Technical Analysis 3.ipynb

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       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
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       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.4.2.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
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       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
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       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.4.2.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
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   "source": [
    "# Provides ways to work with large multidimensional arrays\n",
    "import numpy as np \n",
    "# Allows for further data manipulation and analysis\n",
    "import pandas as pd\n",
    "\n",
    "# In Anaconda -> Environments -> Not Installed -> pandas-datareader -> Apply\n",
    "from pandas_datareader import data as web # Reads stock data \n",
    "import matplotlib.pyplot as plt # Plotting\n",
    "import matplotlib.dates as mdates # Styling dates\n",
    "%matplotlib inline\n",
    "\n",
    "import cufflinks as cf\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "# Make Plotly work in your Jupyter Notebook\n",
    "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
    "init_notebook_mode(connected=True)\n",
    "# Use Plotly locally\n",
    "cf.go_offline()\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter(\"ignore\")\n",
    "\n",
    "# pip install yfinance in Qt Console or Powershell Prompt on Windows\n",
    "import yfinance as yf\n",
    "\n",
    "from plotly.subplots import make_subplots\n",
    "\n",
    "# Install the Python Technical Analysis library\n",
    "# pip install ta in Qt Console or Powershell prompt\n",
    "from ta.trend import MACD\n",
    "from ta.momentum import StochasticOscillator\n",
    "\n",
    "# TA-Lib is used by traders to perform technical analysis\n",
    "# Go here : https://github.com/mrjbq7/ta-lib#dependencies\n",
    "# Download ta-lib-0.4.0-msvc.zip and unzip to C:\\ta-lib\n",
    "# On Windows Download : https://visualstudio.microsoft.com/visual-cpp-build-tools/\n",
    "# Remember to Select [Visual C++]\n",
    "# Build using build tools\n",
    "# Download TA_Lib-0.4.21-cp38-cp38-win_amd64.whl from\n",
    "# https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib\n",
    "# In Powershell Prompt pip install \n",
    "# C:\\Users\\derek\\Downloads\\TA_Lib-0.4.21-cp38-cp38-win_amd64.whl\n",
    "\n",
    "# On MacOS \n",
    "import talib as ta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Relative Strength Index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The RSI is used to determine if a security is overbought or oversold. With them you can take advantage of potential changes in trend. The 2 most commonly used oscillators are the RSI and Stochastic RSI. \n",
    "\n",
    "The RSI focuses on the deviation of upward and downward averages with values between 0 and 100. The RSI normally uses 9, 14 or 25 sessions which means it is used mainly as a short term analysis tool. A 14 session period is the most commonly used. When used with 9 sessions 0 to 20 is oversold and 80 to 100 is overbought. With 14 values over 70 are considered overbought and those below 30 oversold. When using 25 over 65 are considered overbought and those below 35 oversold.\n",
    "\n",
    "This indicator is most commonly used with other indicators."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download Stock Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " - Valid periods: 1d,5d,1mo,3mo,6mo,1y,2y,5y,10y,ytd,max\n",
    " - Valid intervals: 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo"
   ]
  },
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     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
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       "      <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",
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       "    <tr>\n",
       "      <th>Datetime</th>\n",
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       "      <th>2021-11-24 09:30:00-05:00</th>\n",
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       "      <th>2021-11-24 09:45:00-05:00</th>\n",
       "      <td>149.000000</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 10:00:00-05:00</th>\n",
       "      <td>151.419998</td>\n",
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       "      <th>2021-11-24 10:15:00-05:00</th>\n",
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       "      <th>2021-11-24 10:30:00-05:00</th>\n",
       "      <td>153.330002</td>\n",
       "      <td>154.399994</td>\n",
       "      <td>153.119995</td>\n",
       "      <td>153.399994</td>\n",
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       "      <td>153.399994</td>\n",
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       "      <th>2021-11-24 11:00:00-05:00</th>\n",
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       "      <th>2021-11-24 11:30:00-05:00</th>\n",
       "      <td>154.619995</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 11:45:00-05:00</th>\n",
       "      <td>154.929993</td>\n",
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       "      <th>2021-11-24 12:00:00-05:00</th>\n",
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       "      <th>2021-11-24 12:15:00-05:00</th>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 12:30:00-05:00</th>\n",
       "      <td>154.759995</td>\n",
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       "      <td>155.307999</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 12:45:00-05:00</th>\n",
       "      <td>155.309998</td>\n",
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       "      <th>2021-11-24 13:00:00-05:00</th>\n",
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       "      <th>2021-11-24 13:15:00-05:00</th>\n",
       "      <td>155.360001</td>\n",
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       "      <th>2021-11-24 13:30:00-05:00</th>\n",
       "      <td>155.669998</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 13:45:00-05:00</th>\n",
       "      <td>156.000000</td>\n",
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       "      <td>155.320007</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 14:00:00-05:00</th>\n",
       "      <td>155.630005</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>154.440002</td>\n",
       "      <td>155.332001</td>\n",
       "      <td>155.332001</td>\n",
       "      <td>2091453</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 14:15:00-05:00</th>\n",
       "      <td>155.318207</td>\n",
       "      <td>155.660004</td>\n",
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       "      <td>155.054993</td>\n",
       "      <td>155.054993</td>\n",
       "      <td>1260223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 14:30:00-05:00</th>\n",
       "      <td>155.110001</td>\n",
       "      <td>155.979996</td>\n",
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       "      <td>155.929993</td>\n",
       "      <td>155.929993</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 14:45:00-05:00</th>\n",
       "      <td>155.899994</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 15:00:00-05:00</th>\n",
       "      <td>156.320007</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 15:15:00-05:00</th>\n",
       "      <td>156.780106</td>\n",
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       "      <td>157.029999</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 15:30:00-05:00</th>\n",
       "      <td>157.029999</td>\n",
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       "      <td>157.369995</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-24 15:45:00-05:00</th>\n",
       "      <td>157.369995</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-26 09:30:00-05:00</th>\n",
       "      <td>155.800003</td>\n",
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       "      <td>154.949799</td>\n",
       "      <td>5570381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 09:45:00-05:00</th>\n",
       "      <td>155.000000</td>\n",
       "      <td>158.070007</td>\n",
       "      <td>154.800003</td>\n",
       "      <td>157.421005</td>\n",
       "      <td>157.421005</td>\n",
       "      <td>3478202</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-26 10:00:00-05:00</th>\n",
       "      <td>157.399994</td>\n",
