IBKR_Implementation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ddf18e09",
   "metadata": {},
   "source": [
    "## Streaming Tick Data"
   ]
  },
  {
   "cell_type": "code",
   "id": "bde78b8f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:19:20.100797Z",
     "start_time": "2024-08-22T06:19:20.095820Z"
    }
   },
   "source": [
    "from ib_insync import *\n",
    "import pandas as pd\n",
    "util.startLoop() \n",
    "ib = IB()"
   ],
   "outputs": [],
   "execution_count": 21
  },
  {
   "cell_type": "code",
   "id": "37bda241",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:19:22.034751Z",
     "start_time": "2024-08-22T06:19:21.560140Z"
    }
   },
   "source": [
    "ib.connect()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IB connected to 127.0.0.1:7497 clientId=1>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 22
  },
  {
   "cell_type": "code",
   "id": "d4d38d92",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:19:24.095270Z",
     "start_time": "2024-08-22T06:19:24.091190Z"
    }
   },
   "source": [
    "contract = Forex('EURUSD')\n",
    "ib.reqMktData(contract)\n",
    "ticker = ib.ticker(contract)"
   ],
   "outputs": [],
   "execution_count": 23
  },
  {
   "cell_type": "code",
   "id": "75c4477b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:19:26.819949Z",
     "start_time": "2024-08-22T06:19:26.815045Z"
    }
   },
   "source": [
    "ticker"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ticker(contract=Forex('EURUSD', exchange='IDEALPRO'), time=datetime.datetime(2024, 8, 22, 6, 19, 26, 484305, tzinfo=datetime.timezone.utc), minTick=1e-05, bid=1.11451, bidSize=2000000.0, ask=1.11453, askSize=12500000.0, prevBid=1.1145, prevBidSize=3000000.0, prevAsk=1.11452, prevAskSize=13500000.0, high=1.11585, low=1.114, close=1.115, halted=0.0, ticks=[TickData(time=datetime.datetime(2024, 8, 22, 6, 19, 26, 484305, tzinfo=datetime.timezone.utc), tickType=3, price=1.11453, size=12500000.0)])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 24
  },
  {
   "cell_type": "code",
   "id": "1dda693a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:19:28.647655Z",
     "start_time": "2024-08-22T06:19:28.644214Z"
    }
   },
   "source": [
    "def onPendingTickers(tickers): # what shall happen after receiving a new tick\n",
    "    print(\"time: {} | Bid: {} | Ask:{}\".format(ticker.time, ticker.bid, ticker.ask), end = '\\r')"
   ],
   "outputs": [],
   "execution_count": 25
  },
  {
   "cell_type": "code",
   "id": "f3700b57",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:19:30.886872Z",
     "start_time": "2024-08-22T06:19:30.882875Z"
    }
   },
   "source": [
    "ib.pendingTickersEvent += onPendingTickers # activate onPendingTickers"
   ],
   "outputs": [],
   "execution_count": 26
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de31ca12",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.pendingTickersEvent -= onPendingTickers # de-activate onPendingTickers"
   ]
  },
  {
   "cell_type": "code",
   "id": "49890b53",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:19:33.012314Z",
     "start_time": "2024-08-22T06:19:33.007500Z"
    }
   },
   "source": [
    "ticker.bid"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.11452"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 27
  },
  {
   "cell_type": "code",
   "id": "529a67c4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:16:41.997665Z",
     "start_time": "2024-08-22T06:16:41.970240Z"
    }
   },
   "source": [
    "ib.cancelMktData(contract)"
   ],
   "outputs": [
    {
     "ename": "ConnectionError",
     "evalue": "Not connected",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mConnectionError\u001B[0m                           Traceback (most recent call last)",
      "Cell \u001B[1;32mIn[10], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m \u001B[43mib\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcancelMktData\u001B[49m\u001B[43m(\u001B[49m\u001B[43mcontract\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[1;32mC:\\code\\trading\\v1\\pythonProject\\.venv\\Lib\\site-packages\\ib_insync\\ib.py:1252\u001B[0m, in \u001B[0;36mIB.cancelMktData\u001B[1;34m(self, contract)\u001B[0m\n\u001B[0;32m   1250\u001B[0m reqId \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mwrapper\u001B[38;5;241m.\u001B[39mendTicker(ticker, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mmktData\u001B[39m\u001B[38;5;124m'\u001B[39m) \u001B[38;5;28;01mif\u001B[39;00m ticker \u001B[38;5;28;01melse\u001B[39;00m \u001B[38;5;241m0\u001B[39m\n\u001B[0;32m   1251\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m reqId:\n\u001B[1;32m-> 1252\u001B[0m     \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mclient\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcancelMktData\u001B[49m\u001B[43m(\u001B[49m\u001B[43mreqId\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m   1253\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m   1254\u001B[0m     \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[0;32m   1255\u001B[0m         \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mcancelMktData: \u001B[39m\u001B[38;5;124m'\u001B[39m \u001B[38;5;124mf\u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mNo reqId found for contract \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mcontract\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m'\u001B[39m)\n",
      "File \u001B[1;32mC:\\code\\trading\\v1\\pythonProject\\.venv\\Lib\\site-packages\\ib_insync\\client.py:408\u001B[0m, in \u001B[0;36mClient.cancelMktData\u001B[1;34m(self, reqId)\u001B[0m\n\u001B[0;32m    407\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mcancelMktData\u001B[39m(\u001B[38;5;28mself\u001B[39m, reqId):\n\u001B[1;32m--> 408\u001B[0m     \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msend\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m2\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m2\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mreqId\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[1;32mC:\\code\\trading\\v1\\pythonProject\\.venv\\Lib\\site-packages\\ib_insync\\client.py:238\u001B[0m, in \u001B[0;36mClient.send\u001B[1;34m(self, makeEmpty, *fields)\u001B[0m\n\u001B[0;32m    236\u001B[0m \u001B[38;5;250m\u001B[39m\u001B[38;5;124;03m\"\"\"Serialize and send the given fields using the IB socket protocol.\"\"\"\u001B[39;00m\n\u001B[0;32m    237\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39misConnected():\n\u001B[1;32m--> 238\u001B[0m     \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mConnectionError\u001B[39;00m(\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mNot connected\u001B[39m\u001B[38;5;124m'\u001B[39m)\n\u001B[0;32m    240\u001B[0m msg \u001B[38;5;241m=\u001B[39m io\u001B[38;5;241m.\u001B[39mStringIO()\n\u001B[0;32m    241\u001B[0m empty \u001B[38;5;241m=\u001B[39m (\u001B[38;5;28;01mNone\u001B[39;00m, UNSET_INTEGER, UNSET_DOUBLE) \u001B[38;5;28;01mif\u001B[39;00m makeEmpty \u001B[38;5;28;01melse\u001B[39;00m (\u001B[38;5;28;01mNone\u001B[39;00m,)\n",
      "\u001B[1;31mConnectionError\u001B[0m: Not connected"
     ]
    }
   ],
   "execution_count": 10
  },
  {
   "cell_type": "code",
   "id": "6ad1f983",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:19:36.967252Z",
     "start_time": "2024-08-22T06:19:36.962723Z"
    }
   },
