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I/B/E/S is one of the most widely used sources for analysts' expectations in empirical finance and accounting research. Yet important questions about data provenance, coverage, historical revisions, identifiers, and consensus construction can have significant implications for research design and reproducibility.

In this webinar, we sit down with two product specialists from LSEG to discuss I/B/E/S and its underlying data methodology. Drawing on this institutional knowledge, they address the questions researchers most need answered before building I/B/E/S into their empirical work: How is coverage determined, and where are the gaps? What does the data collection process actually look like, and how has it evolved over time? How should researchers navigate identifiers when linking I/B/E/S to other datasets? And how, precisely, is analyst consensus established?

Whether you're a seasoned I/B/E/S user or working with the data for the first time, this conversation offers practical, methodology-level insight that can strengthen your research design and support more reproducible results.

In this webinar of the ��ݮ��ƵResearch Data Webinar Series, a team of experts from S&P Global / Compustat will join us for a Q&A-style session on how Compustat really works—and how that affects your research.

This tutorial explains why merging CRSP and Compustat data can be challenging and introduces Compustat’s new historical identifier tables. Through a practical demonstration in a Jupyter Notebook, the video shows a valid and recommended method for merging the datasets using historical CUSIPs.

This tutorial demonstrates how to merge CRSP and Compustat data using the CRSP/Compustat Merged (CCM) linking table. Through sample code and a practical demonstration, the video covers best practices for using CCM, recommended filters for obtaining high-quality matches, and how this approach compares with merging based on historical CUSIPs.

A Conversation with Professor Eugene F. Fama
Nobel Laureate in Economic Sciences (2013)
Robert R. McCormick Distinguished Service Professor of Finance,
University of Chicago Booth School of Business

Professor Fama, widely recognized as one of the founding fathers of modern empirical finance, will share his reflections on the evolution of financial economics—from the Efficient Market Hypothesis to the Fama–French factor models—and offer his insights on the future of data-driven research in finance.

The session will be a live Q&A format moderated by Rui Dai and Freda Drechsler, Senior Research Directors at WRDS.

��ݮ��Ƶguides you through the website and introduces you to query pages, innovative tools, comprehensive resources, and research support.

��ݮ��Ƶdemocratizes data access so that all disciplines can easily search for concepts across the data repository — hosting the broadest collection of data on the most robust computing infrastructure.

Designed for researchers who use CRSP data, this overview explains the shift to the new CIZ format, also known as Version 2.0. 

• What’s changed? 
• What’s stayed the same? 

This video offers a more technical walkthrough of the new CIZ format (Version 2.0), focusing on how to navigate changes to variables. It includes code conversion examples for everyday research tasks. You will learn:

• How to use CRSP’s new meta tables
• How CRSP calculates monthly returns
• Where to find CIZ support info and sample code

CRSP has enhanced its system with a new Stock & Indexes Flat File Format 2.0 (CIZ). Version 1 (SIZ) is being discontinued and users will need to utilize the new format to continue receiving updated data.

This introductory tutorial explains why understanding the identifiers in your chosen dataset--along with the date ranges for which they are valid--is important to consistency and accuracy in your research.

Topics covered include:

• Universal vs. proprietary identifiers and their uses in financial datasets
• Common identifiers, including tickers, CUSIPs, SEDOLs, ISINs, and CIKs
• How and why identifiers can change over time
• CRSP identifiers PERMNO/PERMCO and Compustat’s GVKEY
• Some best practices for using identifiers to merge datasets and track companies and securities over time

In this overview of BoardEx you will learn about coverage, how the data is structured, key identifiers, and the answers to some frequently asked questions from researchers.

Start using our web-based interface to query your data. The only requirements are a web browser and Internet access. Learn how to:

• Add filters and select variables
• Select the output format
• Download the data
• Access past queries

This tutorial is intended for first-time users, or experienced users looking to refresh their knowledge.