       "      <td>157.550003</td>\n",
       "      <td>155.449997</td>\n",
       "      <td>155.699997</td>\n",
       "      <td>155.699997</td>\n",
       "      <td>2950795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 10:15:00-05:00</th>\n",
       "      <td>155.699997</td>\n",
       "      <td>156.300003</td>\n",
       "      <td>155.020004</td>\n",
       "      <td>156.249603</td>\n",
       "      <td>156.249603</td>\n",
       "      <td>2189973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 10:30:00-05:00</th>\n",
       "      <td>156.210007</td>\n",
       "      <td>156.699997</td>\n",
       "      <td>155.250000</td>\n",
       "      <td>155.287399</td>\n",
       "      <td>155.287399</td>\n",
       "      <td>2115265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 10:45:00-05:00</th>\n",
       "      <td>155.300003</td>\n",
       "      <td>155.309998</td>\n",
       "      <td>154.177505</td>\n",
       "      <td>155.009995</td>\n",
       "      <td>155.009995</td>\n",
       "      <td>2369518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 11:00:00-05:00</th>\n",
       "      <td>155.000000</td>\n",
       "      <td>155.078003</td>\n",
       "      <td>153.830002</td>\n",
       "      <td>153.999893</td>\n",
       "      <td>153.999893</td>\n",
       "      <td>1525855</td>\n",
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       "    <tr>\n",
       "      <th>2021-11-26 11:15:00-05:00</th>\n",
       "      <td>153.949997</td>\n",
       "      <td>154.130005</td>\n",
       "      <td>152.809998</td>\n",
       "      <td>153.770004</td>\n",
       "      <td>153.770004</td>\n",
       "      <td>1969968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 11:30:00-05:00</th>\n",
       "      <td>153.750000</td>\n",
       "      <td>154.750000</td>\n",
       "      <td>153.520004</td>\n",
       "      <td>154.234207</td>\n",
       "      <td>154.234207</td>\n",
       "      <td>1465703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 11:45:00-05:00</th>\n",
       "      <td>154.248199</td>\n",
       "      <td>155.179993</td>\n",
       "      <td>153.880005</td>\n",
       "      <td>154.509995</td>\n",
       "      <td>154.509995</td>\n",
       "      <td>2074984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 12:00:00-05:00</th>\n",
       "      <td>154.509995</td>\n",
       "      <td>155.190002</td>\n",
       "      <td>154.080093</td>\n",
       "      <td>154.938004</td>\n",
       "      <td>154.938004</td>\n",
       "      <td>1321109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 12:15:00-05:00</th>\n",
       "      <td>154.949005</td>\n",
       "      <td>156.029999</td>\n",
       "      <td>154.831207</td>\n",
       "      <td>155.949997</td>\n",
       "      <td>155.949997</td>\n",
       "      <td>1653144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 12:30:00-05:00</th>\n",
       "      <td>155.949997</td>\n",
       "      <td>156.750000</td>\n",
       "      <td>155.529999</td>\n",
       "      <td>155.698898</td>\n",
       "      <td>155.698898</td>\n",
       "      <td>2603152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 12:45:00-05:00</th>\n",
       "      <td>155.685501</td>\n",
       "      <td>155.910004</td>\n",
       "      <td>154.029999</td>\n",
       "      <td>154.889999</td>\n",
       "      <td>154.889999</td>\n",
       "      <td>3618774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 13:00:00-05:00</th>\n",
       "      <td>154.889999</td>\n",
       "      <td>155.089996</td>\n",
       "      <td>154.399994</td>\n",
       "      <td>154.949997</td>\n",
       "      <td>154.949997</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 09:30:00-05:00</th>\n",
       "      <td>157.500000</td>\n",
       "      <td>159.914993</td>\n",
       "      <td>157.454300</td>\n",
       "      <td>158.759995</td>\n",
       "      <td>158.759995</td>\n",
       "      <td>6783298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 09:45:00-05:00</th>\n",
       "      <td>158.250000</td>\n",
       "      <td>159.679993</td>\n",
       "      <td>157.839996</td>\n",
       "      <td>158.910004</td>\n",
       "      <td>158.910004</td>\n",
       "      <td>3638047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 10:00:00-05:00</th>\n",
       "      <td>158.880005</td>\n",
       "      <td>159.860001</td>\n",
       "      <td>158.300003</td>\n",
       "      <td>158.850006</td>\n",
       "      <td>158.850006</td>\n",
       "      <td>2789088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 10:15:00-05:00</th>\n",
       "      <td>158.869904</td>\n",
       "      <td>159.423904</td>\n",
       "      <td>156.940002</td>\n",
       "      <td>157.185501</td>\n",
       "      <td>157.185501</td>\n",
       "      <td>2756871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 10:30:00-05:00</th>\n",
       "      <td>157.160004</td>\n",
       "      <td>157.409607</td>\n",
       "      <td>156.100006</td>\n",
       "      <td>157.029999</td>\n",
       "      <td>157.029999</td>\n",
       "      <td>2972988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 10:45:00-05:00</th>\n",
       "      <td>157.029999</td>\n",
       "      <td>158.699997</td>\n",
       "      <td>156.940002</td>\n",
       "      <td>157.960007</td>\n",
       "      <td>157.960007</td>\n",
       "      <td>3765303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 11:00:00-05:00</th>\n",
       "      <td>157.960007</td>\n",
       "      <td>158.699905</td>\n",
       "      <td>157.510101</td>\n",
       "      <td>158.162796</td>\n",
       "      <td>158.162796</td>\n",
       "      <td>1754281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 11:15:00-05:00</th>\n",
       "      <td>158.220001</td>\n",
       "      <td>158.899994</td>\n",
       "      <td>157.869995</td>\n",
       "      <td>157.899994</td>\n",
       "      <td>157.899994</td>\n",
       "      <td>1517994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 11:30:00-05:00</th>\n",
       "      <td>157.895493</td>\n",
       "      <td>159.270004</td>\n",
       "      <td>157.869995</td>\n",
       "      <td>159.080002</td>\n",
       "      <td>159.080002</td>\n",
       "      <td>1822299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 11:45:00-05:00</th>\n",
       "      <td>159.089996</td>\n",
       "      <td>159.149994</td>\n",
       "      <td>158.600006</td>\n",
       "      <td>158.929993</td>\n",
       "      <td>158.929993</td>\n",
       "      <td>1086505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 12:00:00-05:00</th>\n",
       "      <td>158.940002</td>\n",
       "      <td>159.699997</td>\n",
       "      <td>158.750000</td>\n",
       "      <td>159.190002</td>\n",
       "      <td>159.190002</td>\n",
       "      <td>1594890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 12:14:01-05:00</th>\n",
       "      <td>159.211304</td>\n",
       "      <td>159.211304</td>\n",
       "      <td>159.211304</td>\n",
       "      <td>159.211304</td>\n",
       "      <td>159.211304</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Open        High         Low       Close  \\\n",
       "Datetime                                                                    \n",
       "2021-11-24 09:30:00-05:00  149.460007  150.018494  147.250000  148.970001   \n",
       "2021-11-24 09:45:00-05:00  149.000000  151.619995  148.509995  151.442902   \n",
       "2021-11-24 10:00:00-05:00  151.419998  152.740005  150.899994  152.424301   \n",
       "2021-11-24 10:15:00-05:00  152.429993  153.679993  152.309998  153.304993   \n",
       "2021-11-24 10:30:00-05:00  153.330002  154.399994  153.119995  153.399994   \n",
       "2021-11-24 10:45:00-05:00  153.399994  154.309998  152.880005  152.984604   \n",
       "2021-11-24 11:00:00-05:00  152.970001  153.850006  152.559998  153.460007   \n",
       "2021-11-24 11:15:00-05:00  153.440002  154.799393  153.370102  154.619995   \n",
       "2021-11-24 11:30:00-05:00  154.619995  155.000000  154.330002  154.936905   \n",
       "2021-11-24 11:45:00-05:00  154.929993  155.300003  154.369995  154.679993   \n",
       "2021-11-24 12:00:00-05:00  154.699905  155.399994  154.369995  154.835007   \n",
       "2021-11-24 12:15:00-05:00  154.809998  154.987106  154.179993  154.804993   \n",
       "2021-11-24 12:30:00-05:00  154.759995  155.660004  154.490097  155.307999   \n",
       "2021-11-24 12:45:00-05:00  155.309998  155.669998  155.169998  155.300201   \n",
