套利分析.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 套利分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import ccxt\n",
    "import urllib.error\n",
    "import requests\n",
    "import asyncio\n",
    "import time\n",
    "import matplotlib.pyplot as plt  \n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "SYMBOL = 'ETH/BTC'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_all_exchange():\n",
    "    return [getattr(ccxt,name)() for name in ccxt.exchanges]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def unzip(l): \n",
    "    return list(zip(*l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_order_books(exchange_list, symbol):\n",
    "    return {exchange.id: exchange.fetch_order_book(symbol) \n",
    "            for exchange in exchange_list}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def process_order_book(order_book):\n",
    "    result = order_book.copy()\n",
    "    result['asks'] = pd.DataFrame(data = {'price':list(unzip(order_book['asks']))[0], \n",
    "                                              'volume': list(unzip(order_book['asks']))[1]})\n",
    "    result['bids'] = pd.DataFrame(data = {'price':list(unzip(order_book['bids']))[0], \n",
    "                                              'volume': list(unzip(order_book['bids']))[1]})\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "orders_list = get_order_books([ccxt.huobipro(), ccxt.okex()], SYMBOL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "orders_hobipro,  orders_okex = (process_order_book(orders_list['huobipro']), \n",
    "                               process_order_book(orders_list['okex']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.080473</td>\n",
       "      <td>2.8372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.080498</td>\n",
       "      <td>7.5100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.080508</td>\n",
       "      <td>0.0935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.080536</td>\n",
       "      <td>0.0187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.080547</td>\n",
       "      <td>8.2700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      price  volume\n",
       "0  0.080473  2.8372\n",
       "1  0.080498  7.5100\n",
       "2  0.080508  0.0935\n",
       "3  0.080536  0.0187\n",
       "4  0.080547  8.2700"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orders_hobipro['asks'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.080430</td>\n",
       "      <td>0.2585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.080429</td>\n",
       "      <td>1.3675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.080427</td>\n",
       "      <td>0.0400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.080413</td>\n",
       "      <td>0.0665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.080412</td>\n",
       "      <td>0.0025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      price  volume\n",
       "0  0.080430  0.2585\n",
       "1  0.080429  1.3675\n",
       "2  0.080427  0.0400\n",
       "3  0.080413  0.0665\n",
       "4  0.080412  0.0025"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orders_hobipro['bids'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 火币网和 OKEX 'ETH/BTC' 的交易盘"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
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12bSR8bKaVDo77rQSAED9xVltBAAAAM2qTaZJmAW342UT6awzbQQAGhzhBQAAQDtqk8qL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\n4w5t3pXQaVc8qvt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AhkZ4AQAAAAAAGhrhBQAAAAAAaGiEFwAAAAAAoKERXgAAAAAAgIZG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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112e95eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 6)) \n",
    "\n",
    "ax = plt.subplot(212, )\n",
    "plt.plot(orders_okex['asks']['price'],orders_okex['asks']['volume'], label = 'ask')  \n",
    "plt.plot(orders_okex['bids']['price'],orders_okex['bids']['volume'], label = 'bid')  \n",
    "#plt.legend()\n",
    "plt.title('Okex')\n",
    "plt.subplot(211,sharex=ax)\n",
    "plt.plot(orders_hobipro['asks']['price'],orders_hobipro['asks']['volume'], label = 'ask')  \n",
