Benjamin Graham and Warren Buffett Model Stock-Exchange

Introduction:

• There are about 4000 stocks which are actively traded on the stock exchanges at BSE and NSE.
• We can extract public financial data from sites like to find which are the fundamentally strong stocks.
• On what stocks would the father of value investing, Benjamin Graham and Warren Buffett the most successful investors in the world make their investments on.

Benjamin Graham and Warren Buffett Model:

1. Step 1: Filtering out all companies with sales less than Rs 250 cr. Companies with sales lower than this are very small companies and might not have the business stability and access to finance that is required for a safe investment. This eliminates the basic business risk.
2. Step 2: Filtering out all companies with debt to equity greater than 30%. Companies with low leverage are safer.
3. Step 3: Filtering out all companies with interest coverage ratio of less than 4. Companies with high interest coverage ratio have a highly reduced bankruptcy risk.
4. Step 4: Filtering out all companies with ROE less than 15% since they are earning less than their cost of capital. High ROE companies have a robust business model, which generates increased earnings for the company typically.
5. Step 5: Filtering out all companies with PE ratio greater than 25 since they are too expensive even for a high-quality company. This enables us to pick companies which are relatively cheaper as against their actual value. He points out that applying these filters enables us to reduce and even eliminate a lot of fundamental risks while ensuring a robust business model, strong earning potential and a good buying price.

IMPORTANT!!

• If you would like to find the performance of different companies as per your choice apart from those in the 'Companies.csv' file, just add your required company's MoneyControl Balance Sheet link as per the format shown in the csv file.

Note:

• These values and filteration process is dynamic.
• The data and values in the notebook might change based on the company's performance in the stock market.
• This filter can be applied for any company.
• Data can be created accordingly and can be extracted from multiple websites for multiple companies.