   "source": [
    "ib.disconnect()"
   ],
   "outputs": [],
   "execution_count": 28
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3fb57d22",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2fc65232",
   "metadata": {},
   "source": [
    "## Streaming Tick Data for multiple Symbols"
   ]
  },
  {
   "cell_type": "code",
   "id": "3a7103f2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:32:15.467936Z",
     "start_time": "2024-08-22T06:32:15.463390Z"
    }
   },
   "source": [
    "from ib_insync import *\n",
    "import pandas as pd\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop() \n",
    "ib = IB()"
   ],
   "outputs": [],
   "execution_count": 59
  },
  {
   "cell_type": "code",
   "id": "92743702",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:32:18.223740Z",
     "start_time": "2024-08-22T06:32:17.736219Z"
    }
   },
   "source": [
    "ib.connect()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IB connected to 127.0.0.1:7497 clientId=1>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 60
  },
  {
   "cell_type": "code",
   "id": "2c1309ef",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:32:20.694638Z",
     "start_time": "2024-08-22T06:32:19.863214Z"
    }
   },
   "source": [
    "contracts = [Forex(pair) for pair in ('EURUSD', 'USDJPY', 'GBPUSD', 'USDCHF', 'USDCAD', 'AUDUSD')]\n",
    "ib.qualifyContracts(*contracts)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Forex('EURUSD', conId=12087792, exchange='IDEALPRO', localSymbol='EUR.USD', tradingClass='EUR.USD'),\n",
       " Forex('USDJPY', conId=15016059, exchange='IDEALPRO', localSymbol='USD.JPY', tradingClass='USD.JPY'),\n",
       " Forex('GBPUSD', conId=12087797, exchange='IDEALPRO', localSymbol='GBP.USD', tradingClass='GBP.USD'),\n",
       " Forex('USDCHF', conId=12087820, exchange='IDEALPRO', localSymbol='USD.CHF', tradingClass='USD.CHF'),\n",
       " Forex('USDCAD', conId=15016062, exchange='IDEALPRO', localSymbol='USD.CAD', tradingClass='USD.CAD'),\n",
       " Forex('AUDUSD', conId=14433401, exchange='IDEALPRO', localSymbol='AUD.USD', tradingClass='AUD.USD')]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 61
  },
  {
   "cell_type": "code",
   "id": "2b4e0c5b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:32:23.087374Z",
     "start_time": "2024-08-22T06:32:23.084374Z"
    }
   },
   "source": [
    "for contract in contracts:\n",
    "    ib.reqMktData(contract)"
   ],
   "outputs": [],
   "execution_count": 62
  },
  {
   "cell_type": "code",
   "id": "fae56e5e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:32:34.243153Z",
     "start_time": "2024-08-22T06:32:34.235617Z"
    }
   },
   "source": [
    "df = pd.DataFrame(\n",
    "    index=[c.pair() for c in contracts],\n",
    "    columns=['bidSize', 'bid', 'ask', 'askSize', 'high', 'low', 'close'])\n",
    "df"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "       bidSize  bid  ask askSize high  low close\n",
       "EURUSD     NaN  NaN  NaN     NaN  NaN  NaN   NaN\n",
       "USDJPY     NaN  NaN  NaN     NaN  NaN  NaN   NaN\n",
       "GBPUSD     NaN  NaN  NaN     NaN  NaN  NaN   NaN\n",
       "USDCHF     NaN  NaN  NaN     NaN  NaN  NaN   NaN\n",
       "USDCAD     NaN  NaN  NaN     NaN  NaN  NaN   NaN\n",
       "AUDUSD     NaN  NaN  NaN     NaN  NaN  NaN   NaN"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bidSize</th>\n",
       "      <th>bid</th>\n",
       "      <th>ask</th>\n",
       "      <th>askSize</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>EURUSD</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USDJPY</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GBPUSD</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USDCHF</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USDCAD</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUDUSD</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 66
  },
  {
   "cell_type": "code",
   "id": "009763c5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:32:29.166946Z",
     "start_time": "2024-08-22T06:32:29.163440Z"
    }
   },
   "source": [
    "def onPendingTickers(tickers): # what shall happen after receiving a new tick\n",
    "    for t in tickers:\n",
    "        df.loc[t.contract.pair()] = (\n",
    "            t.bidSize, t.bid, t.ask, t.askSize, t.high, t.low, t.close)\n",
    "        clear_output(wait=True)\n",
    "    display(df) "
   ],
   "outputs": [],
   "execution_count": 64
  },
  {
   "cell_type": "code",
   "id": "1edb91f7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:32:31.123768Z",
     "start_time": "2024-08-22T06:32:31.120787Z"
    }
   },
   "source": [
    "ib.pendingTickersEvent += onPendingTickers # activate onPendingTickers"
   ],
   "outputs": [],
   "execution_count": 65
  },
  {
   "cell_type": "code",
   "id": "4375f9d8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:17:05.893530Z",
     "start_time": "2024-08-22T06:17:05.889749Z"
    }
   },
   "source": [
    "ib.pendingTickersEvent -= onPendingTickers # de-activate onPendingTickers"
   ],
   "outputs": [],
   "execution_count": 18
  },
  {
   "cell_type": "code",
   "id": "909854de",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:26:24.993068Z",
     "start_time": "2024-08-22T06:26:24.982187Z"
    }
   },
   "source": [
    "for contract in contracts:\n",
    "    ib.cancelMktData(contract)"
   ],
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "cancelMktData: No reqId found for contract Forex('EURUSD', conId=12087792, exchange='IDEALPRO', localSymbol='EUR.USD', tradingClass='EUR.USD')\n",
      "cancelMktData: No reqId found for contract Forex('USDJPY', conId=15016059, exchange='IDEALPRO', localSymbol='USD.JPY', tradingClass='USD.JPY')\n",
      "cancelMktData: No reqId found for contract Forex('GBPUSD', conId=12087797, exchange='IDEALPRO', localSymbol='GBP.USD', tradingClass='GBP.USD')\n",
      "cancelMktData: No reqId found for contract Forex('USDCHF', conId=12087820, exchange='IDEALPRO', localSymbol='USD.CHF', tradingClass='USD.CHF')\n",
      "cancelMktData: No reqId found for contract Forex('USDCAD', conId=15016062, exchange='IDEALPRO', localSymbol='USD.CAD', tradingClass='USD.CAD')\n",
      "cancelMktData: No reqId found for contract Forex('AUDUSD', conId=14433401, exchange='IDEALPRO', localSymbol='AUD.USD', tradingClass='AUD.USD')\n"
     ]
    }
   ],
   "execution_count": 42
  },
  {
   "cell_type": "code",
   "id": "4525eacd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:36:33.625200Z",
     "start_time": "2024-08-22T06:36:33.621193Z"
    }
   },
   "source": [
    "ib.disconnect()"
   ],
   "outputs": [],
   "execution_count": 67
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43302e4f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e6766699",
   "metadata": {},
   "source": [
    "## Streaming Real Time Bars (and Historical)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71a92b8a",
   "metadata": {},
   "source": [
    "- Trading Stratgies use bar data (uniform time periods with ohlc data), not tick data (non-constant frequency, based on trades and quotes)\n",
    "- An SMA Crossover 50/200 (days) Strategy works with daily bars.\n",
    "- Day Trading Strategies are based on e.g. [1min, 5min, 20min, 1h, 3h, 6h] bars\n",
    "- Bar Size / Frequency itself is a Strategy Parameter (to be optimized)"
   ]
  },
  {
   "cell_type": "code",
