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viewing stock price slopes
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{"cells":[{"cell_type":"markdown","metadata":{"id":"cEGf_vPrhNa6"},"source":["### This is a Tutorial Notebook to get started with CTO as soon as possible, without any frills\n","- We will be attempting to view stock price slopes\n","- Prequisites:\n"," - pip install all requirements as in the requirements.txt\n"," - Navigate to https://zenodo.org/doi/10.5281/zenodo.11535960 (this link always resolves to the latest version), and download the latest version of CTO!\n"," I downloaded the v0.3 supplementary.zip, and unzipped it in the parent directory.\n"," ```bash\n"," wget https://zenodo.org/records/11608615/files/supplementary.zip -P ../\n"," unzip ../supplementary.zip -d ../\n"," ```\n"," - Follow the setup instructions in stock_price\n","\n","- Slope calculation in stock_price/slope_calculation.ipynb"]},{"cell_type":"code","execution_count":2,"metadata":{"id":"hQBfgx63hNa_","outputId":"3b102a3d-b274-403b-e614-12147e4d5ca4"},"outputs":[{"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>nct_id</th>\n"," <th>Ticker</th>\n"," <th>name</th>\n"," <th>Slope</th>\n"," </tr>\n"," </thead>\n"," <tbody>\n"," <tr>\n"," <th>0</th>\n"," <td>NCT04023084</td>\n"," <td>PFE</td>\n"," <td>Pfizer</td>\n"," <td>-0.275547</td>\n"," </tr>\n"," <tr>\n"," <th>1</th>\n"," <td>NCT01656278</td>\n"," <td>ABT</td>\n"," <td>Abbott</td>\n"," <td>0.108502</td>\n"," </tr>\n"," <tr>\n"," <th>2</th>\n"," <td>NCT03267732</td>\n"," <td>LLY</td>\n"," <td>Eli Lilly and Company</td>\n"," <td>0.256033</td>\n"," </tr>\n"," <tr>\n"," <th>3</th>\n"," <td>NCT02456844</td>\n"," <td>BMY</td>\n"," <td>Bristol-Myers Squibb</td>\n"," <td>-0.252119</td>\n"," </tr>\n"," <tr>\n"," <th>4</th>\n"," <td>NCT03259542</td>\n"," <td>CORT</td>\n"," <td>Corcept Therapeutics</td>\n"," <td>-0.152000</td>\n"," </tr>\n"," <tr>\n"," <th>...</th>\n"," <td>...</td>\n"," <td>...</td>\n"," <td>...</td>\n"," <td>...</td>\n"," </tr>\n"," <tr>\n"," <th>19879</th>\n"," <td>NCT01431898</td>\n"," <td>GILD</td>\n"," <td>Gilead Sciences</td>\n"," <td>0.037673</td>\n"," </tr>\n"," <tr>\n"," <th>19880</th>\n"," <td>NCT01445119</td>\n"," <td>LLY</td>\n"," <td>Eli Lilly and Company</td>\n"," <td>0.033443</td>\n"," </tr>\n"," <tr>\n"," <th>19881</th>\n"," <td>NCT01730339</td>\n"," <td>PFE</td>\n"," <td>Pfizer</td>\n"," <td>0.023169</td>\n"," </tr>\n"," <tr>\n"," <th>19882</th>\n"," <td>NCT01509755</td>\n"," <td>NVO</td>\n"," <td>Novo Nordisk A/S</td>\n"," <td>-0.009617</td>\n"," </tr>\n"," <tr>\n"," <th>19883</th>\n"," <td>NCT01630746</td>\n"," <td>TAK</td>\n"," <td>Takeda</td>\n"," <td>-0.034800</td>\n"," </tr>\n"," </tbody>\n","</table>\n","<p>19884 rows × 4 columns</p>\n","</div>"],"text/plain":[" nct_id Ticker name Slope\n","0 NCT04023084 PFE Pfizer -0.275547\n","1 NCT01656278 ABT Abbott 0.108502\n","2 NCT03267732 LLY Eli Lilly and Company 0.256033\n","3 NCT02456844 BMY Bristol-Myers Squibb -0.252119\n","4 NCT03259542 CORT Corcept Therapeutics -0.152000\n","... ... ... ... ...\n","19879 NCT01431898 GILD Gilead Sciences 0.037673\n","19880 NCT01445119 LLY Eli Lilly and Company 0.033443\n","19881 NCT01730339 PFE Pfizer 0.023169\n","19882 NCT01509755 NVO Novo Nordisk A/S -0.009617\n","19883 NCT01630746 TAK Takeda -0.034800\n","\n","[19884 rows x 4 columns]"]},"execution_count":2,"metadata":{},"output_type":"execute_result"}],"source":["# ============ loading the zipped data, viewing all collected tickers, company names and slopes at completion date ============\n","import numpy as np\n","import pandas as pd\n","import os\n","import glob\n","import yfinance as yf\n","\n","slope_df = pd.read_csv('../supplementary/stock_price/labels_and_tickers.csv', index_col=0)\n","slope_df[['nct_id', 'Ticker', 'name', 'Slope']]"]},{"cell_type":"markdown","metadata":{},"source":["looking at the stock price records of a specific company"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[{"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>Volume</th>\n"," <th>Dividends</th>\n"," <th>Stock Splits</th>\n"," </tr>\n"," <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"," </tr>\n"," </thead>\n"," <tbody>\n"," <tr>\n"," <th>1972-06-01 