Learn how to log in to SAS Studio at ��ݮ��Ƶand take a friendly tour of the interface so you can confidently navigate files, libraries, and programs from your very first session.

Quickly learn how to access Jupyter on ��ݮ��Ƶusing the Python kernel.

• Explore the ��ݮ��ƵPython package, designed for straightforward data access
• Retrieve Dow Jones data
• List libraries available to your institution

This quick overview of the research data on ��ݮ��Ƶbegins by describing usage of the most popular databases.

Databases offered on ��ݮ��Ƶare introduced, categorized by topic:

• Pricing data, including CRSP, Compustat, TAQ, OptionMetrics, and TRACE
• Fundamental data, including Compustat, FactSet, Capital IQ and WorldScope
• Earnings and estimates data, including I/B/E/S and Zacks
• Institutional ownership data, including Thomson Reuters, CRSP Mutual Funds, WRDS-SEC Data, and Audit��ݮ��Ƶ
• Other types of data, including ExecuComp, BoardEx, RavenPack and Capital IQ Key Developments

The video concludes by highlighting a suite of tools that can be used to link databases for conducting empirical research.

Our experts guide you in finding the data needed for your research.

• How data is categorized
• Techniques to locate data
• Resources that index WRDS' data

This video tour will guide you through the extensive support services offered by WRDS.

Our staff of technical and research specialists assist with questions pertaining to research, data queries, and programming.

Experience how this teaching and learning toolkit can introduce finance and business concepts through interactive applications and simulations.

Instructors can utilize these robust tools as a core component of the curriculum, for stand-alone lessons or assignments, or for visually compelling classroom demonstrations.

Topics

• Introduction to WRDS
• Investments, Fixed Income, and Accounting
• Text Analysis
• Macroeconomics
  
  

Our doctoral-level expert guides you through an overview of Compustat data on WRDS:

• What is Compustat?
• Coverage
• Important types of data in Compustat

Expand your knowledge of the benefits of Compustat data on ��ݮ��Ƶthrough this guided video overview.

Supporting all levels of experience, Part II of our Compustat overview continues with instruction on

• How to access data
• How to link with other data for research

Access a comprehensive overview of CRSP data on WRDS.

Key discussion points include:

• The popularity of CRSP data
• CRSP features and benefits
• Types of CRSP data accessible
• Examples of how data is presented on WRDS

In this video, you'll learn how the CRSP stock database is organized on the ��ݮ��Ƶplatform. We cover the following topics:

• Types of Updates
• Time Series vs Event Files
• How to Merge the Files

Understanding the structure of the CRSP database will make it easier to locate the data you need and use it effectively in your projects.

This tutorial introduces CRSP coverage, including the securities and exchanges represented in the database, how coverage changes over time, and the key differences between CRSP and Compustat. It provides the foundation researchers need to choose the appropriate dataset for their analyses.

Learn two different ways to download the historical S&P 500 constituents from CRSP and save the data in different formats:

• Use SAS Studio
• Use a Jupyter Notebook

Requires a subscription to CRSP.

Become a more advanced CRSP user by learning details about CRSP variables, such as:

• What are "negative" CRPS prices
• How to use CRSP data to create a time-series of prices that is consistent after a split
• An explanation of the formula used to calculate returns with dividends
• How delisting returns are calculated
• What to do about missing delisting returns
• How to calculate market capitalization

Take a guided tour through I/B/E/S data — the premier analyst forecast data in academia.

Key discussion points:

• Introduction
• Data categories
• Identifiers
• Forecasting time lines
• I/B/E/S Research Guide

Conduct research using I/B/E/S, I/B/E/S Global Aggregates, I/B/E/S Key Performance Indicators (KPI), and I/B/E/S Guidance.

Identify detailed company financial information for U.S. and international public and private companies and investment firms through S&P Capital IQ.

