g.day) g.k = 1#初始交易期货手数 ### 期货相关设定 ###~~~~~~~~~~~~~~~~~~~~~ ### 期货交易运行 ###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # 开盘前运行 run_daily( before_market_open_future, time='9:00', reference_security='IF8888.CCFX') # 开盘时运行 #run_daily( market_trade_future, time='11:25', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='9:45', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='10:00', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='10:15', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='10:30', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='10:45', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='11:00', reference_security='IF8888.CCFX') run_daily( market_trade_future, time='11:15', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='13:00', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='13:15', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='13:30', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='13:45', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='14:00', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='14:15', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='14:30', reference_security='IF8888.CCFX') #run_daily( market_trade_future, time='14:45', reference_security='IF8888.CCFX') ### 期货交易运行 ###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ def handle_trader(context): # 按年更新 if context.current_dt.month in [5]: g.stocks = choice_stocks(context, g.index, g.num) # 卖出 cdata = get_current_data() for s in context.portfolio.positions: if s not in g.stocks and not cdata[s].paused: log.info('sell', s, cdata[s].name) order_target(s, 0) # 买进 position = 0.99*context.portfolio.total_value / max(1, len(g.stocks)) for s in g.stocks: if s not in context.portfolio.positions and not cdata[s].paused and\ context.portfolio.available_cash > position: log.info('buy', s, cdata[s].name) order_value(s, position) def choice_stocks(context, index, num): # 股票池 stocks = get_index_stocks(index) #stocks = ['601288.XSHE','601988.XSHE','601328.XSHG','601398.XSHG','601658.XSHG','600016.XSHG','601939.XSHG','601818.XSHG'] # 提取市值，基本面过滤 sdf = get_fundamentals(query( valuation.code, valuation.market_cap, #单位，亿元 ).filter( valuation.code.in_(stocks), valuation.pb_ratio <3, valuation.pb_ratio > 0.0, #indicator.gross_profit_margin>0, #indicator.pcf_ratio >0, indicator.roe>0.1, balance.cash_equivalents>0.4*balance.shortterm_loan, indicator.roa>0.05*indicator.roe, balance.total_assets/balance.total_liability>1, indicator.roa>0, valuation.pe_ratio > 0, valuation.ps_ratio > 0, #valuation.pe_ratio < 30, valuation.pcf_ratio > 0, indicator.inc_revenue_year_on_year >10, indicator.inc_net_profit_to_shareholders_year_on_year >10, #valuation.pb_ratio > 0.15*valuation.pe_ratio,#市净率 )).dropna().set_index('code') stocks = list(sdf.index) #log.info('选股', stocks) # 最近三年的股息 dt_3y = context.current_dt.date() - dt.timedelta(days=3*365) ddf = finance.run_query(query( finance.STK_XR_XD.code, finance.STK_XR_XD.company_name, finance.STK_XR_XD.board_plan_pub_date, finance.STK_XR_XD.bonus_amount_rmb, #单位，万元 ).filter( finance.STK_XR_XD.code.in_(stocks), finance.STK_XR_XD.board_plan_pub_date > dt_3y, finance.STK_XR_XD.bonus_amount_rmb > 0 )).dropna() stocks = list(set(ddf.code)) # 累计分红 divy = pd.Series(data=zeros(len(stocks)), index=stocks) for k in ddf.index: s = ddf.code[k] divy[s] += ddf.bonus_amount_rmb[k] # 建立数据表 sdf = sdf.reindex(stocks) sdf['div_3y'] = divy # 计算股息率 sdf['div_ratio'] = 1e-2 * sdf.div_3y / sdf.market_cap # report sdf['name'] = [get_security_info(s).display_name for s in sdf.index] sdf = sdf.sort_values(by='div_ratio', ascending=False) log.info('\n', sdf[:5]) return list(sdf.head(num).index) # end ''' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 资金划转代码 ''' #对冲比例调整+账户间资金划转 def rebalance(context): # 计算资产总价值 total_value = context.portfolio.total_value # 计算预期的股票账户价值 expected_stock_value = total_value * g.stock_share # 将两个账户的钱调到预期的水平 transfer_cash(1, 0, min(context.subportfolios[1].transferable_cash, max(0, expected_stock_value-context.subportfolios[0].total_value))) transfer_cash(0, 1, min(context.subportfolios[0].transferable_cash, max(0, context.subportfolios[0].total_value-expected_stock_value))) # 计算股票账户价值（预期价值和实际价值其中更小的那个） stock_value = min(context.subportfolios[0].total_value, expected_stock_value) ''' ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ CTA部分代码 ''' ## 开盘前运行函数 def before_market_open_future(context): # 获取当月合约 g.code_1 = get_future_contracts(g.future_type)[0] # 