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maurobaraldi/TradingBotOanda.ipynb

Created November 20, 2023 19:47
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Trading bot for Oanda platform
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TradingBotOanda.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1 - Import test data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[*********************100%***********************] 1 of 1 completed\n"
]
},
{
"data": {
"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>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Adj Close</th>\n",
" <th>Volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2022-10-07 00:00:00</th>\n",
" <td>0.979624</td>\n",
" <td>0.979624</td>\n",
" <td>0.979144</td>\n",
" <td>0.979240</td>\n",
" <td>0.979240</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-10-07 00:15:00</th>\n",
" <td>0.979336</td>\n",
" <td>0.979912</td>\n",
" <td>0.979240</td>\n",
" <td>0.979912</td>\n",
" <td>0.979912</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-10-07 00:30:00</th>\n",
" <td>0.979912</td>\n",
" <td>0.980104</td>\n",
" <td>0.979528</td>\n",
" <td>0.979528</td>\n",
" <td>0.979528</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-10-07 00:45:00</th>\n",
" <td>0.979528</td>\n",
" <td>0.979528</td>\n",
" <td>0.978953</td>\n",
" <td>0.979144</td>\n",
" <td>0.979144</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-10-07 01:00:00</th>\n",
" <td>0.979528</td>\n",
" <td>0.979720</td>\n",
" <td>0.978953</td>\n",
" <td>0.979048</td>\n",
" <td>0.979048</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-12-02 21:15:00</th>\n",
" <td>1.054074</td>\n",
" <td>1.054407</td>\n",
" <td>1.053963</td>\n",
" <td>1.054407</td>\n",
" <td>1.054407</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-12-02 21:30:00</th>\n",
" <td>1.054407</td>\n",
" <td>1.054407</td>\n",
" <td>1.053963</td>\n",
" <td>1.054074</td>\n",
" <td>1.054074</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-12-02 21:45:00</th>\n",
" <td>1.053963</td>\n",
" <td>1.054519</td>\n",
" <td>1.053963</td>\n",
" <td>1.054407</td>\n",
" <td>1.054407</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-12-02 22:00:00</th>\n",
" <td>1.053075</td>\n",
" <td>1.053075</td>\n",
" <td>1.053075</td>\n",
" <td>1.053075</td>\n",
" <td>1.053075</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-12-02 22:15:00</th>\n",
" <td>1.053075</td>\n",
" <td>1.053075</td>\n",
" <td>1.053075</td>\n",
" <td>1.053075</td>\n",
" <td>1.053075</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>3877 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" Open High Low Close Adj Close Volume\n",
"Datetime \n",
"2022-10-07 00:00:00 0.979624 0.979624 0.979144 0.979240 0.979240 0\n",
"2022-10-07 00:15:00 0.979336 0.979912 0.979240 0.979912 0.979912 0\n",
"2022-10-07 00:30:00 0.979912 0.980104 0.979528 0.979528 0.979528 0\n",
"2022-10-07 00:45:00 0.979528 0.979528 0.978953 0.979144 0.979144 0\n",
"2022-10-07 01:00:00 0.979528 0.979720 0.978953 0.979048 0.979048 0\n",
"... ... ... ... ... ... ...\n",
"2022-12-02 21:15:00 1.054074 1.054407 1.053963 1.054407 1.054407 0\n",
"2022-12-02 21:30:00 1.054407 1.054407 1.053963 1.054074 1.054074 0\n",
"2022-12-02 21:45:00 1.053963 1.054519 1.053963 1.054407 1.054407 0\n",
"2022-12-02 22:00:00 1.053075 1.053075 1.053075 1.053075 1.053075 0\n",
"2022-12-02 22:15:00 1.053075 1.053075 1.053075 1.053075 1.053075 0\n",
"\n",
"[3877 rows x 6 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import yfinance as yf\n",
"import pandas as pd\n",
"\n",
"dataF = yf.download(\"EURUSD=X\", start=\"2022-10-7\", end=\"2022-12-5\", interval='15m')\n",
"dataF.iloc[:,:]\n",
"#dataF.Open.iloc"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2 - Define your signal function"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def signal_generator(df):\n",
" open = df.Open.iloc[-1]\n",
" close = df.Close.iloc[-1]\n",
" previous_open = df.Open.iloc[-2]\n",
" previous_close = df.Close.iloc[-2]\n",
" \n",
" # Bearish Pattern\n",
" if (open>close and \n",
" previous_open<previous_close and \n",
" close<previous_open and\n",
" open>=previous_close):\n",