Access these key S&P Capital IQ databases through WRDS:

• Capital Structure-Debt
• Key Developments
• Professionals
• Transcripts

This video presents an overview of Capital IQ on the WRDs platform, including detailed information on the following datasets:

• Capital Structure
• People Intelligence
• Key Developments
• Transactions
• Transcripts

The video concludes with a use case study, illustrating the powerful links available across Capital IQ products.

Capital IQ Transcripts provides historical conference call transcripts form around the world, covering approximately 8,000 public companies. Learn key information for using this data, including:

• Details about coverage
• How the data is collected and processed
• How the data in the CIQ Transcripts package on ��ݮ��Ƶis structured
• Summary statistics, such as call types and a breakdown of transcripts by country and year
• Description of the full text data accessible on the ��ݮ��ƵCloud

Using concrete examples with Capital IQ Transcripts, this video illustrates different ways to access data. For example, instructions are provided on how to pull Apple's 2015 earnings call transcripts using:

• PC-SAS Connect
• Python
• PostgreSql on the WRDs Cloud

This is an overview of Compustat Global, highlighting the database's coverage and available variables. Compustat Global's fundamentals, security, and index data are all introduced.

Will you need to filter by country for your research? Step-by-step instructions are provided. The tutorial concludes with a discussion of some common research questions that come up when using Compustat Global data.

Compustat Execucomp is introduced, with a discussion of the:

• Data, including details about coverage, where the data is sourced from, and the different datasets that make up Execucomp
• Compensation items, including total compensation, cash compensation, and stock & option compensation
• Tracking of executives, including using the annual CEO flag, and identifying board members that are CEOs

The video concludes by highlighting the support documentation available on ��ݮ��Ƶfor Execucomp.

��ݮ��Ƶownership data offerings have substantially expanded in recent years. This comprehensive overview of ownership data at ��ݮ��Ƶexamines ownership data at the:

• Institutional level
• Porfolio or fund level
• Insiders level

Regulatory details, data coverage, and reporting frequency are all discussed in this first part of a two-part video series on ownership data.

What information should researchers know when selecting which ownership data to use? This second video in the two-part series on ownership data focuses on known data issues in the most commonly used databases.

For example, a comparison of the three following datasets is discussed:

• Thomson-Reuters Mutual Fund Data (Legacy SP feed)
• Thomson-Reuters Global Ownership Data (OP feed)
• CRSP Mutual Fund Database

The video concludes with an overview of the available ��ݮ��Ƶresearch applications related to ownership data.

NYSE TAQ data — Introduction

��ݮ��Ƶguides you through the introductory steps to access current U.S. market equities at the millisecond level including:

• Access current U.S. market equities at the millisecond level.
• View granular details of all trade and quote activity.
• Validate best execution, develop profitable trading strategies and perform in-depth research on the aggregate marketplace.

This video overview of the American Hospital Association (AHA) data on ��ݮ��Ƶfeatures access to multiple data sets that cover demographic, operational, financial and IT characteristics of the nation’s hospitals.

Topics covered: Research trends, COVID-19, and new variables.

Data collected by the represents the single best source for credible, consistent information about the nation’s hospitals.

Which international database will work best for your research? View an in-depth comparison of the four main international databases that provide financial statement data:

• Compustat Global
• BvD Osiris
• Refinitive Worldscope
• FactSet Fundamentals

Learn about the contents and coverage of each database. In addition, this tutorial provides a discussion of the pros and cons of the databases, as well as their common characteristics.

Use the ��ݮ��ƵEvent Study tools to quickly explore and visualize how specific events affect stock returns in U.S. and global markets. This video introduces the key concepts behind event studies and provides an overview of the four Event Study applications available on WRDS.

You’ll also see the tools in action with a step-by-step walkthrough of a U.S. Daily event study. Learn how to upload your own list of companies and event dates, set up your study using the ��ݮ��Ƶquery form, and run your analysis—making it easy to move from your research question to event study results.

