指数对冲

利用价值因子选股后，在大盘低于MA30时，卖出一张股指期货作为对冲大盘风险。

import numpy as np
import talib as ta
import pandas as pd
import rqalpha
from rqalpha.api import *
from fxdayu_data import DataAPI
from rqalpha.const import INSTRUMENT_TYPE
def init(context):
    df = DataAPI.candle('000001.XSHE', 'D')
    df['MA_hedge'] = ta.abstract.DEMA(df, 4)
    context.df = df
    codes = pd.read_excel('factor.xlsx')
    context.codes = codes.set_index('date')
def find_pool(context, date):
    codes = context.codes.loc[date]
    stocks = codes.index[codes == 1]
    return stocks
def handle_bar(context, bar_dict):
    hedge(context)
    buy(context, bar_dict)
def buy(context, bar_dict):
    try:
        pool = find_pool(context, context.now)
    except KeyError:
        return
    if pool is not None:
        stocks_len = len(pool)
    for stock in context.portfolio.positions:
        instrument = instruments(stock)
        if instrument.enum_type == INSTRUMENT_TYPE.FUTURE:
            continue
        if stock not in pool:
            order_target_percent(stock, 0)
    result = []
    try:
        for codes in pool:
            data_c = history_bars(codes, 25, '1d', 'close', adjust_type='post')
            ma = ta.MA(data_c, timeperiod=20)
            if len(ma) > 3 and context.df.close.loc[context.now] > context.df.MA_hedge.loc[context.now]:
                if ma[-1] > ma[-2] and ma[-2] > ma[-3] and codes not in result and codes not in context.portfolio.positions:
                    result.append(codes)
    except KeyError:
        return
    if len(result):
        for r in result:
            order_target_percent(r, 1.0 / stocks_len)
def hedge(context):
    for future in get_future_contracts("IF"):
        try:
            sell_qty = context.portfolio.positions[future].sell_quantity
            if context.df.close.loc[context.now] < context.df.MA_hedge.loc[context.now] and sell_qty == 0:
                sell_open(future, 1)
            if context.df.close.loc[context.now] > context.df.MA_hedge.loc[context.now] and sell_qty > 0:
                buy_close(future, 1)
        except KeyError:
            continue
config = {
    "base": {
        "start_date": "2016-08-01",
        "end_date": "2017-08-01",
        "frequency": '1d',
        "accounts": {'stock':1000000, 'future':1000000},
        "benchmark": "000300.XSHG"
    },
    "extra": {
        "log_level": "verbose",
    },
    "mod": {
        "sys_analyser": {
            "enabled": True,
            "plot": True
        }
    }
}
rqalpha.run_func(init=init, handle_bar=handle_bar, config=config)