Bloomberg provides access to real-time data, news, analytics on global financial markets, and cutting-edge financial analysis tools. It also provides information on every asset class – from fixed income to equities, foreign exchange to commodities, derivatives to mortgages. It seamlessly integrates real-time and historical information on bonds, equities, commodities, currencies, and funds. Bloomberg’s research insights help understand driving forces behind movements in major asset classes, credit metrics, economics, and policies. 

Refinitiv Eikon provides access to comprehensive historical financial data and economic information with securities and indicators for over 175 countries in 60 markets for the past 50 years

Covering both developed and emerging markets, the data includes bonds, commodities and derivatives, company accounts, equities, futures, and options. Eikon also covers interest and exchange rates, international macroeconomics, market indices, unit, and investment trusts. Eikon allows the user to export data and charts into Excel, PowerPoint or Word.

Morningstar Direct is a web-based research platform, which provides access to comprehensive data and independent analysis on thousands of investments, spanning mutual funds, stocks, exchange-traded funds, open-end funds, and closed-end funds. The platform supports competitive analysis, performance evaluation, and portfolio creation.

The database provides additional feature - Morningstar Add-In, which allows the user retrieve various types of data points from the Morningstar databases within Microsoft Excel for further calculation, formatting or charting.

We have procured annual reports of listed companies in India (in pdf format) for approximately 20 years.

This dataset captures all corporate filings made by companies to MCA. The dataset contains folders for each company with scanned files (image) on annual returns and balance sheet forms, certificates, change in directors, charge documents, incorporation documents etc.

The dataset contains quarterly data on index constituents (including weights) of the following five S&P indices, from the respective start dates till Sep-2021

1. S&P 500:                    
2. S&P Midcap 400
3. S&P Smallcap 600 
4. S&P 500 Growth  
5. S&P 500 Value       

This dataset covers account level data of PMJDY and saving account holders from a public sector bank. The demographic information of the savers is also obtained in the data collection process. It also covers the data relating to all the loans sanctioned by eleven bank branches at a daily level.

A Non-Disclosure Agreement and an Indemnity Agreement needs to be signed to obtain this data.

This is a PAN India database covering loan repayment data for eight different loan types* for the years 2017 to 2020. The data is available at quarterly intervals. The data is at a district, lender type and area type (Rural, Semi-Rural and Urban).

*Loan types:

1. Kisan Credit Card 
2. Micro Finance Institution 
3. Business Loan 
4. Consumer Loan 
5. Household Loan 
6. Personal Loan 
7. Tractor Loan 
8. Two-Wheeler Loans 

A Non-Disclosure Agreement and an Indemnity Agreement needs to be signed to obtain this data.

This is a PAN India database covering daily transaction level data for the years 2015 to 2020.

A Non-Disclosure Agreement and an Indemnity Agreement needs to be signed to obtain this data.

This is a PAN India database covering individual loan application and performance details of over 10,000 customers for the years 2017 to 2020.

A Non-Disclosure Agreement and an Indemnity Agreement needs to be signed to obtain this data.

This is a PAN India database covering individual loan performance data. The data is available for the years 2016 to 2019. 

A Non-Disclosure Agreement and an Indemnity Agreement needs to be signed to obtain this data.

This database includes data on over 4 lakh low-income households in Tamil Nadu, Orissa, and Uttarakhand between 2008 and 2015, enlisted with Kshetriya Gramin Financial Services (KGFS), a rural financial institution. These datasets are primarily derived from the administrative database of KGFS, with Household Demographics, Customer Engagement (Products and transactions), and Product-Specific Information.

A Non-Disclosure Agreement and an Indemnity Agreement needs to be signed to obtain this data.

The National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE) are the two most significant stock exchanges in India, and between them, are responsible for the majority of share transactions. Specifically, the NSE transactions database contains the complete trading records of all stocks that traded on the exchange between January 1, 2005 and June 30, 2006. The most significant characteristic of the dataset is that it comes at the transaction level which identifies both counterparties ( buyer and seller) in a transaction, unlike all other existing datasets which have information only on one side ( buy or sell). The dataset contain about 1.8 billion trading records carried out by over three million distinct investors. Similarly, the BSE database contains the complete trading records of all stocks that traded on the exchange between January 1, 2005 and December 30, 2010. The dataset contains about 5 billion trading records carried out by over 3 million distinct investors.

This dataset contains detailed account information from one of the public sector banks of around 25000 farmers belonging to the states of Andhra Pradesh, Karnataka and Maharashtra. The dataset includes account level data for about sixteen thousand farmers whose loans were waived and about 9000 farmers whose loans were not waived. The transaction records of the farmers in the data include the date of each transaction, a description of the transaction, type of the transaction (debit or credit), transaction amount, account balance. The data also include land holdings for the beneficiaries of the debt waiver program (i.e. the partial and full waived groups).

A Non-Disclosure Agreement and an Indemnity Agreement needs to be signed to obtain this data.

Fama French Factors for a given market, describes the stock returns. These are developed for the U.S markets and CAF is developing these factors for the Indian Markets. These are freely available for use and can be downloaded from the links below.

1) India F-F 3 Factors (Ex. Dividends)
2) India F-F 3 Factors

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