       "2021-11-24 13:00:00-05:00  155.294998  155.489197  155.020004  155.366898   \n",
       "2021-11-24 13:15:00-05:00  155.360001  155.860001  155.320007  155.650497   \n",
       "2021-11-24 13:30:00-05:00  155.669998  156.259995  155.449997  155.994995   \n",
       "2021-11-24 13:45:00-05:00  156.000000  156.050003  155.320007  155.671005   \n",
       "2021-11-24 14:00:00-05:00  155.630005  156.000000  154.440002  155.332001   \n",
       "2021-11-24 14:15:00-05:00  155.318207  155.660004  154.811005  155.054993   \n",
       "2021-11-24 14:30:00-05:00  155.110001  155.979996  155.110001  155.929993   \n",
       "2021-11-24 14:45:00-05:00  155.899994  156.539993  155.809998  156.309998   \n",
       "2021-11-24 15:00:00-05:00  156.320007  156.850006  156.119995  156.789993   \n",
       "2021-11-24 15:15:00-05:00  156.780106  157.095001  156.570007  157.029999   \n",
       "2021-11-24 15:30:00-05:00  157.029999  157.679993  156.839996  157.369995   \n",
       "2021-11-24 15:45:00-05:00  157.369995  157.929993  157.039993  157.779999   \n",
       "2021-11-26 09:30:00-05:00  155.800003  157.230499  154.850006  154.949799   \n",
       "2021-11-26 09:45:00-05:00  155.000000  158.070007  154.800003  157.421005   \n",
       "2021-11-26 10:00:00-05:00  157.399994  157.550003  155.449997  155.699997   \n",
       "2021-11-26 10:15:00-05:00  155.699997  156.300003  155.020004  156.249603   \n",
       "2021-11-26 10:30:00-05:00  156.210007  156.699997  155.250000  155.287399   \n",
       "2021-11-26 10:45:00-05:00  155.300003  155.309998  154.177505  155.009995   \n",
       "2021-11-26 11:00:00-05:00  155.000000  155.078003  153.830002  153.999893   \n",
       "2021-11-26 11:15:00-05:00  153.949997  154.130005  152.809998  153.770004   \n",
       "2021-11-26 11:30:00-05:00  153.750000  154.750000  153.520004  154.234207   \n",
       "2021-11-26 11:45:00-05:00  154.248199  155.179993  153.880005  154.509995   \n",
       "2021-11-26 12:00:00-05:00  154.509995  155.190002  154.080093  154.938004   \n",
       "2021-11-26 12:15:00-05:00  154.949005  156.029999  154.831207  155.949997   \n",
       "2021-11-26 12:30:00-05:00  155.949997  156.750000  155.529999  155.698898   \n",
       "2021-11-26 12:45:00-05:00  155.685501  155.910004  154.029999  154.889999   \n",
       "2021-11-26 13:00:00-05:00  154.889999  155.089996  154.399994  154.949997   \n",
       "2021-11-29 09:30:00-05:00  157.500000  159.914993  157.454300  158.759995   \n",
       "2021-11-29 09:45:00-05:00  158.250000  159.679993  157.839996  158.910004   \n",
       "2021-11-29 10:00:00-05:00  158.880005  159.860001  158.300003  158.850006   \n",
       "2021-11-29 10:15:00-05:00  158.869904  159.423904  156.940002  157.185501   \n",
       "2021-11-29 10:30:00-05:00  157.160004  157.409607  156.100006  157.029999   \n",
       "2021-11-29 10:45:00-05:00  157.029999  158.699997  156.940002  157.960007   \n",
       "2021-11-29 11:00:00-05:00  157.960007  158.699905  157.510101  158.162796   \n",
       "2021-11-29 11:15:00-05:00  158.220001  158.899994  157.869995  157.899994   \n",
       "2021-11-29 11:30:00-05:00  157.895493  159.270004  157.869995  159.080002   \n",
       "2021-11-29 11:45:00-05:00  159.089996  159.149994  158.600006  158.929993   \n",
       "2021-11-29 12:00:00-05:00  158.940002  159.699997  158.750000  159.190002   \n",
       "2021-11-29 12:14:01-05:00  159.211304  159.211304  159.211304  159.211304   \n",
       "\n",
       "                            Adj Close   Volume  \n",
       "Datetime                                        \n",
       "2021-11-24 09:30:00-05:00  148.970001  4650297  \n",
       "2021-11-24 09:45:00-05:00  151.442902  3931598  \n",
       "2021-11-24 10:00:00-05:00  152.424301  4026580  \n",
       "2021-11-24 10:15:00-05:00  153.304993  3302656  \n",
       "2021-11-24 10:30:00-05:00  153.399994  3118773  \n",
       "2021-11-24 10:45:00-05:00  152.984604  3233784  \n",
       "2021-11-24 11:00:00-05:00  153.460007  2325867  \n",
       "2021-11-24 11:15:00-05:00  154.619995  2346425  \n",
       "2021-11-24 11:30:00-05:00  154.936905  3090393  \n",
       "2021-11-24 11:45:00-05:00  154.679993  2377495  \n",
       "2021-11-24 12:00:00-05:00  154.835007  1965996  \n",
       "2021-11-24 12:15:00-05:00  154.804993  1545364  \n",
       "2021-11-24 12:30:00-05:00  155.307999  1833890  \n",
       "2021-11-24 12:45:00-05:00  155.300201  1315181  \n",
       "2021-11-24 13:00:00-05:00  155.366898  1021886  \n",
       "2021-11-24 13:15:00-05:00  155.650497  1160713  \n",
       "2021-11-24 13:30:00-05:00  155.994995  1797823  \n",
       "2021-11-24 13:45:00-05:00  155.671005  1290246  \n",
       "2021-11-24 14:00:00-05:00  155.332001  2091453  \n",
       "2021-11-24 14:15:00-05:00  155.054993  1260223  \n",
       "2021-11-24 14:30:00-05:00  155.929993  1181077  \n",
       "2021-11-24 14:45:00-05:00  156.309998  1558408  \n",
       "2021-11-24 15:00:00-05:00  156.789993  1753262  \n",
       "2021-11-24 15:15:00-05:00  157.029999  1449452  \n",
       "2021-11-24 15:30:00-05:00  157.369995  2584528  \n",
       "2021-11-24 15:45:00-05:00  157.779999  3277326  \n",
       "2021-11-26 09:30:00-05:00  154.949799  5570381  \n",
       "2021-11-26 09:45:00-05:00  157.421005  3478202  \n",
       "2021-11-26 10:00:00-05:00  155.699997  2950795  \n",
       "2021-11-26 10:15:00-05:00  156.249603  2189973  \n",
       "2021-11-26 10:30:00-05:00  155.287399  2115265  \n",
       "2021-11-26 10:45:00-05:00  155.009995  2369518  \n",
       "2021-11-26 11:00:00-05:00  153.999893  1525855  \n",
       "2021-11-26 11:15:00-05:00  153.770004  1969968  \n",
       "2021-11-26 11:30:00-05:00  154.234207  1465703  \n",
       "2021-11-26 11:45:00-05:00  154.509995  2074984  \n",
       "2021-11-26 12:00:00-05:00  154.938004  1321109  \n",
       "2021-11-26 12:15:00-05:00  155.949997  1653144  \n",
       "2021-11-26 12:30:00-05:00  155.698898  2603152  \n",
       "2021-11-26 12:45:00-05:00  154.889999  3618774  \n",
       "2021-11-26 13:00:00-05:00  154.949997        0  \n",
       "2021-11-29 09:30:00-05:00  158.759995  6783298  \n",
       "2021-11-29 09:45:00-05:00  158.910004  3638047  \n",
       "2021-11-29 10:00:00-05:00  158.850006  2789088  \n",
       "2021-11-29 10:15:00-05:00  157.185501  2756871  \n",
       "2021-11-29 10:30:00-05:00  157.029999  2972988  \n",
       "2021-11-29 10:45:00-05:00  157.960007  3765303  \n",
       "2021-11-29 11:00:00-05:00  158.162796  1754281  \n",
       "2021-11-29 11:15:00-05:00  157.899994  1517994  \n",
       "2021-11-29 11:30:00-05:00  159.080002  1822299  \n",
       "2021-11-29 11:45:00-05:00  158.929993  1086505  \n",
       "2021-11-29 12:00:00-05:00  159.190002  1594890  \n",
       "2021-11-29 12:14:01-05:00  159.211304        0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amd_df = yf.download(tickers=\"AMD\", period=\"3d\", interval='15m')\n",
    "amd_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculating RSI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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",
       "      <th>RSI</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-11-24 09:30:00-05:00</th>\n",
       "      <td>149.460007</td>\n",
       "      <td>150.018494</td>\n",
       "      <td>147.250000</td>\n",
       "      <td>148.970001</td>\n",
       "      <td>148.970001</td>\n",
       "      <td>4650297</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 09:45:00-05:00</th>\n",
       "      <td>149.000000</td>\n",
       "      <td>151.619995</td>\n",
       "      <td>148.509995</td>\n",
       "      <td>151.442902</td>\n",
       "      <td>151.442902</td>\n",
       "      <td>3931598</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 10:00:00-05:00</th>\n",
       "      <td>151.419998</td>\n",
       "      <td>152.740005</td>\n",
       "      <td>150.899994</td>\n",
       "      <td>152.424301</td>\n",
       "      <td>152.424301</td>\n",
       "      <td>4026580</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 10:15:00-05:00</th>\n",
       "      <td>152.429993</td>\n",
       "      <td>153.679993</td>\n",
       "      <td>152.309998</td>\n",
       "      <td>153.304993</td>\n",
       "      <td>153.304993</td>\n",
       "      <td>3302656</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 10:30:00-05:00</th>\n",
       "      <td>153.330002</td>\n",
       "      <td>154.399994</td>\n",
       "      <td>153.119995</td>\n",
       "      <td>153.399994</td>\n",
       "      <td>153.399994</td>\n",
       "      <td>3118773</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 10:45:00-05:00</th>\n",