00:00:00-04:00</th>\n"," <td>0.000000</td>\n"," <td>0.163931</td>\n"," <td>0.161448</td>\n"," <td>0.163931</td>\n"," <td>2458771</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," <tr>\n"," <th>1972-06-02 00:00:00-04:00</th>\n"," <td>0.163931</td>\n"," <td>0.164428</td>\n"," <td>0.161448</td>\n"," <td>0.161944</td>\n"," <td>1613885</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," <tr>\n"," <th>1972-06-05 00:00:00-04:00</th>\n"," <td>0.161944</td>\n"," <td>0.162441</td>\n"," <td>0.160454</td>\n"," <td>0.161448</td>\n"," <td>2585251</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," <tr>\n"," <th>1972-06-06 00:00:00-04:00</th>\n"," <td>0.161448</td>\n"," <td>0.165918</td>\n"," <td>0.160951</td>\n"," <td>0.164925</td>\n"," <td>2347469</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," <tr>\n"," <th>1972-06-07 00:00:00-04:00</th>\n"," <td>0.164925</td>\n"," <td>0.164925</td>\n"," <td>0.162441</td>\n"," <td>0.164925</td>\n"," <td>1032077</td>\n"," <td>0.0</td>\n"," <td>0.0</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"," <td>...</td>\n"," </tr>\n"," <tr>\n"," <th>2024-06-28 00:00:00-04:00</th>\n"," <td>27.780001</td>\n"," <td>28.120001</td>\n"," <td>27.639999</td>\n"," <td>27.980000</td>\n"," <td>33189200</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," <tr>\n"," <th>2024-07-01 00:00:00-04:00</th>\n"," <td>27.950001</td>\n"," <td>28.629999</td>\n"," <td>27.940001</td>\n"," <td>28.219999</td>\n"," <td>26209000</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," <tr>\n"," <th>2024-07-02 00:00:00-04:00</th>\n"," <td>28.219999</td>\n"," <td>28.280001</td>\n"," <td>27.690001</td>\n"," <td>27.830000</td>\n"," <td>21989800</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," <tr>\n"," <th>2024-07-03 00:00:00-04:00</th>\n"," <td>27.920000</td>\n"," <td>28.049999</td>\n"," <td>27.620001</td>\n"," <td>27.700001</td>\n"," <td>15180100</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," <tr>\n"," <th>2024-07-05 00:00:00-04:00</th>\n"," <td>27.760000</td>\n"," <td>28.090000</td>\n"," <td>27.670000</td>\n"," <td>28.049999</td>\n"," <td>17259500</td>\n"," <td>0.0</td>\n"," <td>0.0</td>\n"," </tr>\n"," </tbody>\n","</table>\n","<p>13135 rows × 7 columns</p>\n","</div>"],"text/plain":[" Open High Low Close \\\n","Date \n","1972-06-01 00:00:00-04:00 0.000000 0.163931 0.161448 0.163931 \n","1972-06-02 00:00:00-04:00 0.163931 0.164428 0.161448 0.161944 \n","1972-06-05 00:00:00-04:00 0.161944 0.162441 0.160454 0.161448 \n","1972-06-06 00:00:00-04:00 0.161448 0.165918 0.160951 0.164925 \n","1972-06-07 00:00:00-04:00 0.164925 0.164925 0.162441 0.164925 \n","... ... ... ... ... \n","2024-06-28 00:00:00-04:00 27.780001 28.120001 27.639999 27.980000 \n","2024-07-01 00:00:00-04:00 27.950001 28.629999 27.940001 28.219999 \n","2024-07-02 00:00:00-04:00 28.219999 28.280001 27.690001 27.830000 \n","2024-07-03 00:00:00-04:00 27.920000 28.049999 27.620001 27.700001 \n","2024-07-05 00:00:00-04:00 27.760000 28.090000 27.670000 28.049999 \n","\n"," Volume Dividends Stock Splits \n","Date \n","1972-06-01 00:00:00-04:00 2458771 0.0 0.0 \n","1972-06-02 00:00:00-04:00 1613885 0.0 0.0 \n","1972-06-05 00:00:00-04:00 2585251 0.0 0.0 \n","1972-06-06 00:00:00-04:00 2347469 0.0 0.0 \n","1972-06-07 00:00:00-04:00 1032077 0.0 0.0 \n","... ... ... ... \n","2024-06-28 00:00:00-04:00 33189200 0.0 0.0 \n","2024-07-01 00:00:00-04:00 26209000 0.0 0.0 \n","2024-07-02 00:00:00-04:00 21989800 0.0 0.0 \n","2024-07-03 00:00:00-04:00 15180100 0.0 0.0 \n","2024-07-05 00:00:00-04:00 17259500 0.0 0.0 \n","\n","[13135 rows x 7 columns]"]},"execution_count":6,"metadata":{},"output_type":"execute_result"}],"source":["#example ticker to get historical data. We used PFE (Pfizer Inc.) for the analysis\n","ticker = 'PFE'\n","\n","stock = yf.Ticker(ticker)\n","\n","# Retrieve historical market data\n","hist = stock.history(period=\"max\")\n","\n","#print(hist)\n","hist\n"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["#we used 'Close' price for the analysis in the paper"]}],"metadata":{"colab":{"provenance":[]},"kernelspec":{"display_name":"dp","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.9.7"}},"nbformat":4,"nbformat_minor":0}

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