交割日 de_day = get_CCFX_end_date(g.code_1) #判断是否交割日，确定下一月交易的手数 if context.current_dt.date() == de_day: g.de_day = 1 #资产全价值的15%（70%指增，30%的CTA，其中30%的50%为保证金专用） value = int(context.subportfolios[1].total_value) * g.future_position #用于交易头寸的保证金占用 margin = int(get_bars(g.benchmark, 1, '1d', ['close'], end_dt=context.previous_date,include_now=True)['close'][0]) * g.unitprice * g.futures_margin_rate #计算最大持仓手数（保证金15%）最高不超过100手 g.k = min(int(value / margin),100) log.info('手数',g.k) else: g.de_day = 0 # 计数，每g.day天拟合一次 if g.day_count == g.day: g.day_count = 0 else: g.day_count += 1 #开盘时运行交易函数(波动率小开仓开1.2倍，波动率大开仓开0.8倍),外加止损模块 def market_trade_future(context): g.sign = update_niu_signal(context,g.benchmark) g.loss_stop = loss_stop(context,g.benchmark) g.volatility = volatility(context, g.benchmark) #如果波动率小，可以按1.5倍加仓；波动率大就正常 if g.volatility == -1: future_position = int(1.5 *g.k) elif g.volatility == 1: future_position = int(1 *g.k) #开仓信号 if (len(context.subportfolios[1].long_positions) == 0) & (len(context.subportfolios[1].short_positions) == 0): if g.sign > 0: order(g.code_1, future_position, side='long', pindex=1) elif g.sign < 0: order(g.code_1, future_position, side='short', pindex=1) #平仓信号 elif (len(context.subportfolios[1].long_positions) + len(context.subportfolios[1].short_positions)) > 0: if g.de_day == 0: #止损：如果从最大收益处回撤g.stop倍ATR,则止损清仓 if (len(context.subportfolios[1].long_positions) > 0) & (g.loss_stop == 1): order_target(g.code_1, 0, side='long',pindex=1) elif (len(context.subportfolios[1].short_positions) > 0) & (g.loss_stop == 1): order_target(g.code_1, 0, side='short',pindex=1) #平开仓：价格上穿或下穿ema线，调整仓位 elif (len(context.subportfolios[1].long_positions) > 0) & (g.sign == 0): order_target(g.code_1, 0, side='long', pindex=1) order(g.code_1, future_position, side='short', pindex=1) elif (len(context.subportfolios[1].short_positions) > 0) & (g.sign > 0): order_target(g.code_1, 0, side='short', pindex=1) order(g.code_1, future_position, side='long', pindex=1) # 交割日平仓 else: if len(context.subportfolios[1].long_positions) > 0: order_target(g.code_1, 0, side='long', pindex=1) else: order_target(g.code_1, 0, side='short', pindex=1) #ATR波动率信号 def volatility(context,ind): ind=g.benchmark #ATR(security_list, check_date, timeperiod=14) current_ATR_a = ATR(ind,context.current_dt, g.shortdays) current_ATR_b = ATR(ind,context.current_dt, g.longdays) k = current_ATR_a[-1][ind] - g.para * current_ATR_b[-1][ind] if k < 0: volatility = -1 #波动率低，可重仓 elif k > 0: volatility = 1 #波动率高，可轻仓 return volatility #ATR止损信号 def loss_stop(context,ind): include_now = True#表示读取当天的日K线 unit='1d' ind=g.benchmark #ATR(security_list, check_date, timeperiod=14) current_ATR = ATR(ind,context.current_dt, g.ATRdays) close = get_bars(ind, 1, '1d', ['close'], end_dt=context.current_dt,include_now=include_now)['close'] high = max(get_bars(ind, g.boundrydays, unit, ['high'], end_dt=context.previous_date,include_now=include_now)['high'])#5日最高 low = min(get_bars(ind, g.boundrydays, unit, ['low'], end_dt=context.previous_date,include_now=include_now)['low'])#5日最低 if (len(context.portfolio.long_positions) > 0) & (close < high - g.stop * current_ATR[-1][ind]): loss_stop = 1 #多头止损 elif (len(context.portfolio.short_positions) > 0) & (close > low + g.stop * current_ATR[-1][ind]): loss_stop = 1 #空头止损 else: loss_stop = 0 return loss_stop #开平仓信号 def update_niu_signal(context,ind): include_now = True#表示读取当天的日K线 unit='1d' #-------------------标的指数的5日均线，如果均线朝下表示趋势向下，暂停交易--------------- ind=g.benchmark close = get_bars(ind, 1, '1d', ['close'], end_dt=context.current_dt,include_now=include_now)['close'] #当天获取5日均线 current = EMA(ind,context.current_dt, timeperiod=g.long_days, unit = unit, include_now =include_now, fq_ref_date = None)[ind] #前一天的5日均线 previous = EMA(ind,context.previous_date, timeperiod=g.long_days, unit=unit, fq_ref_date = None)[ind] #当天获取2日均线 current_close = EMA(ind,context.current_dt, timeperiod=g.short_days, unit = unit, include_now =include_now, fq_ref_date = None)[ind] #当天获取2日均线 previous_close = EMA(ind,context.previous_date, timeperiod=g.short_days, unit=unit, fq_ref_date = None)[ind] if close<current:#<previous:#当价格低于5日均线且5日均线空头排列的时候开空 niu_signal = -1 #开仓数量=0 elif close>current_close:#>previous_close:#当价格高于5日均线且5日均线多头排列的时候开多 niu_signal = 1 #开仓数量=1 else: niu_signal = 0 return niu_signal # 获取金融期货合约到期日 def get_CCFX_end_date(future_code): # 获取金融期货合约到期日 return get_security_info(future_code).end_date ```
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