The ��ݮ��ƵSEC ��ݮ��Ƶ Suite is a “one-stop” research platform that provides standardized service tools to enable users to overcome the challenges in systematically parsing regulatory reports on the SEC website.

This video--the first in a multi-part series--introduces the ��ݮ��ƵSEC ��ݮ��Ƶ Suite, covering:

• Importance of regulatory filings
• Newly available disclosures
• Search capabilities
• Derived datasets
• Tracking of entities over time using linking tables
• Growth of available SEC filings over time

With over 19.8 million SEC filings available since 1994, it is important to be able to easily access the the specific filings that are of interest.

This video--the second in a series--discusses the structure of SEC filings, including

• How the filings are maintained
• How the filings are organized on the ��ݮ��Ƶserver
• How the filings are referenced in the metadata

This third video in the series explains how to use web queries to access the SEC filings--including lists of exhibits and 8-K items--with a particular emphasis on the versatility of the search function. The discussion also includes a description of available textual analytics tools, covering

• Readability and sentiment
• ��ݮ��ƵBag of Words

��ݮ��ƵInsiders includes all insider trades after the SEC mandated electronic disclosure--from June 30, 2003 to the present. This introductory video covers key information for using the data, such as:

• What is covered in the data?
• Where does the data come from?
• How is the data structured?

Comprehensive guide to using ��ݮ��ƵInsiders, including:

• Details about ��ݮ��ƵInsiders coverage
• Description of insider trading transactions common to all insider trading databases
• Discussion of the general ecosystem of insider trading

Guide to assembling a trade level dataset for derivatives/non-derivatives transactions in ��ݮ��ƵInsiders. The end result is the creation of a dataset similar to Thomson-Reuters Table 1/Table 2. 

There are hundreds of datasets provided by different vendors on WRDS. Learn the basics to linking databases, including:

• Common identifiers used for linking
• Procedures used to generate linking tables on WRDS
• Other linking resources available on WRDS

The goal of this application is to reproduce, as closely as possible, the Fama-French SMB and HML factors in order to provide researchers with a set of programs that can be modified to further advance research in this area. This tutorial presents a step-by-step replication of the SMB and HML Fama-French factors using SAS, including:

• Using Compustat data to calculate book value of equity
• Using CRSP stock data for portfolio formation
• Merging of CRSP and Compustat data
• Portfolio formation
• Calculating the Fama-French factors
• Comparison of results with Ken French's data

A series of additional videos describes each of the calculations behind these steps in more detail.

Learn how to work with Compustat annual data to calculate the book value of common shares. Presentation includes detailed examination of the relevant portion of SAS code used to replicate the Fama-French factors.

Learn how to work with CRSP stock data to calculate market equity. Presentation includes detailed examination of the relevant portion of SAS code used to replicate the Fama-French factors.

Learn how to work with CRSP data to calculate portfolio weights for value-weighted returns. Presentation includes detailed examination of the relevant portion of SAS code used to replicate the Fama-French factors.

Learn how to merge CRSP and Compustat data to create book-to-market ratios. Presentation includes a detailed examination of the relevant portion of the SAS code used for replicating the Fama-French factors.

Learn how to form portfolios and calculate the returns necessary to create the SMB and HML factors. Presentation includes a detailed examination of the relevant portion of the SAS code used for replicating the Fama-French factors.

This final video in the Fama-French series demonstrates the last step in the process: how to calculate the SMB and HML Fama-French factors. Presentation includes a detailed examination of the relevant portion of the SAS code used for replicating the Fama-French factors. The video concludes with a discussion of the correlation between the results of this replication and Professor French's factors.

Learn how the ��ݮ��ƵCloud can be used to execute research and strategy development.

• How to access ��ݮ��ƵSupport Section for Cloud needs
• Which languages are supported on ��ݮ��ƵCloud
• ��ݮ��ƵWeb-query -vs- the ��ݮ��ƵCloud
• Head nodes -vs- compute nodes

Learn how to use Python on the ��ݮ��Ƶplatform for research—pulling structured data, subsetting by firm and time period, combining multiple datasets, and plotting your results.

