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高频跨期套利策略.md

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Name

高频跨期套利策略

Author

巴啦啦小魔仙

Strategy Description

策略说明

交易标的：比特币（BTC）

价差数据：BTC 永续 - BTC 季度（省略协整性检验）

交易周期：1 分钟

头寸匹配：1:1

交易类型：同品种跨期

做多价差开仓条件：如果当前账户没有持仓，并且价差 < （长期价差水平 - 阈值），就做多价差。即：买开 BTC 永续，卖开 BTC 季度。

做空价差开仓条件：如果当前账户没有持仓，并且价差 > （长期价差水平 + 阈值），就做空价差。即：卖开 BTC 永续，买开 BTC 季度。

做多价差平仓条件：如果当前账户持有 BTC 永续多单，并且持有 BTC 季度空单，并且价差 > 长期价差水平，就平多价差。即：卖平 BTC 永续，买平 BTC 季度。

做空价差平仓条件：如果当前账户持有 BTC 永续空单，并且持有 BTC 季度多单，并且价差 < 长期价差水平，就平空价差。即：买平 BTC 永续，卖平 BTC 季度。

举个例子，假设 BTC 永续 和 BTC 当季的价差长期维持在 35 左右。如果某一天价差达到 50 ，我们预计价差会在未来某段时间回归到 35 及以下。那么就可以卖出 BTC 永续，同时买入 BTC 当季，来做空这个价差。反之亦然，注意 BTC 永续 和 BTC 当季 的价差总会回归到0附近（到期交割），所以价差为正的时候，优先做空价差，价差为负的时候，优先做多价差。

联系方式

👉 如果你对该策略有兴趣，请+V：Irene11229 (点击我的主页，我将会持续更新更多策略，同时还可获得几大头部交易所的市场分析数据)

Source (python)

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import json
import time

from kumex.client import Trade, Market


class Hf(object):

    def __init__(self):
        # read configuration from json file
        with open('config.json', 'r') as file:
            config = json.load(file)

        self.api_key = config['api_key']
        self.api_secret = config['api_secret']
        self.api_passphrase = config['api_passphrase']
        self.sandbox = config['is_sandbox']
        self.symbol_a = config['symbol_a']
        self.symbol_b = config['symbol_b']
        self.spread_mean = float(config['spread_mean'])
        self.leverage = float(config['leverage'])
        self.size = int(config['size'])
        self.num_param = float(config['num_param'])
        self.trade = Trade(self.api_key, self.api_secret, self.api_passphrase, is_sandbox=self.sandbox)
        self.market = Market(self.api_key, self.api_secret, self.api_passphrase, is_sandbox=self.sandbox)

    def get_symbol_price(self, symbol):
        ticker = self.market.get_ticker(symbol)
        return float(ticker['price'])


if __name__ == '__main__':
    hf = Hf()
    while 1:
        # ticker of symbols
        price_af = hf.get_symbol_price(hf.symbol_a)
        price_bf = hf.get_symbol_price(hf.symbol_b)
        # position of symbols
        position_a = hf.trade.get_position_details(hf.symbol_a)
        position_a_qty = int(position_a['currentQty'])
        position_b = hf.trade.get_position_details(hf.symbol_b)
        position_b_qty = int(position_b['currentQty'])
        # interval of price
        new_spread = price_af - price_bf
        print('new_spread =', new_spread)

        if position_a_qty == position_b_qty == 0 and new_spread < (hf.spread_mean - hf.num_param):
            buy_order = hf.trade.create_limit_order(hf.symbol_a, 'buy', hf.leverage, hf.size, price_af + 1)
            print('buy %s,order id =%s' % (hf.symbol_a, buy_order['orderId']))
            sell_order = hf.trade.create_limit_order(hf.symbol_b, 'sell', hf.leverage, hf.size, price_bf - 1)
            print('sell %s,order id =%s' % (hf.symbol_b, sell_order['orderId']))
        elif position_a_qty == position_b_qty == 0 and new_spread > (hf.spread_mean + hf.num_param):
            buy_order = hf.trade.create_limit_order(hf.symbol_a, 'sell', hf.leverage, hf.size, price_af - 1)
            print('sell %s,order id =%s' % (hf.symbol_a, buy_order['orderId']))
            sell_order = hf.trade.create_limit_order(hf.symbol_b, 'buy', hf.leverage, hf.size, price_bf + 1)
            print('buy %s,order id =%s' % (hf.symbol_b, sell_order['orderId']))
        elif position_a_qty > 0 and position_b_qty < 0 and new_spread > hf.spread_mean:
            buy_order = hf.trade.create_limit_order(hf.symbol_a, 'sell', position_a['realLeverage'],
                                                    position_a_qty, price_af + 1)
            print('sell %s,order id =%s' % (hf.symbol_a, buy_order['orderId']))
            sell_order = hf.trade.create_limit_order(hf.symbol_b, 'buy', position_a['realLeverage'],
                                                     position_a_qty, price_bf - 1)
            print('buy %s,order id =%s' % (hf.symbol_b, sell_order['orderId']))
        elif position_a_qty < 0 and position_b_qty > 0 and new_spread < hf.spread_mean:
            buy_order = hf.trade.create_limit_order(hf.symbol_a, 'buy', position_a['realLeverage'],
                                                    position_a_qty, price_af - 1)
            print('buy %s,order id =%s' % (hf.symbol_a, buy_order['orderId']))
            sell_order = hf.trade.create_limit_order(hf.symbol_b, 'sell', position_a['realLeverage'],
                                                     position_a_qty, price_bf + 1)
            print('sell %s,order id =%s' % (hf.symbol_b, sell_order['orderId']))

        time.sleep(60)

Detail

https://www.fmz.com/strategy/207009

Last Modified

2021-03-04 10:13:06