       "      <td>153.399994</td>\n",
       "      <td>154.309998</td>\n",
       "      <td>152.880005</td>\n",
       "      <td>152.984604</td>\n",
       "      <td>152.984604</td>\n",
       "      <td>3233784</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 11:00:00-05:00</th>\n",
       "      <td>152.970001</td>\n",
       "      <td>153.850006</td>\n",
       "      <td>152.559998</td>\n",
       "      <td>153.460007</td>\n",
       "      <td>153.460007</td>\n",
       "      <td>2325867</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 11:15:00-05:00</th>\n",
       "      <td>153.440002</td>\n",
       "      <td>154.799393</td>\n",
       "      <td>153.370102</td>\n",
       "      <td>154.619995</td>\n",
       "      <td>154.619995</td>\n",
       "      <td>2346425</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 11:30:00-05:00</th>\n",
       "      <td>154.619995</td>\n",
       "      <td>155.000000</td>\n",
       "      <td>154.330002</td>\n",
       "      <td>154.936905</td>\n",
       "      <td>154.936905</td>\n",
       "      <td>3090393</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 11:45:00-05:00</th>\n",
       "      <td>154.929993</td>\n",
       "      <td>155.300003</td>\n",
       "      <td>154.369995</td>\n",
       "      <td>154.679993</td>\n",
       "      <td>154.679993</td>\n",
       "      <td>2377495</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 12:00:00-05:00</th>\n",
       "      <td>154.699905</td>\n",
       "      <td>155.399994</td>\n",
       "      <td>154.369995</td>\n",
       "      <td>154.835007</td>\n",
       "      <td>154.835007</td>\n",
       "      <td>1965996</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 12:15:00-05:00</th>\n",
       "      <td>154.809998</td>\n",
       "      <td>154.987106</td>\n",
       "      <td>154.179993</td>\n",
       "      <td>154.804993</td>\n",
       "      <td>154.804993</td>\n",
       "      <td>1545364</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 12:30:00-05:00</th>\n",
       "      <td>154.759995</td>\n",
       "      <td>155.660004</td>\n",
       "      <td>154.490097</td>\n",
       "      <td>155.307999</td>\n",
       "      <td>155.307999</td>\n",
       "      <td>1833890</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 12:45:00-05:00</th>\n",
       "      <td>155.309998</td>\n",
       "      <td>155.669998</td>\n",
       "      <td>155.169998</td>\n",
       "      <td>155.300201</td>\n",
       "      <td>155.300201</td>\n",
       "      <td>1315181</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 13:00:00-05:00</th>\n",
       "      <td>155.294998</td>\n",
       "      <td>155.489197</td>\n",
       "      <td>155.020004</td>\n",
       "      <td>155.366898</td>\n",
       "      <td>155.366898</td>\n",
       "      <td>1021886</td>\n",
       "      <td>90.915923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 13:15:00-05:00</th>\n",
       "      <td>155.360001</td>\n",
       "      <td>155.860001</td>\n",
       "      <td>155.320007</td>\n",
       "      <td>155.650497</td>\n",
       "      <td>155.650497</td>\n",
       "      <td>1160713</td>\n",
       "      <td>91.257493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 13:30:00-05:00</th>\n",
       "      <td>155.669998</td>\n",
       "      <td>156.259995</td>\n",
       "      <td>155.449997</td>\n",
       "      <td>155.994995</td>\n",
       "      <td>155.994995</td>\n",
       "      <td>1797823</td>\n",
       "      <td>91.667363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 13:45:00-05:00</th>\n",
       "      <td>156.000000</td>\n",
       "      <td>156.050003</td>\n",
       "      <td>155.320007</td>\n",
       "      <td>155.671005</td>\n",
       "      <td>155.671005</td>\n",
       "      <td>1290246</td>\n",
       "      <td>87.512011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 14:00:00-05:00</th>\n",
       "      <td>155.630005</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>154.440002</td>\n",
       "      <td>155.332001</td>\n",
       "      <td>155.332001</td>\n",
       "      <td>2091453</td>\n",
       "      <td>83.259126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 14:15:00-05:00</th>\n",
       "      <td>155.318207</td>\n",
       "      <td>155.660004</td>\n",
       "      <td>154.811005</td>\n",
       "      <td>155.054993</td>\n",
       "      <td>155.054993</td>\n",
       "      <td>1260223</td>\n",
       "      <td>79.844579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 14:30:00-05:00</th>\n",
       "      <td>155.110001</td>\n",
       "      <td>155.979996</td>\n",
       "      <td>155.110001</td>\n",
       "      <td>155.929993</td>\n",
       "      <td>155.929993</td>\n",
       "      <td>1181077</td>\n",
       "      <td>82.312185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 14:45:00-05:00</th>\n",
       "      <td>155.899994</td>\n",
       "      <td>156.539993</td>\n",
       "      <td>155.809998</td>\n",
       "      <td>156.309998</td>\n",
       "      <td>156.309998</td>\n",
       "      <td>1558408</td>\n",
       "      <td>83.270133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 15:00:00-05:00</th>\n",
       "      <td>156.320007</td>\n",
       "      <td>156.850006</td>\n",
       "      <td>156.119995</td>\n",
       "      <td>156.789993</td>\n",
       "      <td>156.789993</td>\n",
       "      <td>1753262</td>\n",
       "      <td>84.418080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 15:15:00-05:00</th>\n",
       "      <td>156.780106</td>\n",
       "      <td>157.095001</td>\n",
       "      <td>156.570007</td>\n",
       "      <td>157.029999</td>\n",
       "      <td>157.029999</td>\n",
       "      <td>1449452</td>\n",
       "      <td>84.973295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 15:30:00-05:00</th>\n",
       "      <td>157.029999</td>\n",
       "      <td>157.679993</td>\n",
       "      <td>156.839996</td>\n",
       "      <td>157.369995</td>\n",
       "      <td>157.369995</td>\n",
       "      <td>2584528</td>\n",
       "      <td>85.748031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24 15:45:00-05:00</th>\n",
       "      <td>157.369995</td>\n",
       "      <td>157.929993</td>\n",
       "      <td>157.039993</td>\n",
       "      <td>157.779999</td>\n",
       "      <td>157.779999</td>\n",
       "      <td>3277326</td>\n",
       "      <td>86.642398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 09:30:00-05:00</th>\n",
       "      <td>155.800003</td>\n",
       "      <td>157.230499</td>\n",
       "      <td>154.850006</td>\n",
       "      <td>154.949799</td>\n",
       "      <td>154.949799</td>\n",
       "      <td>5570381</td>\n",
       "      <td>59.080916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 09:45:00-05:00</th>\n",
       "      <td>155.000000</td>\n",
       "      <td>158.070007</td>\n",
       "      <td>154.800003</td>\n",
       "      <td>157.421005</td>\n",
       "      <td>157.421005</td>\n",
       "      <td>3478202</td>\n",
       "      <td>68.502514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 10:00:00-05:00</th>\n",
       "      <td>157.399994</td>\n",
       "      <td>157.550003</td>\n",
       "      <td>155.449997</td>\n",
       "      <td>155.699997</td>\n",
       "      <td>155.699997</td>\n",
       "      <td>2950795</td>\n",
       "      <td>58.415050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 10:15:00-05:00</th>\n",
       "      <td>155.699997</td>\n",
       "      <td>156.300003</td>\n",
       "      <td>155.020004</td>\n",
       "      <td>156.249603</td>\n",
       "      <td>156.249603</td>\n",
       "      <td>2189973</td>\n",
       "      <td>60.419566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 10:30:00-05:00</th>\n",
       "      <td>156.210007</td>\n",
       "      <td>156.699997</td>\n",
       "      <td>155.250000</td>\n",
       "      <td>155.287399</td>\n",
       "      <td>155.287399</td>\n",
       "      <td>2115265</td>\n",
       "      <td>55.386025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 10:45:00-05:00</th>\n",
       "      <td>155.300003</td>\n",
       "      <td>155.309998</td>\n",
       "      <td>154.177505</td>\n",
       "      <td>155.009995</td>\n",
       "      <td>155.009995</td>\n",
       "      <td>2369518</td>\n",
       "      <td>53.989537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 11:00:00-05:00</th>\n",
       "      <td>155.000000</td>\n",
       "      <td>155.078003</td>\n",