    "plt.plot(orders_hobipro['bids']['price'],orders_hobipro['bids']['volume'], label = 'bid')  \n",
    "plt.legend()\n",
    "plt.title('Huobi')\n",
    "plt.tight_layout()\n",
    "plt.show()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算两个交易所之间的价差"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def difference_between_two_exchange(ex1, ex2, symbol,t = 10):\n",
    "    \n",
    "    ex1_bids = []\n",
    "    ex2_bids = []\n",
    "    ex1_asks = []\n",
    "    ex2_asks = []\n",
    "    for i in range(t):\n",
    "        ex1_order_book = ex1.fetch_order_book(symbol)\n",
    "        ex2_order_book = ex2.fetch_order_book(symbol)\n",
    "        ex1_bids.append(ex1_order_book['bids'][0][0])\n",
    "        ex2_bids.append(ex2_order_book['bids'][0][0])\n",
    "        ex1_asks.append(ex1_order_book['asks'][0][0])\n",
    "        ex2_asks.append(ex2_order_book['asks'][0][0])\n",
    "        time.sleep(1)\n",
    "    ex1_bids = np.array(ex1_bids)\n",
    "    ex2_bids = np.array(ex2_bids) \n",
    "    ex1_asks = np.array(ex1_asks) \n",
    "    ex2_asks = np.array(ex2_asks)\n",
    "    \n",
    "    return {'dbids': ex1_bids - ex2_bids,\n",
    "            'dasks': ex1_asks - ex2_asks,\n",
    "            'dbidask':ex1_bids - ex2_asks,\n",
    "            'daskbid':ex1_asks - ex2_bids}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将火币和 OKEX 的 ‘ETH/BTC’ 价格进行比较\n",
    "时间为 10s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "r = difference_between_two_exchange(ccxt.huobipro(), ccxt.okex(), SYMBOL, t = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DlhyitLU5XTyq0NPbCTeH3H1ErhelFMM9h2Nfwp4J+ycweONgfm79M7YWtvma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\nFwVkEREREREXBWQREREREZf/DxaVavWIiy5XAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure object at 0x117caacf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6)) \n",
    "plt.plot(r['dbids'], label = 'dbids')  \n",
    "plt.plot(r['dasks'], label = 'dasks')  \n",
    "plt.plot(r['daskbid'], label = 'daskbid')  \n",
    "plt.plot(r['dbidask'], label = 'dbidask')  \n",
    "plt.legend()\n",
    "plt.title('huobipro & okex')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ##  找到所有交易所中最便宜的卖价 和 最贵的买价\n",
    " 没考虑时延和异步"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def arbitrage(symbol, high_limit=0.2, low_limit=0.001 ):\n",
    "    highest_bid = ('', 0)\n",
    "    lowest_ask = ('', 1000)\n",
    "    for exchange in get_all_exchange():\n",
    "        try:\n",
    "            orders = exchange.fetch_order_book(symbol)\n",
    "            if orders['timestamp'] is None:\n",
    "                continue\n",
    "            e_bid = orders['bids'][0][0]\n",
    "            e_ask = orders['asks'][0][0]\n",
    "            if e_ask > high_limit or e_ask < low_limit:\n",
    "                continue\n",
    "            highest_bid = highest_bid if e_bid < highest_bid[1] else (exchange.id, e_bid)\n",
    "            lowest_ask = lowest_ask if e_ask > lowest_ask[1] else (exchange.id, e_ask)\n",
    "        except ccxt.AuthenticationError:\n",
    "            pass\n",
    "        except ccxt.ExchangeError:\n",
    "            pass\n",
    "        except requests.exceptions.HTTPError:\n",
    "            pass\n",
    "        except:\n",
    "            pass\n",
    "    return highest_bid, lowest_ask, (highest_bid[1]/lowest_ask[1]-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 看一下 ETH 和 BTC 有没有套利空间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(('luno', 0.0812), ('therock', 0.08086231), 0.004176111219182266)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arbitrage(SYMBOL)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 看看其它与比特币有关的交易对有没有套利空间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "BTC_PAIRS = [symbol for symbol in ccxt.okex().loadMarkets().keys() \n",
    "             if symbol.startswith('BTC') or symbol.endswith('BTC')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 这段代码得改成异步的，不然运行时间太长\n",
    "# 得考虑一下查询频率 有些交易所有限制\n",
    "#for symbol in BTC_PAIRS:\n",
    "#    print(symbol)\n",
    "#    print(arbitrage(symbol))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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