   "id": "8b95f649",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:30:22.799406Z",
     "start_time": "2024-08-22T06:30:21.622894Z"
    }
   },
   "source": [
    "from ib_insync import *\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop() "
   ],
   "outputs": [],
   "execution_count": 45
  },
  {
   "cell_type": "code",
   "id": "41e4a270",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:30:24.962537Z",
     "start_time": "2024-08-22T06:30:24.358548Z"
    }
   },
   "source": [
    "ib = IB()\n",
    "ib.connect()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IB connected to 127.0.0.1:7497 clientId=1>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 46
  },
  {
   "cell_type": "code",
   "id": "9b9d1c76",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:30:26.798019Z",
     "start_time": "2024-08-22T06:30:26.793490Z"
    }
   },
   "source": [
    "contract = Forex('EURUSD')\n",
    "contract"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Forex('EURUSD', exchange='IDEALPRO')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 47
  },
  {
   "cell_type": "markdown",
   "id": "da9aaccb",
   "metadata": {},
   "source": [
    "__durationStr__: Time span of all the bars. Examples:\n",
    "        __'60 S', '30 D', '13 W', '6 M', '10 Y'__."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a0574a6",
   "metadata": {},
   "source": [
    "__barSizeSetting__: Time period of one bar. Must be one of:\n",
    "        __'1 secs', '5 secs', '10 secs' 15 secs', '30 secs',\n",
    "        '1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',\n",
    "        '20 mins', '30 mins',\n",
    "        '1 hour', '2 hours', '3 hours', '4 hours', '8 hours',\n",
    "        '1 day', '1 week', '1 month'__."
   ]
  },
  {
   "cell_type": "code",
   "id": "f7466dd3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:30:31.547804Z",
     "start_time": "2024-08-22T06:30:29.214406Z"
    }
   },
   "source": [
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='100 S',\n",
    "        barSizeSetting='10 secs',\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)"
   ],
   "outputs": [],
   "execution_count": 48
  },
  {
   "cell_type": "code",
   "id": "4974c543",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:30:33.721144Z",
     "start_time": "2024-08-22T06:30:33.715621Z"
    }
   },
   "source": [
    "bars"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[BarData(date=datetime.datetime(2024, 8, 22, 6, 28, 40, tzinfo=datetime.timezone.utc), open=1.1147, high=1.11475, low=1.1147, close=1.11475, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 28, 50, tzinfo=datetime.timezone.utc), open=1.11475, high=1.1148, low=1.11475, close=1.1148, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 29, tzinfo=datetime.timezone.utc), open=1.1148, high=1.11485, low=1.1148, close=1.11485, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 29, 10, tzinfo=datetime.timezone.utc), open=1.11485, high=1.11485, low=1.11485, close=1.11485, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 29, 20, tzinfo=datetime.timezone.utc), open=1.11485, high=1.1149, low=1.11485, close=1.11485, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 29, 30, tzinfo=datetime.timezone.utc), open=1.11485, high=1.11485, low=1.11485, close=1.11485, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 29, 40, tzinfo=datetime.timezone.utc), open=1.11485, high=1.11485, low=1.11485, close=1.11485, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 29, 50, tzinfo=datetime.timezone.utc), open=1.11485, high=1.1149, low=1.11485, close=1.1149, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 30, tzinfo=datetime.timezone.utc), open=1.1149, high=1.1149, low=1.11485, close=1.11485, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 30, 10, tzinfo=datetime.timezone.utc), open=1.11485, high=1.11485, low=1.11485, close=1.11485, volume=-1.0, average=-1.0, barCount=-1),\n",
       " BarData(date=datetime.datetime(2024, 8, 22, 6, 30, 20, tzinfo=datetime.timezone.utc), open=1.11485, high=1.11485, low=1.11485, close=1.11485, volume=-1.0, average=-1.0, barCount=-1)]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 49
  },
  {
   "cell_type": "code",
   "id": "1c79853d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:31:28.360885Z",
     "start_time": "2024-08-22T06:31:28.350581Z"
    }
   },
   "source": [
    "pd.DataFrame(bars)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                        date     open     high      low    close  volume  \\\n",
       "0  2024-08-22 06:29:45+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "1  2024-08-22 06:29:50+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "2  2024-08-22 06:29:55+00:00  1.11485  1.11490  1.11485  1.11490    -1.0   \n",
       "3  2024-08-22 06:30:00+00:00  1.11490  1.11490  1.11485  1.11485    -1.0   \n",
       "4  2024-08-22 06:30:05+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "5  2024-08-22 06:30:10+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "6  2024-08-22 06:30:15+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "7  2024-08-22 06:30:20+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "8  2024-08-22 06:30:25+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "9  2024-08-22 06:30:30+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "10 2024-08-22 06:30:40+00:00  1.11485  1.11490  1.11485  1.11485    -1.0   \n",
       "11 2024-08-22 06:30:45+00:00  1.11485  1.11490  1.11485  1.11490    -1.0   \n",
       "12 2024-08-22 06:30:50+00:00  1.11490  1.11490  1.11485  1.11485    -1.0   \n",
       "13 2024-08-22 06:30:55+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "14 2024-08-22 06:31:00+00:00  1.11485  1.11490  1.11485  1.11490    -1.0   \n",
       "15 2024-08-22 06:31:05+00:00  1.11490  1.11490  1.11485  1.11485    -1.0   \n",
       "16 2024-08-22 06:31:10+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "17 2024-08-22 06:31:15+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "18 2024-08-22 06:31:20+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "19 2024-08-22 06:31:25+00:00  1.11485  1.11485  1.11485  1.11485    -1.0   \n",
       "\n",
       "    average  barCount  \n",
       "0      -1.0        -1  \n",
       "1      -1.0        -1  \n",
       "2      -1.0        -1  \n",
       "3      -1.0        -1  \n",
       "4      -1.0        -1  \n",
       "5      -1.0        -1  \n",
       "6      -1.0        -1  \n",
       "7      -1.0        -1  \n",
       "8      -1.0        -1  \n",
       "9      -1.0        -1  \n",
       "10     -1.0        -1  \n",
       "11     -1.0        -1  \n",
       "12     -1.0        -1  \n",
       "13     -1.0        -1  \n",
       "14     -1.0        -1  \n",
       "15     -1.0        -1  \n",
       "16     -1.0        -1  \n",
       "17     -1.0        -1  \n",
       "18     -1.0        -1  \n",
       "19     -1.0        -1  "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>average</th>\n",