       "      <td>153.830002</td>\n",
       "      <td>153.999893</td>\n",
       "      <td>153.999893</td>\n",
       "      <td>1525855</td>\n",
       "      <td>49.131787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 11:15:00-05:00</th>\n",
       "      <td>153.949997</td>\n",
       "      <td>154.130005</td>\n",
       "      <td>152.809998</td>\n",
       "      <td>153.770004</td>\n",
       "      <td>153.770004</td>\n",
       "      <td>1969968</td>\n",
       "      <td>48.071673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 11:30:00-05:00</th>\n",
       "      <td>153.750000</td>\n",
       "      <td>154.750000</td>\n",
       "      <td>153.520004</td>\n",
       "      <td>154.234207</td>\n",
       "      <td>154.234207</td>\n",
       "      <td>1465703</td>\n",
       "      <td>50.398987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 11:45:00-05:00</th>\n",
       "      <td>154.248199</td>\n",
       "      <td>155.179993</td>\n",
       "      <td>153.880005</td>\n",
       "      <td>154.509995</td>\n",
       "      <td>154.509995</td>\n",
       "      <td>2074984</td>\n",
       "      <td>51.781644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 12:00:00-05:00</th>\n",
       "      <td>154.509995</td>\n",
       "      <td>155.190002</td>\n",
       "      <td>154.080093</td>\n",
       "      <td>154.938004</td>\n",
       "      <td>154.938004</td>\n",
       "      <td>1321109</td>\n",
       "      <td>53.928105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 12:15:00-05:00</th>\n",
       "      <td>154.949005</td>\n",
       "      <td>156.029999</td>\n",
       "      <td>154.831207</td>\n",
       "      <td>155.949997</td>\n",
       "      <td>155.949997</td>\n",
       "      <td>1653144</td>\n",
       "      <td>58.618665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 12:30:00-05:00</th>\n",
       "      <td>155.949997</td>\n",
       "      <td>156.750000</td>\n",
       "      <td>155.529999</td>\n",
       "      <td>155.698898</td>\n",
       "      <td>155.698898</td>\n",
       "      <td>2603152</td>\n",
       "      <td>57.066210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 12:45:00-05:00</th>\n",
       "      <td>155.685501</td>\n",
       "      <td>155.910004</td>\n",
       "      <td>154.029999</td>\n",
       "      <td>154.889999</td>\n",
       "      <td>154.889999</td>\n",
       "      <td>3618774</td>\n",
       "      <td>52.264212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26 13:00:00-05:00</th>\n",
       "      <td>154.889999</td>\n",
       "      <td>155.089996</td>\n",
       "      <td>154.399994</td>\n",
       "      <td>154.949997</td>\n",
       "      <td>154.949997</td>\n",
       "      <td>0</td>\n",
       "      <td>52.582926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 09:30:00-05:00</th>\n",
       "      <td>157.500000</td>\n",
       "      <td>159.914993</td>\n",
       "      <td>157.454300</td>\n",
       "      <td>158.759995</td>\n",
       "      <td>158.759995</td>\n",
       "      <td>6783298</td>\n",
       "      <td>67.446685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 09:45:00-05:00</th>\n",
       "      <td>158.250000</td>\n",
       "      <td>159.679993</td>\n",
       "      <td>157.839996</td>\n",
       "      <td>158.910004</td>\n",
       "      <td>158.910004</td>\n",
       "      <td>3638047</td>\n",
       "      <td>67.873690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 10:00:00-05:00</th>\n",
       "      <td>158.880005</td>\n",
       "      <td>159.860001</td>\n",
       "      <td>158.300003</td>\n",
       "      <td>158.850006</td>\n",
       "      <td>158.850006</td>\n",
       "      <td>2789088</td>\n",
       "      <td>67.492367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 10:15:00-05:00</th>\n",
       "      <td>158.869904</td>\n",
       "      <td>159.423904</td>\n",
       "      <td>156.940002</td>\n",
       "      <td>157.185501</td>\n",
       "      <td>157.185501</td>\n",
       "      <td>2756871</td>\n",
       "      <td>57.791871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 10:30:00-05:00</th>\n",
       "      <td>157.160004</td>\n",
       "      <td>157.409607</td>\n",
       "      <td>156.100006</td>\n",
       "      <td>157.029999</td>\n",
       "      <td>157.029999</td>\n",
       "      <td>2972988</td>\n",
       "      <td>56.968098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 10:45:00-05:00</th>\n",
       "      <td>157.029999</td>\n",
       "      <td>158.699997</td>\n",
       "      <td>156.940002</td>\n",
       "      <td>157.960007</td>\n",
       "      <td>157.960007</td>\n",
       "      <td>3765303</td>\n",
       "      <td>60.586526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 11:00:00-05:00</th>\n",
       "      <td>157.960007</td>\n",
       "      <td>158.699905</td>\n",
       "      <td>157.510101</td>\n",
       "      <td>158.162796</td>\n",
       "      <td>158.162796</td>\n",
       "      <td>1754281</td>\n",
       "      <td>61.349703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 11:15:00-05:00</th>\n",
       "      <td>158.220001</td>\n",
       "      <td>158.899994</td>\n",
       "      <td>157.869995</td>\n",
       "      <td>157.899994</td>\n",
       "      <td>157.899994</td>\n",
       "      <td>1517994</td>\n",
       "      <td>59.735415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 11:30:00-05:00</th>\n",
       "      <td>157.895493</td>\n",
       "      <td>159.270004</td>\n",
       "      <td>157.869995</td>\n",
       "      <td>159.080002</td>\n",
       "      <td>159.080002</td>\n",
       "      <td>1822299</td>\n",
       "      <td>64.280245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 11:45:00-05:00</th>\n",
       "      <td>159.089996</td>\n",
       "      <td>159.149994</td>\n",
       "      <td>158.600006</td>\n",
       "      <td>158.929993</td>\n",
       "      <td>158.929993</td>\n",
       "      <td>1086505</td>\n",
       "      <td>63.302041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 12:00:00-05:00</th>\n",
       "      <td>158.940002</td>\n",
       "      <td>159.699997</td>\n",
       "      <td>158.750000</td>\n",
       "      <td>159.190002</td>\n",
       "      <td>159.190002</td>\n",
       "      <td>1594890</td>\n",
       "      <td>64.315686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29 12:14:01-05:00</th>\n",
       "      <td>159.211304</td>\n",
       "      <td>159.211304</td>\n",
       "      <td>159.211304</td>\n",
       "      <td>159.211304</td>\n",
       "      <td>159.211304</td>\n",
       "      <td>0</td>\n",
       "      <td>64.402435</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Open        High         Low       Close  \\\n",
       "Datetime                                                                    \n",
       "2021-11-24 09:30:00-05:00  149.460007  150.018494  147.250000  148.970001   \n",
       "2021-11-24 09:45:00-05:00  149.000000  151.619995  148.509995  151.442902   \n",
       "2021-11-24 10:00:00-05:00  151.419998  152.740005  150.899994  152.424301   \n",
       "2021-11-24 10:15:00-05:00  152.429993  153.679993  152.309998  153.304993   \n",
       "2021-11-24 10:30:00-05:00  153.330002  154.399994  153.119995  153.399994   \n",
       "2021-11-24 10:45:00-05:00  153.399994  154.309998  152.880005  152.984604   \n",
       "2021-11-24 11:00:00-05:00  152.970001  153.850006  152.559998  153.460007   \n",
       "2021-11-24 11:15:00-05:00  153.440002  154.799393  153.370102  154.619995   \n",
       "2021-11-24 11:30:00-05:00  154.619995  155.000000  154.330002  154.936905   \n",
       "2021-11-24 11:45:00-05:00  154.929993  155.300003  154.369995  154.679993   \n",
       "2021-11-24 12:00:00-05:00  154.699905  155.399994  154.369995  154.835007   \n",
       "2021-11-24 12:15:00-05:00  154.809998  154.987106  154.179993  154.804993   \n",
       "2021-11-24 12:30:00-05:00  154.759995  155.660004  154.490097  155.307999   \n",
       "2021-11-24 12:45:00-05:00  155.309998  155.669998  155.169998  155.300201   \n",
       "2021-11-24 13:00:00-05:00  155.294998  155.489197  155.020004  155.366898   \n",
       "2021-11-24 13:15:00-05:00  155.360001  155.860001  155.320007  155.650497   \n",
       "2021-11-24 13:30:00-05:00  155.669998  156.259995  155.449997  155.994995   \n",
       "2021-11-24 13:45:00-05:00  156.000000  156.050003  155.320007  155.671005   \n",
       "2021-11-24 14:00:00-05:00  155.630005  156.000000  154.440002  155.332001   \n",
