# 标题：价值投资+期货对冲V4.0,无惧市场大跌
# 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
关键函数解锁后查看：
#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
2025-02-23 