       "      <th>barCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2024-08-22 06:29:45+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2024-08-22 06:29:50+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2024-08-22 06:29:55+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2024-08-22 06:30:00+00:00</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2024-08-22 06:30:05+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2024-08-22 06:30:10+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2024-08-22 06:30:15+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2024-08-22 06:30:20+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2024-08-22 06:30:25+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2024-08-22 06:30:30+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2024-08-22 06:30:40+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2024-08-22 06:30:45+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2024-08-22 06:30:50+00:00</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2024-08-22 06:30:55+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2024-08-22 06:31:00+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2024-08-22 06:31:05+00:00</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11490</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2024-08-22 06:31:10+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2024-08-22 06:31:15+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2024-08-22 06:31:20+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2024-08-22 06:31:25+00:00</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>1.11485</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 57
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ff6d024",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars) # cancel subscription"
   ]
  },
  {
   "cell_type": "code",
   "id": "8e668cef",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:30:41.377458Z",
     "start_time": "2024-08-22T06:30:41.372951Z"
    }
   },
   "source": [
    "def onBarUpdate(bars, hasNewBar):  # what shall happen after receiving a new bar\n",
    "    df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]]\n",
    "    df.set_index(\"date\", inplace = True)\n",
    "    clear_output(wait=True)\n",
    "    display(df)"
   ],
   "outputs": [],
   "execution_count": 51
  },
  {
   "cell_type": "code",
   "id": "cae32efd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:30:45.495936Z",
     "start_time": "2024-08-22T06:30:44.607215Z"
    }
   },
   "source": [
    "# start stream\n",
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='50 S',\n",
    "        barSizeSetting='5 secs',\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)"
   ],
   "outputs": [],
   "execution_count": 52
  },
  {
   "cell_type": "code",
   "id": "48c10737",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-22T06:30:50.709601Z",
     "start_time": "2024-08-22T06:30:50.706208Z"
    }
   },
   "source": [
    "bars.updateEvent += onBarUpdate # activate onBarUpdate"
   ],
   "outputs": [],
   "execution_count": 53
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a7e90440",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars.updateEvent -= onBarUpdate # de-activate onBarUpdate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d416f8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars) # cancel subscription"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f4d2e045",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "acdfb0ed",
   "metadata": {},
   "source": [
    "## Application: Creating a live Candle Stick Chart "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa74a57a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar):\n",
    "    plt.close()\n",
    "    plot = util.barplot(bars, title = \"EURUSD\", upColor = \"green\", downColor = \"red\")\n",
    "    clear_output(wait=True)\n",
    "    display(plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43d30ff7",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1000 S',\n",
    "        barSizeSetting='10 secs',\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c849440",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars.updateEvent += onBarUpdate # activate onBarUpdate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3fb8301",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars.updateEvent -= onBarUpdate # de-activate onBarUpdate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "356517b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars) # cancel subscription"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e92e6a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.disconnect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6336a401",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8ce61d6b",
   "metadata": {},
   "source": [
    "## Preparing the Data for Day Trading"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3f4318a",
   "metadata": {},
   "source": [
    "- Problem: most recent bar is (typically) incomplete (until the end of the bar has been reached)\n",
    "- In Trading: Take actions once a new bar is complete "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c829ac67",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ib_insync import * \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac9f9b38",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib = IB()\n",
    "ib.connect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c59de438",
   "metadata": {},
   "outputs": [],
   "source": [
    "contract = Forex('EURUSD')\n",
    "contract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "492e08b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar):\n",
    "    print(dt.datetime.utcnow())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47f34569",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D',\n",
    "        barSizeSetting='1 min',\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "299e74d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars.updateEvent += onBarUpdate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "57befe9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3182e29b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar): \n",
    "    global df\n",
    "    df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]].iloc[:-1] # remove current bar (incomplete)\n",
    "    df.set_index(\"date\", inplace = True)\n",
    "    clear_output(wait=True)\n",
    "    display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7ceff64",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D',\n",
    "        barSizeSetting='1 min',\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)\n",
    "bars.updateEvent += onBarUpdate "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20e954f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ef78943",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "bd123446",
   "metadata": {},
   "source": [
    "## Improving Code Efficiency"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "618049f4",
   "metadata": {},
   "source": [
    "Idea: We need to run major parts of onBarUpdate only if a bar is complete (== new bar has been added)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "99a0f060",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9777cfb4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# check if current (incomplete) bar is more recent than the last complete bar\n",
    "bars[-1].date > bars[-2].date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac98470f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar):  \n",
    "    global df, last_bar\n",
    "    if bars[-1].date > last_bar: # if bar completed / new bar\n",
    "        last_bar = bars[-1].date\n",