" return 1\n",
"\n",
" # Bullish Pattern\n",
" elif (open<close and \n",
" previous_open>previous_close and \n",
" close>previous_open and\n",
" open<=previous_close):\n",
" return 2\n",
" \n",
" # No clear pattern\n",
" else:\n",
" return 0\n",
"\n",
"signal = []\n",
"signal.append(0)\n",
"for i in range(1,len(dataF)):\n",
" df = dataF[i-1:i+1]\n",
" signal.append(signal_generator(df))\n",
"#signal_generator(data)\n",
"dataF[\"signal\"] = signal"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 3527\n",
"2 178\n",
"1 172\n",
"Name: signal, dtype: int64"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataF.signal.value_counts()\n",
"#dataF.iloc[:, :]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3 - Connect to the market and execute trades"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"from apscheduler.schedulers.blocking import BlockingScheduler\n",
"from oandapyV20 import API\n",
"import oandapyV20.endpoints.orders as orders\n",
"from oandapyV20.contrib.requests import MarketOrderRequest\n",
"from oanda_candles import Pair, Gran, CandleClient\n",
"from oandapyV20.contrib.requests import TakeProfitDetails, StopLossDetails"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n",
"True\n",
"True\n"
]
}
],
"source": [
"from config import access_token, accountID\n",
"def get_candles(n):\n",
" #access_token='XXXXXXX'#you need token here generated from OANDA account\n",
" client = CandleClient(access_token, real=False)\n",
" collector = client.get_collector(Pair.EUR_USD, Gran.M15)\n",
" candles = collector.grab(n)\n",
" return candles\n",
"\n",
"candles = get_candles(3)\n",
"for candle in candles:\n",
" print(float(str(candle.bid.o))>1)\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"def trading_job():\n",
" candles = get_candles(3)\n",
" dfstream = pd.DataFrame(columns=['Open','Close','High','Low'])\n",
" \n",
" i=0\n",
" for candle in candles:\n",
" dfstream.loc[i, ['Open']] = float(str(candle.bid.o))\n",
" dfstream.loc[i, ['Close']] = float(str(candle.bid.c))\n",
" dfstream.loc[i, ['High']] = float(str(candle.bid.h))\n",
" dfstream.loc[i, ['Low']] = float(str(candle.bid.l))\n",
" i=i+1\n",
"\n",
" dfstream['Open'] = dfstream['Open'].astype(float)\n",
" dfstream['Close'] = dfstream['Close'].astype(float)\n",
" dfstream['High'] = dfstream['High'].astype(float)\n",
" dfstream['Low'] = dfstream['Low'].astype(float)\n",
"\n",
" signal = signal_generator(dfstream.iloc[:-1,:])#\n",
" \n",
" # EXECUTING ORDERS\n",
" #accountID = \"XXXXXXX\" #your account ID here\n",
" client = API(access_token)\n",
" \n",
" SLTPRatio = 2.\n",
" previous_candleR = abs(dfstream['High'].iloc[-2]-dfstream['Low'].iloc[-2])\n",
" \n",
" SLBuy = float(str(candle.bid.o))-previous_candleR\n",
" SLSell = float(str(candle.bid.o))+previous_candleR\n",
"\n",
" TPBuy = float(str(candle.bid.o))+previous_candleR*SLTPRatio\n",
" TPSell = float(str(candle.bid.o))-previous_candleR*SLTPRatio\n",
" \n",
" print(dfstream.iloc[:-1,:])\n",
" print(TPBuy, \" \", SLBuy, \" \", TPSell, \" \", SLSell)\n",
" signal = 2\n",
" #Sell\n",
" if signal == 1:\n",
" mo = MarketOrderRequest(instrument=\"EUR_USD\", units=-1000, takeProfitOnFill=TakeProfitDetails(price=TPSell).data, stopLossOnFill=StopLossDetails(price=SLSell).data)\n",
" r = orders.OrderCreate(accountID, data=mo.data)\n",
" rv = client.request(r)\n",
" print(rv)\n",
" #Buy\n",
" elif signal == 2:\n",
" mo = MarketOrderRequest(instrument=\"EUR_USD\", units=1000, takeProfitOnFill=TakeProfitDetails(price=TPBuy).data, stopLossOnFill=StopLossDetails(price=SLBuy).data)\n",
" r = orders.OrderCreate(accountID, data=mo.data)\n",
" rv = client.request(r)\n",
" print(rv)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 4 - Executing orders automatically with a scheduler"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"trading_job()\n",
"\n",
"#scheduler = BlockingScheduler()\n",
"#scheduler.add_job(trading_job, 'cron', day_of_week='mon-fri', hour='00-23', minute='1,16,31,46', start_date='2022-01-12 12:00:00', timezone='America/Chicago')\n",
"#scheduler.start()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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