Demonstration of how to run a momentum strategy using the ��ݮ��ƵPython API and the CRSP dataset.

• Follows the momentum strategy as documented by Jegadeesh and Titman (1993)
• Includes how to plot the return series

This tutorial for how to create Python virtual environments on the ��ݮ��Ƶserver covers:

• Benefits of using a virtual environment
• Steps for creating a virtual environment
• Activating and deactivating a virtual environment
• Using pip to install packages

Step-by-step instructions for how to run a basic regression in Python. Learn how to:

• Install the required packages
• Read data into Python
• Fit a model
• Obtain output from the model

SASPy is a Python package which enables integration of SAS programs with Python programs. This video--the first in a 4-part series--presents a general overview of the package, including:

• Reasons for using SASPy
• Configuration for local computer
• How to use SASPy on the ��ݮ��ƵCloud

This second video in the SASPy series introduces useful SASPy functions, as well as Jupyter magic for SAS. The tutorial includes:

• Starting a SAS session
• Submitting SAS jobs in a Python session
• Exchanging data between SAS and Python
• Transferring a Python variable to SAS macro variable

This third video in the SASPy series demonstrates how to work with SASPy on ��ݮ��ƵJupyter Hub. The tutorial covers many functions, including:

• Advanced SAS data access using dataset options
• Methods for submitting a SAS job
• Transferring macro variables between SAS and Python

This last video in the four-part series demonstrates a sample workflow using Python and SASPy running on a local PC. The example used is running an event study using CRSP data and a pre-written SAS macro.

��ݮ��Ƶte guía a través de la plataforma y te presenta su página web en donde descargar datos, sus herramientas innovadoras, así como sus recursos integrales y de apoyo para el investigador.

• Primeros Pasos
• ¿Qué datos puedes encontrar en WRDS?
• ¿Cómo hacer una descarga web?
• Herramientas de ��ݮ��Ƶ creadas por WRDS
• Herramientas para la Investigación, ejemplos de programación, y más
• Herramientas de apoyo para el investigador.

Learn how to access sample sets of trial data at WRDS.

Learn how to search for variables in datasets and forms.

Open and explore a dataset in SAS Studio, and learn how to select columns and filter rows to quickly focus on the data you need.

Demo of a complete SAS Studio workflow—from uploading a file, to running custom code, to downloading results—bringing the full process together in one practical example.

Learn how data storage works on the ��ݮ��ƵCloud, including how to use your Home directory, your institution’s scratch space, and the SAS Temp directory.

Through parsing of the SEC 13F Holdings data reported in XML attachments, you can access details on holdings as well as well as summary information of equity positions held by institutional investors. As such format was mandated by the SEC after June 2013, the SEC 13F Holdings data is complete only for the period after that reporting date.

I/B/E/S International Inc. created their Academic Research Program over 30 years ago to provide both summary and individual analyst forecasts of company earnings, cash flows, and other important financial items, as well as buy-sell-hold recommendations. In 2000, I/B/E/S was integrated with Thomson Reuters / First Call, and in 2012 First Call was discontinued.

Introduction Training to Compustat, CRSP, and ��ݮ��Ƶ��ݮ��Ƶ.

Training overview of Classroom Tools by WRDS. These tools are a teaching and learning toolkit designed specifically for faculty who are introducing finance and business concepts in the classroom.

BoardEx contains valuable information on 1.7 million corporate executives and board members from over 2.2 million organizations. Biographical data includes details such as age, gender, positions held, educational qualifications, compensation and stock holdings, as well as insights into the executive's professional network.

WRDS' proprietary SEC research platform is used in such disciplines as corporate due diligence, forensic accounting, disclosure research, and investment management. This teaching tool is designed to help you to learn more about the different components of the suite.