    "    \n",
    "        df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]].iloc[:-1] \n",
    "        df.set_index(\"date\", inplace = True)\n",
    "        clear_output(wait=True)\n",
    "        display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c38d1167",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D',\n",
    "        barSizeSetting='1 min',\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)\n",
    "last_bar = bars[-1].date # initialize last_bar\n",
    "bars.updateEvent += onBarUpdate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "106aa277",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "382beb6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.disconnect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "053dab79",
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c38043b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "last_bar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d77a077c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "751de213",
   "metadata": {},
   "source": [
    "## Define an SMA Day Trading Strategy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b559ba5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ib_insync import * \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b99a3bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib = IB()\n",
    "ib.connect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88415e43",
   "metadata": {},
   "outputs": [],
   "source": [
    "contract = Forex('EURUSD')\n",
    "contract"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9b84a39",
   "metadata": {},
   "source": [
    "Strategy: SMA 50/200 (minutes) Crossover (needs to be backtested!!!)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6c29ce1",
   "metadata": {},
   "outputs": [],
   "source": [
    "sma_s = 50\n",
    "sma_l = 200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d564884",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar): \n",
    "    global df, last_bar\n",
    "    \n",
    "    if bars[-1].date > last_bar: \n",
    "        last_bar = bars[-1].date\n",
    "    \n",
    "        # Data Processing\n",
    "        df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]].iloc[:-1]\n",
    "        df.set_index(\"date\", inplace = True)\n",
    "        \n",
    "        ####################### Trading Strategy ###########################\n",
    "        df = df[[\"close\"]].copy()\n",
    "        df[\"sma_s\"] = df.close.rolling(sma_s).mean()\n",
    "        df[\"sma_l\"] = df.close.rolling(sma_l).mean()\n",
    "        df.dropna(inplace = True)\n",
    "        df[\"position\"] = np.where(df[\"sma_s\"] > df[\"sma_l\"], 1, -1 )\n",
    "        ####################################################################\n",
    "        \n",
    "        # Action\n",
    "        clear_output(wait=True)\n",
    "        display(df)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6077da72",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D',\n",
    "        barSizeSetting='1 min',\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)\n",
    "last_bar = bars[-1].date\n",
    "bars.updateEvent += onBarUpdate "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29017466",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5a8f72fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.disconnect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98b8ed79",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "67330e78",
   "metadata": {},
   "source": [
    "## Trading"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54b121fd",
   "metadata": {},
   "source": [
    "__Please run the following code only with your Paper Trading Account!!!__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c3d17f0",
   "metadata": {},
   "source": [
    "__Check the Regular Trading Hours!!!__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc543c96",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ib_insync import * \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc405333",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib = IB()\n",
    "ib.connect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "58cab0a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# strategy parameters\n",
    "sma_s = 50\n",
    "sma_l = 200\n",
    "freq = \"1 min\"\n",
    "units = 1000\n",
    "contract = Forex('EURUSD') # for data streaming\n",
    "ib.qualifyContracts(contract)\n",
    "cfd = CFD(\"EUR\", currency = \"USD\") # for trading\n",
    "ib.qualifyContracts(cfd)\n",
    "conID = cfd.conId"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bda6da5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "conID"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c18c259",
   "metadata": {},
   "source": [
    "__barSizeSetting__: Time period of one bar. Must be one of:\n",
    "        __'1 secs', '5 secs', '10 secs' 15 secs', '30 secs',\n",
    "        '1 min', '2 mins', '3 mins', '5 mins', '10 mins', '15 mins',\n",
    "        '20 mins', '30 mins',\n",
    "        '1 hour', '2 hours', '3 hours', '4 hours', '8 hours',\n",
    "        '1 day', '1 week', '1 month'__."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "238ec94d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar):  \n",
    "    global df, last_bar\n",
    "    \n",
    "    if bars[-1].date > last_bar: \n",
    "        last_bar = bars[-1].date\n",
    "    \n",
    "        # Data Processing\n",
    "        df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]].iloc[:-1] \n",
    "        df.set_index(\"date\", inplace = True)\n",
    "        \n",
    "        ####################### Trading Strategy ###########################\n",
    "        df = df[[\"close\"]].copy()\n",
    "        df[\"sma_s\"] = df.close.rolling(sma_s).mean()\n",
    "        df[\"sma_l\"] = df.close.rolling(sma_l).mean()\n",
    "        df.dropna(inplace = True)\n",
    "        df[\"position\"] = np.where(df[\"sma_s\"] > df[\"sma_l\"], 1, -1 )\n",
    "        ####################################################################\n",
    "        \n",
    "        # Trading\n",
    "        target = df[\"position\"][-1] * units\n",
    "        execute_trade(target = target)\n",
    "        \n",
    "        # Display\n",
    "        clear_output(wait=True)\n",
    "        display(df)\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "def execute_trade(target):\n",
    "    global current_pos\n",
    "    \n",
    "    # 1. get current Position\n",
    "    try:\n",
    "        current_pos = [pos.position for pos in ib.positions() if pos.contract.conId == conID][0]\n",
    "    except:\n",
    "        current_pos = 0\n",
    "         \n",
    "    # 2. identify required trades\n",
    "    trades = target - current_pos\n",
    "        \n",
    "    # 3. trade execution\n",
    "    if trades > 0:\n",
    "        side = \"BUY\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)  \n",
    "    elif trades < 0:\n",
    "        side = \"SELL\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)\n",
    "    else:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5285dd5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D', # must be sufficiently long!!! (200 * 1 min)\n",
    "        barSizeSetting=freq,\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)\n",