       "2021-11-24 14:15:00-05:00  155.318207  155.660004  154.811005  155.054993   \n",
       "2021-11-24 14:30:00-05:00  155.110001  155.979996  155.110001  155.929993   \n",
       "2021-11-24 14:45:00-05:00  155.899994  156.539993  155.809998  156.309998   \n",
       "2021-11-24 15:00:00-05:00  156.320007  156.850006  156.119995  156.789993   \n",
       "2021-11-24 15:15:00-05:00  156.780106  157.095001  156.570007  157.029999   \n",
       "2021-11-24 15:30:00-05:00  157.029999  157.679993  156.839996  157.369995   \n",
       "2021-11-24 15:45:00-05:00  157.369995  157.929993  157.039993  157.779999   \n",
       "2021-11-26 09:30:00-05:00  155.800003  157.230499  154.850006  154.949799   \n",
       "2021-11-26 09:45:00-05:00  155.000000  158.070007  154.800003  157.421005   \n",
       "2021-11-26 10:00:00-05:00  157.399994  157.550003  155.449997  155.699997   \n",
       "2021-11-26 10:15:00-05:00  155.699997  156.300003  155.020004  156.249603   \n",
       "2021-11-26 10:30:00-05:00  156.210007  156.699997  155.250000  155.287399   \n",
       "2021-11-26 10:45:00-05:00  155.300003  155.309998  154.177505  155.009995   \n",
       "2021-11-26 11:00:00-05:00  155.000000  155.078003  153.830002  153.999893   \n",
       "2021-11-26 11:15:00-05:00  153.949997  154.130005  152.809998  153.770004   \n",
       "2021-11-26 11:30:00-05:00  153.750000  154.750000  153.520004  154.234207   \n",
       "2021-11-26 11:45:00-05:00  154.248199  155.179993  153.880005  154.509995   \n",
       "2021-11-26 12:00:00-05:00  154.509995  155.190002  154.080093  154.938004   \n",
       "2021-11-26 12:15:00-05:00  154.949005  156.029999  154.831207  155.949997   \n",
       "2021-11-26 12:30:00-05:00  155.949997  156.750000  155.529999  155.698898   \n",
       "2021-11-26 12:45:00-05:00  155.685501  155.910004  154.029999  154.889999   \n",
       "2021-11-26 13:00:00-05:00  154.889999  155.089996  154.399994  154.949997   \n",
       "2021-11-29 09:30:00-05:00  157.500000  159.914993  157.454300  158.759995   \n",
       "2021-11-29 09:45:00-05:00  158.250000  159.679993  157.839996  158.910004   \n",
       "2021-11-29 10:00:00-05:00  158.880005  159.860001  158.300003  158.850006   \n",
       "2021-11-29 10:15:00-05:00  158.869904  159.423904  156.940002  157.185501   \n",
       "2021-11-29 10:30:00-05:00  157.160004  157.409607  156.100006  157.029999   \n",
       "2021-11-29 10:45:00-05:00  157.029999  158.699997  156.940002  157.960007   \n",
       "2021-11-29 11:00:00-05:00  157.960007  158.699905  157.510101  158.162796   \n",
       "2021-11-29 11:15:00-05:00  158.220001  158.899994  157.869995  157.899994   \n",
       "2021-11-29 11:30:00-05:00  157.895493  159.270004  157.869995  159.080002   \n",
       "2021-11-29 11:45:00-05:00  159.089996  159.149994  158.600006  158.929993   \n",
       "2021-11-29 12:00:00-05:00  158.940002  159.699997  158.750000  159.190002   \n",
       "2021-11-29 12:14:01-05:00  159.211304  159.211304  159.211304  159.211304   \n",
       "\n",
       "                            Adj Close   Volume        RSI  \n",
       "Datetime                                                   \n",
       "2021-11-24 09:30:00-05:00  148.970001  4650297        NaN  \n",
       "2021-11-24 09:45:00-05:00  151.442902  3931598        NaN  \n",
       "2021-11-24 10:00:00-05:00  152.424301  4026580        NaN  \n",
       "2021-11-24 10:15:00-05:00  153.304993  3302656        NaN  \n",
       "2021-11-24 10:30:00-05:00  153.399994  3118773        NaN  \n",
       "2021-11-24 10:45:00-05:00  152.984604  3233784        NaN  \n",
       "2021-11-24 11:00:00-05:00  153.460007  2325867        NaN  \n",
       "2021-11-24 11:15:00-05:00  154.619995  2346425        NaN  \n",
       "2021-11-24 11:30:00-05:00  154.936905  3090393        NaN  \n",
       "2021-11-24 11:45:00-05:00  154.679993  2377495        NaN  \n",
       "2021-11-24 12:00:00-05:00  154.835007  1965996        NaN  \n",
       "2021-11-24 12:15:00-05:00  154.804993  1545364        NaN  \n",
       "2021-11-24 12:30:00-05:00  155.307999  1833890        NaN  \n",
       "2021-11-24 12:45:00-05:00  155.300201  1315181        NaN  \n",
       "2021-11-24 13:00:00-05:00  155.366898  1021886  90.915923  \n",
       "2021-11-24 13:15:00-05:00  155.650497  1160713  91.257493  \n",
       "2021-11-24 13:30:00-05:00  155.994995  1797823  91.667363  \n",
       "2021-11-24 13:45:00-05:00  155.671005  1290246  87.512011  \n",
       "2021-11-24 14:00:00-05:00  155.332001  2091453  83.259126  \n",
       "2021-11-24 14:15:00-05:00  155.054993  1260223  79.844579  \n",
       "2021-11-24 14:30:00-05:00  155.929993  1181077  82.312185  \n",
       "2021-11-24 14:45:00-05:00  156.309998  1558408  83.270133  \n",
       "2021-11-24 15:00:00-05:00  156.789993  1753262  84.418080  \n",
       "2021-11-24 15:15:00-05:00  157.029999  1449452  84.973295  \n",
       "2021-11-24 15:30:00-05:00  157.369995  2584528  85.748031  \n",
       "2021-11-24 15:45:00-05:00  157.779999  3277326  86.642398  \n",
       "2021-11-26 09:30:00-05:00  154.949799  5570381  59.080916  \n",
       "2021-11-26 09:45:00-05:00  157.421005  3478202  68.502514  \n",
       "2021-11-26 10:00:00-05:00  155.699997  2950795  58.415050  \n",
       "2021-11-26 10:15:00-05:00  156.249603  2189973  60.419566  \n",
       "2021-11-26 10:30:00-05:00  155.287399  2115265  55.386025  \n",
       "2021-11-26 10:45:00-05:00  155.009995  2369518  53.989537  \n",
       "2021-11-26 11:00:00-05:00  153.999893  1525855  49.131787  \n",
       "2021-11-26 11:15:00-05:00  153.770004  1969968  48.071673  \n",
       "2021-11-26 11:30:00-05:00  154.234207  1465703  50.398987  \n",
       "2021-11-26 11:45:00-05:00  154.509995  2074984  51.781644  \n",
       "2021-11-26 12:00:00-05:00  154.938004  1321109  53.928105  \n",
       "2021-11-26 12:15:00-05:00  155.949997  1653144  58.618665  \n",
       "2021-11-26 12:30:00-05:00  155.698898  2603152  57.066210  \n",
       "2021-11-26 12:45:00-05:00  154.889999  3618774  52.264212  \n",
       "2021-11-26 13:00:00-05:00  154.949997        0  52.582926  \n",
       "2021-11-29 09:30:00-05:00  158.759995  6783298  67.446685  \n",
       "2021-11-29 09:45:00-05:00  158.910004  3638047  67.873690  \n",
       "2021-11-29 10:00:00-05:00  158.850006  2789088  67.492367  \n",
       "2021-11-29 10:15:00-05:00  157.185501  2756871  57.791871  \n",
       "2021-11-29 10:30:00-05:00  157.029999  2972988  56.968098  \n",
       "2021-11-29 10:45:00-05:00  157.960007  3765303  60.586526  \n",
       "2021-11-29 11:00:00-05:00  158.162796  1754281  61.349703  \n",
       "2021-11-29 11:15:00-05:00  157.899994  1517994  59.735415  \n",
       "2021-11-29 11:30:00-05:00  159.080002  1822299  64.280245  \n",
       "2021-11-29 11:45:00-05:00  158.929993  1086505  63.302041  \n",
       "2021-11-29 12:00:00-05:00  159.190002  1594890  64.315686  \n",
       "2021-11-29 12:14:01-05:00  159.211304        0  64.402435  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To use this library we must convert the column we are using into a Numpy array\n",
    "# We will use the period of 14 as I stated\n",
    "amd_df['RSI'] = ta.RSI(np.array(amd_df['Close']), timeperiod=14)\n",
    "amd_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot RSI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
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        "plotlyServerURL": "https://plot.ly"
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       "            Plotly.purge(gd);\n",
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       "\n",
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     "metadata": {},
     "output_type": "display_data"
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   "source": [
    "fig = make_subplots(rows=2, cols=1, shared_xaxes=True, \n",
    "                    vertical_spacing=0.01,\n",
    "                   row_heights=[0.7, 0.3])\n",
    "\n",
    "candle = go.Candlestick(x=amd_df.index, open=amd_df['Open'],\n",
    "                       high=amd_df['High'], low=amd_df['Low'],\n",
    "                       close=amd_df['Close'], name='Candlestick')\n",
    "\n",
    "rsi = go.Scatter(x=amd_df.index, y=amd_df['RSI'], \n",
    "                 line=dict(color='blue', width=2))\n",
    "\n",
    "fig.add_trace(candle, row=1, col=1)  \n",
    "fig.add_trace(rsi, row=2, col=1) \n",
    "\n",
    "# Draw 20 and 80 lines\n",
    "fig.add_hline(y=30, line_width=1, line_dash=\"dash\", line_color=\"red\", row=2, col=1)\n",
    "fig.add_hline(y=70, line_width=1, line_dash=\"dash\", line_color=\"green\", row=2, col=1)\n",
    "\n",
