This project deals with understanding how covid-19 has impacted the stock market. For our analysis we have considered 50 companies from various secotrs. All 50 stocks are dealt in NASDAQ/NYSE market which are of mostly large & mid cap stocks and a few small caps as well and we have tried to study the impact of 2007-09 economic recession and the current pandemic on all the following stocks. And predict the nature of the stocks if not for the pandemic.
There are stocks from all categories:
Energy
Materials
Industrials
Utilities
Healthcare
Financials
Consumer Discretionary
Consumer Staples
Information Technology
Communication Services
Real Estate
'AXP'-American Express Financial services
'AAPL'-Apple Technology
'AMZN'-Amazon.com E-commerce
'ADBE'-Adobe Computer software
'ADS'-Alliance Data Systems Corporation
'BA'-Boeing Aerospace
'BAC'-Bank of America Investment banking
'CAT'-Caterpillar Inc. Construction machinery and equipment
'CVX'-Chevron Corporation Oil industry
'CSCO'-Cisco Systems Networking hardware
'COST'-Costco Retail
'DIS'-The Walt Disney Company Mass media
'FB'-Facebook Social Media
'GE'-General Electric Multinational conglomerate
'GS'-Goldman Sachs Investment banking
'GOOGL'-Alphabet Inc. Multinational conglomerate
'HD-The Home Depot Home improvement'
'HDB'-HDFC Bank Financial services
'HOG'-Harley-Davidson motorcycle manufacturer
'IBM'-IBM Computer hardware
'INTC'-Intel Semiconductor
'INFY'-Infosys Information technology consulting
'JNJ'-Johnson & Johnson Medical device
'JPM'-JPMorgan Chase Investment banking
'JBHT'-J.B. Hunt Transportation and Logistics
'KO'-The Coca-Cola Company Beverages
'KEX'-Kirby Corporation Transportation
'MCD'-McDonald's Fast food
'MSFT'-Microsoft Corporation Technology
'MMM'-3M Multinational conglomerate
'MRK'-Merck & Co. Pharmaceutical
'NFLX'-Netflix Production
'NKE'-Nike Footwear manufacturing
'NVDA'-Nvidia Computer Hardware and Software
'PFE'-Pfizer Pharmaceutical
'PG'-Procter & Gamble Consumer Goods
'PEP'-PepsiCo Food
'REGN'-Regeneron Pharmaceuticals Biotechnology
'SBUX'-Starbucks Coffeehouse
'TRV'-The Travelers Companies Insurance
'TGT'-Target Corporation Retail
'T'-AT&T Telecommunications
'UTX'-Raytheon Technologies Corporation Aircraft manufacturing
'UNH'-UnitedHealth Group Managed care
'UPS'-United Parcel Service Logistics
'UNP'-Union Pacific Corporation Transport
'VZ'-Verizon Communications Telecommunications
'WMT'-Walmart Retail
'XOM'-ExxonMobil multinational oil and gas
'YUM'-Yum! Brands Fast food
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|-- data
| |-- ..
|-- src
| |-- data_collection.ipynb
| |-- eda.ipynb
| |-- arima.ipynb
| |-- rnn.ipynb
| |-- arima_lstm_hybrid.ipynb
src contains all notebooks which contain the source for the project.
3 models have been used to analysie and make predictions for the dataset.All models used can be found under the src directory.
The naming convention for the models are as follows : <model_name>.ipynb
This project has multiple requirements which need to be installed in order to run the source files.
Most of the requirements can be installed by using the requirements.txt file. To install these requirements type:
pip install -r requirements.txt
Another library we have used is the Technical Analysis library. Sometimes this gives an error if we directly try to install it via pip. Hence follow the steps to install the TA-Lib:
wget https://launchpad.net/~mario-mariomedina/+archive/ubuntu/talib/+files/libta-lib0_0.4.0-oneiric1_amd64.deb -qO libta.deb
wget https://launchpad.net/~mario-mariomedina/+archive/ubuntu/talib/+files/ta-lib0-dev_0.4.0-oneiric1_amd64.deb -qO ta.deb
dpkg -i libta.deb ta.deb
pip install TA-Lib==0.4.17
All notebooks were created and executed on Google Colab and the contained source code can be executed.
Note: Before executing the soruce code on google colab make sure you have uploaded the data onto your drive.