Business data induction 2022–05–18

Datastream time series request for equities and economics

Today we are connecting to Datastream and launching the Navigator to search for companies and macroeconomic time series data.

Previous session, accessing or installing Datastream via Eikon

Types of request

  • Time Series, for items with a regular period.
  • Static, for items which seldom change.
  • You cannot mix static datatypes in a time series request, and vice versa.

Navigator

Launch a time series request from the icon in Excel.

  • The Find Series button launches the Navigator where you can search or browse for ‘who you are looking for’.
  • The Datatypes button launches the Navigator where you can search or browse for ‘what do you want to know about them’.
  • We used the Explore option to find economics, then key indicators by country, then China. It listed a few pages of results.
  • There is no datatype to choose for economics series.
  • Set the start and end date (relative or absolute year or dd/mm/yyyy) and frequency from daily to yearly.
  • Untick ‘Auto reload’ and consider ticking ‘Transpose’.

The data appears from the cell you had selected, down and right. You can edit the query if you select the top-left cell then the Excel menu item. Be aware that some of your data may be overwritten but not all.

  • In a new time series request, search for Tesla by name. Also browse the equities for UK automotive companies and find Aston Martin.
  • Use the preview of these series to find out which companies they are, what datatypes are available, select some of them.
  • Use the Navigator to search for other datatypes. Make sure to select the same data category ‘Equities’ and time series, as Navigator can show you items which are not available for your selected series.
  • Choose daily data and a few recent months.

Homework

  1. Download some recent price, volume and returns data for three automotive companies in different countries. Download the GDP or similar economic data for the countries which these companies are based in. Can you see anything interesting in the data?

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