WRDS instructor training 20210927

Phil Reed
TTT specialist business databases
2 min readSep 27, 2021

First session of a new run to train up colleagues who are somewhat new to business databases. This series will be delivered every two weeks, some online and some face-to-face. I have prepared an induction plan for one colleague (person A) and will allow more familiar colleagues to join as a refresher. Some weeks, there will be other guest trainers joining us to learn specific items.

We will start with WRDS then move onto Bloomberg. We will also priorities practical matters about door codes, IT and AV. A’s progress so far includes QA-ing a Capital IQ training resource. The general direction is to focus on workshop delivery, then online workbook/resource creation, then answering enquiries and running drop-ins.

Work through UG WRDS workbook

We are updating the UG empirical finance workbook where we teach them how to use WRDS for company accounts data (think ‘internal’ data), company market performance data (think ‘external’ data), and macroeconomic data (how the market performs as a whole).

The workbook is being refreshed (link for internal use only). Today we looked at:

  • CRSP for US market data
  • Compustat North America for company accounts data (fundamentals)

We used Ford Motor Company as an example. We considered how company identifiers are used, how data items are searched, what is the context for this kind of search (what is the data being used for).

We talked about accounting basics, what the students are likely to already know (accounting language) and what they are likely to fall on (identifier types, quirks of each database, how to apply the data in regression). The BMC course is a good way to improve understanding of accounting concepts and this will feature as part of the long-term induction plan.

Company identifiers

  • GVKEY is the primary or native type for Compustat, PERMNO for CRSP.
  • You can search for companies using several types of identifiers in each database but these are not always consistent across databases. For example, TICKER is the human-readable, friendly identifier (eg F for Ford, AAPL for Apple, MSFT for Microsoft) but it is different for each database, they can be recycled if a company changes name so not safe for historic data research.
  • CUSIP is difficult, we try to avoid it for UG use but make special mention of it with PG groups.

Homework for next time

  1. Continue with the workbook and look at the macroeconomic data (Fama French factors).
  2. Complete the quiz in the workbook.
  3. Form questions about the prospect of dual teaching this content.

Likely content for next time

  • Continue with WRDS, invite other new instructors, get Person A to teach them the workbook content.
  • Work through the workbook quiz, explain why the answers are what they are. Suggest similar questions.
  • May start working on Bloomberg.
  • May look at practical issues (if we are face-to-face).

--

--

Phil Reed
TTT specialist business databases

Librarian Data Specialist, The University of Manchester. Supporting teaching, learning and research with financial databases, digital skills and scholarship.