    "# Add title\n",
    "fig.update_layout(title=\"AMD\")\n",
    "\n",
    "# Get rid of empty dates and market closed\n",
    "fig.update_layout(height=900, width=1200, \n",
    "                  showlegend=False, \n",
    "                  xaxis_rangeslider_visible=False,\n",
    "                  xaxis_rangebreaks=[\n",
    "            dict(bounds=[\"sat\", \"mon\"]),\n",
    "            dict(bounds=[16, 9.5], pattern=\"hour\"), \n",
    "            dict(values=[\"2021-12-25\", \"2022-01-01\"])\n",
    "        ])\n",
    "                                            \n",
    "fig.show()"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bollinger Bands"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bollinger Bands plot 2 lines using a moving average and the standard deviation defines how far apart the lines are. They also are used to define if prices are to high or low. When bands tighten it is believed a sharp price move in some direction. Prices tend to bounce off of the bands which provides potential market actions. \n",
    "\n",
    "A strong trend should be noted if the price moves outside the band. If prices go over the resistance line it is in overbought territory and if it breaks through support it is a sign of an oversold position.\n",
    "\n",
    "You normally use 20 sessions when using them. \n",
    " - High Band (Resistance) = Simple Moving Average + 2 * Standard Deviation\n",
    " - Low Band (Support) = Simple Moving Average - 2 * Standard Deviation"
   ]
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   ],
   "source": [
    "# Use Cufflinks QuantFigure Module to create Bollinger Bands\n",
    "# add_sma - Simple Moving Average\n",
    "# add_ema() - Exponential Moving Average\n",
    "# add_trendline() - Trend line\n",
    "# add_support() - Support line\n",
    "# add_rsi - Relative Strength Indicator\n",
    "# add_adx - Average Directional Index\n",
    "# add_atr() - Average True Range\n",
    "# add_macd() - Moving Average Convergence Divergence\n",
    "# add_bollinger_bands - Bollinger Bands\n",
    "# add_volume - Volume bars\n",
    "# add_cci() - Commodity Channel Indicator\n",
    "# add_dmi() - Directional Movement Index\n",
    "# add_ptps() - Parabolic SAR\n",
    "# add_resistance() - Resistance line\n",
    "msft_df = yf.download(tickers=\"MSFT\", period=\"6mo\", interval='1d')\n",
    "msft_df\n",
    "\n",
    "qf=cf.QuantFig(msft_df, title='MSFT Quant Figure',legend='top',name='GS')\n",
    "qf.add_bollinger_bands()\n",
    "qf.add_volume()\n",
    "\n",
    "qf.iplot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hand Code Bollinger Bands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
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       "      <th>2021-06-01</th>\n",
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       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2021-06-01  251.229996  251.289993  246.960007  247.399994  246.476334   \n",
       "2021-06-02  248.130005  249.270004  245.839996  247.300003  246.376724   \n",
       "2021-06-03  245.220001  246.339996  243.000000  245.710007  244.792679   \n",
       "2021-06-04  247.759995  251.649994  247.509995  250.789993  249.853699   \n",
       "2021-06-07  249.979996  254.089996  249.809998  253.809998  252.862411   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2021-11-22  344.619995  349.670013  339.549988  339.829987  339.829987   \n",
       "2021-11-23  337.049988  339.450012  333.559998  337.679993  337.679993   \n",
       "2021-11-24  336.279999  338.160004  333.910004  337.910004  337.910004   \n",
       "2021-11-26  334.350006  337.929993  328.119995  329.679993  329.679993   \n",
       "2021-11-29  334.940002  339.029999  334.750000  337.820007  337.820007   \n",
       "\n",
       "              Volume        Mean  \n",
       "Date                              \n",
       "2021-06-01  23213300         NaN  \n",
       "2021-06-02  19406700         NaN  \n",
       "2021-06-03  25307700         NaN  \n",
       "2021-06-04  25281100         NaN  \n",
       "2021-06-07  23079200         NaN  \n",
       "...              ...         ...  \n",
       "2021-11-22  31031100  333.502498  \n",
       "2021-11-23  30427600  334.880998  \n",
       "2021-11-24  21661300  335.617998  \n",
       "2021-11-26  24217200  335.884497  \n",
       "2021-11-29  12621536  336.194498  \n",
       "\n",
       "[127 rows x 7 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get rolling mean\n",
    "msft_df['Mean'] = msft_df['Close'].rolling(window=20).mean()\n",
    "msft_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <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",
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       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-06-01</th>\n",
       "      <td>251.229996</td>\n",
       "      <td>251.289993</td>\n",
       "      <td>246.960007</td>\n",
       "      <td>247.399994</td>\n",
       "      <td>246.476334</td>\n",
       "      <td>23213300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-02</th>\n",
       "      <td>248.130005</td>\n",
       "      <td>249.270004</td>\n",
       "      <td>245.839996</td>\n",
       "      <td>247.300003</td>\n",
       "      <td>246.376724</td>\n",
       "      <td>19406700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-03</th>\n",
       "      <td>245.220001</td>\n",
       "      <td>246.339996</td>\n",
       "      <td>243.000000</td>\n",
       "      <td>245.710007</td>\n",
       "      <td>244.792679</td>\n",
       "      <td>25307700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-04</th>\n",
       "      <td>247.759995</td>\n",
       "      <td>251.649994</td>\n",
       "      <td>247.509995</td>\n",
       "      <td>250.789993</td>\n",
       "      <td>249.853699</td>\n",
       "      <td>25281100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-07</th>\n",
       "      <td>249.979996</td>\n",
       "      <td>254.089996</td>\n",
       "      <td>249.809998</td>\n",
       "      <td>253.809998</td>\n",
       "      <td>252.862411</td>\n",
       "      <td>23079200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-22</th>\n",
       "      <td>344.619995</td>\n",
       "      <td>349.670013</td>\n",
       "      <td>339.549988</td>\n",
       "      <td>339.829987</td>\n",
       "      <td>339.829987</td>\n",
       "      <td>31031100</td>\n",
       "      <td>333.502498</td>\n",
       "      <td>7.531645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-23</th>\n",
       "      <td>337.049988</td>\n",
       "      <td>339.450012</td>\n",
       "      <td>333.559998</td>\n",
       "      <td>337.679993</td>\n",
       "      <td>337.679993</td>\n",
       "      <td>30427600</td>\n",
       "      <td>334.880998</td>\n",
       "      <td>5.181061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24</th>\n",
       "      <td>336.279999</td>\n",
       "      <td>338.160004</td>\n",
       "      <td>333.910004</td>\n",
       "      <td>337.910004</td>\n",
       "      <td>337.910004</td>\n",
       "      <td>21661300</td>\n",
       "      <td>335.617998</td>\n",
       "      <td>4.419983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26</th>\n",
       "      <td>334.350006</td>\n",
       "      <td>337.929993</td>\n",
       "      <td>328.119995</td>\n",
       "      <td>329.679993</td>\n",
       "      <td>329.679993</td>\n",
       "      <td>24217200</td>\n",
       "      <td>335.884497</td>\n",
       "      <td>3.825542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29</th>\n",
       "      <td>334.940002</td>\n",
       "      <td>339.029999</td>\n",
       "      <td>334.750000</td>\n",
       "      <td>337.820007</td>\n",
       "      <td>337.820007</td>\n",
       "      <td>12621536</td>\n",
       "      <td>336.194498</td>\n",
       "      <td>3.711283</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>127 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2021-06-01  251.229996  251.289993  246.960007  247.399994  246.476334   \n",
       "2021-06-02  248.130005  249.270004  245.839996  247.300003  246.376724   \n",
       "2021-06-03  245.220001  246.339996  243.000000  245.710007  244.792679   \n",
       "2021-06-04  247.759995  251.649994  247.509995  250.789993  249.853699   \n",
       "2021-06-07  249.979996  254.089996  249.809998  253.809998  252.862411   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2021-11-22  344.619995  349.670013  339.549988  339.829987  339.829987   \n",