    "last_bar = bars[-1].date\n",
    "bars.updateEvent += onBarUpdate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c6b2059",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "112f01d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb0a88d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.disconnect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "93dcfefe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a91b9644",
   "metadata": {},
   "source": [
    "## Trade Reporting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80e0e12b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ib_insync import * \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d2a0a2c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib = IB()\n",
    "ib.connect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee4b2599",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.fills()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb5d1924",
   "metadata": {},
   "outputs": [],
   "source": [
    "util.df([fs.execution for fs in ib.fills()])[[\"execId\", \"time\", \"side\", \"cumQty\", \"avgPrice\"]].set_index(\"execId\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e076ba5",
   "metadata": {},
   "outputs": [],
   "source": [
    "util.df([fs.commissionReport for fs in ib.fills()])[[\"execId\", \"realizedPNL\"]].set_index(\"execId\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a4cf5a6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# strategy parameters\n",
    "sma_s = 2\n",
    "sma_l = 5\n",
    "freq = \"1 min\"\n",
    "units = 1000\n",
    "contract = Forex('EURUSD') \n",
    "ib.qualifyContracts(contract)\n",
    "cfd = CFD(\"EUR\", currency = \"USD\")\n",
    "ib.qualifyContracts(cfd)\n",
    "conID = cfd.conId"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f800229",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar):  \n",
    "    global df, last_bar\n",
    "    \n",
    "    if bars[-1].date > last_bar: \n",
    "        last_bar = bars[-1].date\n",
    "    \n",
    "        # Data Processing\n",
    "        df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]].iloc[:-1] \n",
    "        df.set_index(\"date\", inplace = True)\n",
    "        \n",
    "        ####################### Trading Strategy ###########################\n",
    "        df = df[[\"close\"]].copy()\n",
    "        df[\"sma_s\"] = df.close.rolling(sma_s).mean()\n",
    "        df[\"sma_l\"] = df.close.rolling(sma_l).mean()\n",
    "        df.dropna(inplace = True)\n",
    "        df[\"position\"] = np.where(df[\"sma_s\"] > df[\"sma_l\"], 1, -1 )\n",
    "        ####################################################################\n",
    "        \n",
    "        # Trading\n",
    "        target = df[\"position\"][-1] * units\n",
    "        execute_trade(target = target)\n",
    "        \n",
    "        # Display\n",
    "        clear_output(wait=True)\n",
    "        display(df)\n",
    "    else:\n",
    "        try:\n",
    "            trade_reporting()\n",
    "        except:\n",
    "            pass\n",
    "\n",
    "def execute_trade(target):\n",
    "    global current_pos\n",
    "    \n",
    "    # 1. get current Position\n",
    "    try:\n",
    "        current_pos = [pos.position for pos in ib.positions() if pos.contract.conId == conID][0]\n",
    "    except:\n",
    "        current_pos = 0\n",
    "         \n",
    "    # 2. identify required trades\n",
    "    trades = target - current_pos\n",
    "        \n",
    "    # 3. trade execution\n",
    "    if trades > 0:\n",
    "        side = \"BUY\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)  \n",
    "    elif trades < 0:\n",
    "        side = \"SELL\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "def trade_reporting():\n",
    "    global report\n",
    "    \n",
    "    fill_df = util.df([fs.execution for fs in ib.fills()])[[\"execId\", \"time\", \"side\", \"cumQty\", \"avgPrice\"]].set_index(\"execId\")\n",
    "    profit_df = util.df([fs.commissionReport for fs in ib.fills()])[[\"execId\", \"realizedPNL\"]].set_index(\"execId\")\n",
    "    report = pd.concat([fill_df, profit_df], axis = 1).set_index(\"time\").loc[session_start:]\n",
    "    report = report.groupby(\"time\").agg({\"side\":\"first\", \"cumQty\":\"max\", \"avgPrice\":\"mean\", \"realizedPNL\":\"sum\"})\n",
    "    report[\"cumPNL\"] = report.realizedPNL.cumsum()\n",
    "        \n",
    "    clear_output(wait=True)\n",
    "    display(df, report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a624a53",
   "metadata": {},
   "outputs": [],
   "source": [
    "session_start = pd.to_datetime(dt.datetime.utcnow()).tz_localize(\"utc\")\n",
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D',\n",
    "        barSizeSetting=freq,\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)\n",
    "last_bar = bars[-1].date\n",
    "bars.updateEvent += onBarUpdate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "317e0639",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.cancelHistoricalData(bars) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c7641a58",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib.disconnect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "881020a9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "279ce160",
   "metadata": {},
   "source": [
    "## Stop the Trading Session"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "608c22a7",
   "metadata": {},
   "source": [
    "Potential Triggers:\n",
    "- stop at a certain time (e.g. 21:59 UTC time)\n",
    "- stop once a certain profit/loss limit has been reached\n",
    "- etc."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "834a81fb",
   "metadata": {},
   "source": [
    "Required Actions:\n",
    "- Stop Stream/Session\n",
    "- Close Open Position (go neutral)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "797e866a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ib_insync import * \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7d265a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib = IB()\n",
    "ib.connect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2865a698",
   "metadata": {},
   "outputs": [],
   "source": [
    "# strategy parameters\n",
    "sma_s = 2\n",
    "sma_l = 5\n",
    "freq = \"1 min\"\n",
    "units = 1000\n",
    "end_time = dt.time(21, 59, 0) # stop condition\n",
    "contract = Forex('EURUSD') \n",
    "ib.qualifyContracts(contract)\n",
    "cfd = CFD(\"EUR\", currency = \"USD\")\n",
    "ib.qualifyContracts(cfd)\n",
    "conID = cfd.conId"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "747e2f6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "dt.datetime.utcnow().time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d99d25d",
   "metadata": {},
   "outputs": [],
   "source": [
    "dt.datetime.utcnow().time() >= end_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2c18795b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar):  \n",
    "    global df, last_bar\n",
    "    \n",
    "    if bars[-1].date > last_bar: \n",
    "        last_bar = bars[-1].date\n",
    "    \n",
    "        # Data Processing\n",
    "        df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]].iloc[:-1] \n",
    "        df.set_index(\"date\", inplace = True)\n",
    "        \n",
