SEC Filing Analyzer is an app for analysing EDGAR SEC filing data.
Submission for the Inter-IIT Tech Meet's High Prep event: Digital Alpha's SEC Filing Analyzer for SaaS Companies
To deploy this project run
- Step 1 - Clone the repository
git clone https://github.com/joetho786/SEC_file_analyzer.git
- Step 2 - make a virtual environment to run the code unhindered
virtualenv venv
- Step 3 - activate virtual environment
source venv/bin/activate
- Step 4 - change the directory
cd SEC_filing_analyser
- Step 5 - install all dependencies and make Migration
- pip install -r requirements.txt - python manage.py makemigrations - python manage.py migrate
- Step 6 - Run server
python manage.py runserver
- Step 7 - Integrate the data
- go to http://127.0.0.1:8000/import-csv/ - Then upload the dataset.csv file and submit - Again go to http://127.0.0.1:8000/
- Now the Dashboard is Complete and ready to use.
- We displayed links of the filings of 10-K, 10-Q and 8-K in the dashboard.
- We used Amazon based AWS SageMaker API and used inbuilt
NLPScorer()
,JaccardSummarizerConfig()
,KMedoidsSummarizerConfig()
,SECXMLFilingParser()
functions to do the sentiment Analysis which resulted in getting positivity, negativity, certainity, uncertainity, risk, safe, litigous, fraud, sentiment, polarity, readability. - The plot for sentiment scores of each company has been displayed on its corresponding page.
- We used single call API provided by SageMaker named
EDGARDatasetConfig()
andDataLoader()
for making dataset of numerous companies thorugh their tickers or CIK numbers. - After that, we converted the datset into CSV file and stored it on S3 bucket.
We hosted our website in a EC2 instance in AWS.
- We used selenium to automate browser to excel file for every CIK number by searching that CIK number on
https://www.sec.gov/edgar/searchedgar/companysearch.html
. - These files were merged together to one by using
pandas
python package in format of CIK number v/s year of filing for displaying the links on the dashboard.
You can download the assets and Shares data through the column given
- Download the Assets Data
- Download the Shares Data.
Members:
- Aditya Soni
- Akshat Jain
- Saahil Bhavsar
- Jaimin Gajjar
- Jayant Kataria
- Joel Thomas
- Mohit Mathuria