       "2021-11-23  337.049988  339.450012  333.559998  337.679993  337.679993   \n",
       "2021-11-24  336.279999  338.160004  333.910004  337.910004  337.910004   \n",
       "2021-11-26  334.350006  337.929993  328.119995  329.679993  329.679993   \n",
       "2021-11-29  334.940002  339.029999  334.750000  337.820007  337.820007   \n",
       "\n",
       "              Volume        Mean        SD  \n",
       "Date                                        \n",
       "2021-06-01  23213300         NaN       NaN  \n",
       "2021-06-02  19406700         NaN       NaN  \n",
       "2021-06-03  25307700         NaN       NaN  \n",
       "2021-06-04  25281100         NaN       NaN  \n",
       "2021-06-07  23079200         NaN       NaN  \n",
       "...              ...         ...       ...  \n",
       "2021-11-22  31031100  333.502498  7.531645  \n",
       "2021-11-23  30427600  334.880998  5.181061  \n",
       "2021-11-24  21661300  335.617998  4.419983  \n",
       "2021-11-26  24217200  335.884497  3.825542  \n",
       "2021-11-29  12621536  336.194498  3.711283  \n",
       "\n",
       "[127 rows x 8 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get rolling standard deviation\n",
    "msft_df['SD'] = msft_df['Close'].rolling(window=20).std()\n",
    "msft_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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",
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       "      <th>BB_Low</th>\n",
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       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>2021-06-01</th>\n",
       "      <td>251.229996</td>\n",
       "      <td>251.289993</td>\n",
       "      <td>246.960007</td>\n",
       "      <td>247.399994</td>\n",
       "      <td>246.476334</td>\n",
       "      <td>23213300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-02</th>\n",
       "      <td>248.130005</td>\n",
       "      <td>249.270004</td>\n",
       "      <td>245.839996</td>\n",
       "      <td>247.300003</td>\n",
       "      <td>246.376724</td>\n",
       "      <td>19406700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-03</th>\n",
       "      <td>245.220001</td>\n",
       "      <td>246.339996</td>\n",
       "      <td>243.000000</td>\n",
       "      <td>245.710007</td>\n",
       "      <td>244.792679</td>\n",
       "      <td>25307700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-04</th>\n",
       "      <td>247.759995</td>\n",
       "      <td>251.649994</td>\n",
       "      <td>247.509995</td>\n",
       "      <td>250.789993</td>\n",
       "      <td>249.853699</td>\n",
       "      <td>25281100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-07</th>\n",
       "      <td>249.979996</td>\n",
       "      <td>254.089996</td>\n",
       "      <td>249.809998</td>\n",
       "      <td>253.809998</td>\n",
       "      <td>252.862411</td>\n",
       "      <td>23079200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-22</th>\n",
       "      <td>344.619995</td>\n",
       "      <td>349.670013</td>\n",
       "      <td>339.549988</td>\n",
       "      <td>339.829987</td>\n",
       "      <td>339.829987</td>\n",
       "      <td>31031100</td>\n",
       "      <td>333.502498</td>\n",
       "      <td>7.531645</td>\n",
       "      <td>348.565788</td>\n",
       "      <td>318.439208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-23</th>\n",
       "      <td>337.049988</td>\n",
       "      <td>339.450012</td>\n",
       "      <td>333.559998</td>\n",
       "      <td>337.679993</td>\n",
       "      <td>337.679993</td>\n",
       "      <td>30427600</td>\n",
       "      <td>334.880998</td>\n",
       "      <td>5.181061</td>\n",
       "      <td>345.243120</td>\n",
       "      <td>324.518876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-24</th>\n",
       "      <td>336.279999</td>\n",
       "      <td>338.160004</td>\n",
       "      <td>333.910004</td>\n",
       "      <td>337.910004</td>\n",
       "      <td>337.910004</td>\n",
       "      <td>21661300</td>\n",
       "      <td>335.617998</td>\n",
       "      <td>4.419983</td>\n",
       "      <td>344.457964</td>\n",
       "      <td>326.778031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-26</th>\n",
       "      <td>334.350006</td>\n",
       "      <td>337.929993</td>\n",
       "      <td>328.119995</td>\n",
       "      <td>329.679993</td>\n",
       "      <td>329.679993</td>\n",
       "      <td>24217200</td>\n",
       "      <td>335.884497</td>\n",
       "      <td>3.825542</td>\n",
       "      <td>343.535580</td>\n",
       "      <td>328.233414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-29</th>\n",
       "      <td>334.940002</td>\n",
       "      <td>339.029999</td>\n",
       "      <td>334.750000</td>\n",
       "      <td>337.820007</td>\n",
       "      <td>337.820007</td>\n",
       "      <td>12621536</td>\n",
       "      <td>336.194498</td>\n",
       "      <td>3.711283</td>\n",
       "      <td>343.617064</td>\n",
       "      <td>328.771931</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>127 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2021-06-01  251.229996  251.289993  246.960007  247.399994  246.476334   \n",
       "2021-06-02  248.130005  249.270004  245.839996  247.300003  246.376724   \n",
       "2021-06-03  245.220001  246.339996  243.000000  245.710007  244.792679   \n",
       "2021-06-04  247.759995  251.649994  247.509995  250.789993  249.853699   \n",
       "2021-06-07  249.979996  254.089996  249.809998  253.809998  252.862411   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2021-11-22  344.619995  349.670013  339.549988  339.829987  339.829987   \n",
       "2021-11-23  337.049988  339.450012  333.559998  337.679993  337.679993   \n",
       "2021-11-24  336.279999  338.160004  333.910004  337.910004  337.910004   \n",
       "2021-11-26  334.350006  337.929993  328.119995  329.679993  329.679993   \n",
       "2021-11-29  334.940002  339.029999  334.750000  337.820007  337.820007   \n",
       "\n",
       "              Volume        Mean        SD       BB_Hi      BB_Low  \n",
       "Date                                                                \n",
       "2021-06-01  23213300         NaN       NaN         NaN         NaN  \n",
       "2021-06-02  19406700         NaN       NaN         NaN         NaN  \n",
       "2021-06-03  25307700         NaN       NaN         NaN         NaN  \n",
       "2021-06-04  25281100         NaN       NaN         NaN         NaN  \n",
       "2021-06-07  23079200         NaN       NaN         NaN         NaN  \n",
       "...              ...         ...       ...         ...         ...  \n",
       "2021-11-22  31031100  333.502498  7.531645  348.565788  318.439208  \n",
       "2021-11-23  30427600  334.880998  5.181061  345.243120  324.518876  \n",
       "2021-11-24  21661300  335.617998  4.419983  344.457964  326.778031  \n",
       "2021-11-26  24217200  335.884497  3.825542  343.535580  328.233414  \n",
       "2021-11-29  12621536  336.194498  3.711283  343.617064  328.771931  \n",
       "\n",
       "[127 rows x 10 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "msft_df['BB_Hi'] = msft_df['Mean'] + (2 * msft_df['SD'])\n",
    "msft_df['BB_Low'] = msft_df['Mean'] - (2 * msft_df['SD'])\n",
    "msft_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     },
     "metadata": {},
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   ],
   "source": [
    "fig = go.Figure()\n",
    "\n",
    "# Define candlestick and moving average lines\n",
    "candle = go.Candlestick(x=msft_df.index, open=msft_df['Open'],\n",
    "                       high=msft_df['High'], low=msft_df['Low'],\n",
    "                       close=msft_df['Close'], name='Candlestick')\n",
    "bb_hi = go.Scatter(x=msft_df.index, y=msft_df['BB_Hi'], \n",
    "                   line=dict(color='green', width=1), name=\"BB Hi\")\n",
    "\n",
    "bb_low = go.Scatter(x=msft_df.index, y=msft_df['BB_Low'], \n",
    "                  line=dict(color='orange', width=1), name=\"BB Low\")\n",
    "\n",
    "# Add plots to the figure\n",
    "fig.add_trace(candle)\n",
    "fig.add_trace(bb_hi)\n",
    "fig.add_trace(bb_low)      \n",
    "\n",
    "# Add title\n",
    "fig.update_layout(title=\"MSFT\")\n",
    "\n",
    "# Get rid of empty dates on the weekend\n",
    "fig.update_xaxes(rangebreaks=[dict(bounds=[\"sat\", \"mon\"])])\n",
    "                                            \n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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