    "        ####################### Trading Strategy ###########################\n",
    "        df = df[[\"close\"]].copy()\n",
    "        df[\"sma_s\"] = df.close.rolling(sma_s).mean()\n",
    "        df[\"sma_l\"] = df.close.rolling(sma_l).mean()\n",
    "        df.dropna(inplace = True)\n",
    "        df[\"position\"] = np.where(df[\"sma_s\"] > df[\"sma_l\"], 1, -1 )\n",
    "        ####################################################################\n",
    "        \n",
    "        # Trading\n",
    "        target = df[\"position\"][-1] * units\n",
    "        execute_trade(target = target)\n",
    "        \n",
    "        # Display\n",
    "        clear_output(wait=True)\n",
    "        display(df)\n",
    "    else:\n",
    "        try:\n",
    "            trade_reporting()\n",
    "        except:\n",
    "            pass\n",
    "\n",
    "def execute_trade(target):\n",
    "    global current_pos\n",
    "    \n",
    "    # 1. get current Position\n",
    "    try:\n",
    "        current_pos = [pos.position for pos in ib.positions() if pos.contract.conId == conID][0]\n",
    "    except:\n",
    "        current_pos = 0\n",
    "         \n",
    "    # 2. identify required trades\n",
    "    trades = target - current_pos\n",
    "        \n",
    "    # 3. trade execution\n",
    "    if trades > 0:\n",
    "        side = \"BUY\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)  \n",
    "    elif trades < 0:\n",
    "        side = \"SELL\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "def trade_reporting():\n",
    "    global report\n",
    "    \n",
    "    fill_df = util.df([fs.execution for fs in ib.fills()])[[\"execId\", \"time\", \"side\", \"cumQty\", \"avgPrice\"]].set_index(\"execId\")\n",
    "    profit_df = util.df([fs.commissionReport for fs in ib.fills()])[[\"execId\", \"realizedPNL\"]].set_index(\"execId\")\n",
    "    report = pd.concat([fill_df, profit_df], axis = 1).set_index(\"time\").loc[session_start:]\n",
    "    report = report.groupby(\"time\").agg({\"side\":\"first\", \"cumQty\":\"max\", \"avgPrice\":\"mean\", \"realizedPNL\":\"sum\"})\n",
    "    report[\"cumPNL\"] = report.realizedPNL.cumsum()\n",
    "        \n",
    "    clear_output(wait=True)\n",
    "    display(df, report)\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7e6a365",
   "metadata": {},
   "outputs": [],
   "source": [
    "# start trading session\n",
    "session_start = pd.to_datetime(dt.datetime.utcnow()).tz_localize(\"utc\")\n",
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D',\n",
    "        barSizeSetting=freq,\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)\n",
    "last_bar = bars[-1].date\n",
    "bars.updateEvent += onBarUpdate\n",
    "\n",
    "# stop trading session\n",
    "while True:\n",
    "    ib.sleep(5) # check every 5 seconds\n",
    "    if dt.datetime.utcnow().time() >= end_time: # if stop conditions has been met\n",
    "        execute_trade(target = 0) # close open position \n",
    "        ib.cancelHistoricalData(bars) # stop stream\n",
    "        ib.sleep(10)\n",
    "        try:\n",
    "            trade_reporting() # final reporting\n",
    "        except:\n",
    "            pass\n",
    "        print(\"Session Stopped.\")\n",
    "        ib.disconnect()\n",
    "        break\n",
    "    else:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bbb82d3d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "16a02a34",
   "metadata": {},
   "source": [
    "## Trading other Strategies - Coding Challenge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ece36f56",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ib_insync import * \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d67af75f",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib = IB()\n",
    "ib.connect()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67b877d5",
   "metadata": {},
   "source": [
    "__Strategy 1__: Simple Contrarian Strategy (1min / window = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1402c00",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "baa4a4a9",
   "metadata": {},
   "source": [
    "## Stop here if you don´t want to see the solution!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74f8c4f9",
   "metadata": {},
   "source": [
    "###############################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0124bd81",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "890541cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# strategy parameters\n",
    "freq = \"1 min\"\n",
    "window = 1\n",
    "units = 1000\n",
    "end_time = dt.time(21, 59, 0) # stop condition\n",
    "contract = Forex('EURUSD') \n",
    "ib.qualifyContracts(contract)\n",
    "cfd = CFD(\"EUR\", currency = \"USD\")\n",
    "ib.qualifyContracts(cfd)\n",
    "conID = cfd.conId"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1ef525b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar):  \n",
    "    global df, last_bar\n",
    "    \n",
    "    if bars[-1].date > last_bar: \n",
    "        last_bar = bars[-1].date\n",
    "    \n",
    "        # Data Processing\n",
    "        df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]].iloc[:-1] \n",
    "        df.set_index(\"date\", inplace = True)\n",
    "        \n",
    "        ####################### Trading Strategy ###########################\n",
    "        df = df[[\"close\"]].copy()\n",
    "        df[\"returns\"] = np.log(df[\"close\"] / df[\"close\"].shift())\n",
    "        df[\"position\"] = -np.sign(df.returns.rolling(window).mean())\n",
    "        ####################################################################\n",
    "        \n",
    "        # Trading\n",
    "        target = df[\"position\"][-1] * units\n",
    "        execute_trade(target = target)\n",
    "        \n",
    "        # Display\n",
    "        clear_output(wait=True)\n",
    "        display(df)\n",
    "    else:\n",
    "        try:\n",
    "            trade_reporting()\n",
    "        except:\n",
    "            pass\n",
    "\n",
    "def execute_trade(target):\n",
    "    global current_pos\n",
    "    \n",
    "    # 1. get current Position\n",
    "    try:\n",
    "        current_pos = [pos.position for pos in ib.positions() if pos.contract.conId == conID][0]\n",
    "    except:\n",
    "        current_pos = 0\n",
    "         \n",
    "    # 2. identify required trades\n",
    "    trades = target - current_pos\n",
    "        \n",
    "    # 3. trade execution\n",
    "    if trades > 0:\n",
    "        side = \"BUY\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)  \n",
    "    elif trades < 0:\n",
    "        side = \"SELL\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "def trade_reporting():\n",
    "    global report\n",
    "    \n",
    "    fill_df = util.df([fs.execution for fs in ib.fills()])[[\"execId\", \"time\", \"side\", \"cumQty\", \"avgPrice\"]].set_index(\"execId\")\n",
    "    profit_df = util.df([fs.commissionReport for fs in ib.fills()])[[\"execId\", \"realizedPNL\"]].set_index(\"execId\")\n",
    "    report = pd.concat([fill_df, profit_df], axis = 1).set_index(\"time\").loc[session_start:]\n",
    "    report = report.groupby(\"time\").agg({\"side\":\"first\", \"cumQty\":\"max\", \"avgPrice\":\"mean\", \"realizedPNL\":\"sum\"})\n",
    "    report[\"cumPNL\"] = report.realizedPNL.cumsum()\n",
    "        \n",
    "    clear_output(wait=True)\n",
    "    display(df, report)\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dcab5fe7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# start trading session\n",
    "session_start = pd.to_datetime(dt.datetime.utcnow()).tz_localize(\"utc\")\n",
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D',\n",
    "        barSizeSetting=freq,\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)\n",
    "last_bar = bars[-1].date\n",
    "bars.updateEvent += onBarUpdate\n",
    "\n",
    "# stop trading session\n",
    "while True:\n",
    "    ib.sleep(5) # check every 5 seconds\n",
    "    if dt.datetime.utcnow().time() >= end_time: # if stop conditions has been met\n",
    "        execute_trade(target = 0) # close open position \n",
    "        ib.cancelHistoricalData(bars) # stop stream\n",
    "        ib.sleep(10)\n",
    "        try:\n",
    "            trade_reporting() # final reporting\n",
    "        except:\n",
    "            pass\n",
    "        print(\"Session Stopped.\")\n",
    "        ib.disconnect()\n",
    "        break\n",
    "    else:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb62b3e4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "de5186e0",
   "metadata": {},
   "source": [
    "__Strategy 2__: Bollinger Bands SMA 20 (minutes) / 1 Standard Deviation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9ac16e97",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "df06cc64",
   "metadata": {},
   "source": [
    "## Stop here if you don´t want to see the solution!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0ea3b5f",
   "metadata": {},
   "source": [
    "###############################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d402f250",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c6f0b00",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ib_insync import * \n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "from IPython.display import display, clear_output\n",
    "util.startLoop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0eacaab3",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib = IB()\n",
    "ib.connect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f3ce757",
   "metadata": {},
   "outputs": [],
   "source": [
    "# strategy parameters\n",
    "freq = \"1 min\"\n",
    "sma = 20\n",
    "dev = 1\n",
    "units = 1000\n",
    "end_time = dt.time(13, 35, 0) # stop condition\n",
    "contract = Forex('EURUSD') \n",
    "ib.qualifyContracts(contract)\n",
    "cfd = CFD(\"EUR\", currency = \"USD\")\n",
    "ib.qualifyContracts(cfd)\n",
    "conID = cfd.conId"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ce0ffcf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def onBarUpdate(bars, hasNewBar):  \n",
    "    global df, last_bar\n",
    "    \n",
    "    if bars[-1].date > last_bar: \n",
    "        last_bar = bars[-1].date\n",
    "    \n",
    "        # Data Processing\n",
    "        df = pd.DataFrame(bars)[[\"date\", \"open\", \"high\", \"low\", \"close\"]].iloc[:-1] \n",
    "        df.set_index(\"date\", inplace = True)\n",
    "        \n",
    "        ####################### Trading Strategy ###########################\n",
    "        df = df[[\"close\"]].copy()\n",
    "        df[\"SMA\"] = df[\"close\"].rolling(sma).mean()\n",
    "        df[\"Lower\"] = df[\"SMA\"] - df[\"close\"].rolling(sma).std() * dev\n",
    "        df[\"Upper\"] = df[\"SMA\"] + df[\"close\"].rolling(sma).std() * dev\n",
    "        df[\"distance\"] = df[\"close\"] - df.SMA\n",
    "        df[\"position\"] = np.where(df[\"close\"] < df.Lower, 1, np.nan)\n",
    "        df[\"position\"] = np.where(df[\"close\"] > df.Upper, -1, df[\"position\"])\n",
    "        df[\"position\"] = np.where(df.distance * df.distance.shift(1) < 0, 0, df[\"position\"])\n",
    "        df[\"position\"] = df.position.ffill().fillna(0)\n",
    "        ####################################################################\n",
    "        \n",
    "        # Trading\n",
    "        target = df[\"position\"][-1] * units\n",
    "        execute_trade(target = target)\n",
    "        \n",
    "        # Display\n",
    "        clear_output(wait=True)\n",
    "        display(df)\n",
    "    else:\n",
    "        try:\n",
    "            trade_reporting()\n",
    "        except:\n",
    "            pass\n",
    "\n",
    "def execute_trade(target):\n",
    "    global current_pos\n",
    "    \n",
    "    # 1. get current Position\n",
    "    try:\n",
    "        current_pos = [pos.position for pos in ib.positions() if pos.contract.conId == conID][0]\n",
    "    except:\n",
    "        current_pos = 0\n",
    "         \n",
    "    # 2. identify required trades\n",
    "    trades = target - current_pos\n",
    "        \n",
    "    # 3. trade execution\n",
    "    if trades > 0:\n",
    "        side = \"BUY\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)  \n",
    "    elif trades < 0:\n",
    "        side = \"SELL\"\n",
    "        order = MarketOrder(side, abs(trades))\n",
    "        trade = ib.placeOrder(cfd, order)\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "def trade_reporting():\n",
    "    global report\n",
    "    \n",
    "    fill_df = util.df([fs.execution for fs in ib.fills()])[[\"execId\", \"time\", \"side\", \"cumQty\", \"avgPrice\"]].set_index(\"execId\")\n",
    "    profit_df = util.df([fs.commissionReport for fs in ib.fills()])[[\"execId\", \"realizedPNL\"]].set_index(\"execId\")\n",
    "    report = pd.concat([fill_df, profit_df], axis = 1).set_index(\"time\").loc[session_start:]\n",
    "    report = report.groupby(\"time\").agg({\"side\":\"first\", \"cumQty\":\"max\", \"avgPrice\":\"mean\", \"realizedPNL\":\"sum\"})\n",
    "    report[\"cumPNL\"] = report.realizedPNL.cumsum()\n",
    "        \n",
    "    clear_output(wait=True)\n",
    "    display(df, report)\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38b2681f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# start trading session\n",
    "session_start = pd.to_datetime(dt.datetime.utcnow()).tz_localize(\"utc\")\n",
    "bars = ib.reqHistoricalData(\n",
    "        contract,\n",
    "        endDateTime='',\n",
    "        durationStr='1 D',\n",
    "        barSizeSetting=freq,\n",
    "        whatToShow='MIDPOINT',\n",
    "        useRTH=True,\n",
    "        formatDate=2,\n",
    "        keepUpToDate=True)\n",
    "last_bar = bars[-1].date\n",
    "bars.updateEvent += onBarUpdate\n",
    "\n",
    "# stop trading session\n",
    "while True:\n",
    "    ib.sleep(5) # check every 5 seconds\n",
    "    if dt.datetime.utcnow().time() >= end_time: # if stop conditions has been met\n",
    "        execute_trade(target = 0) # close open position \n",
    "        ib.cancelHistoricalData(bars) # stop stream\n",
    "        ib.sleep(10)\n",
    "        try:\n",
    "            trade_reporting() # final reporting\n",
    "        except:\n",
    "            pass\n",
    "        print(\"Session Stopped.\")\n",
    "        ib.disconnect()\n",
    "        break\n",
    "    else:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b269846d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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