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Dissertation Research

19 October 2017 1 comment

When seeking to complete a dissertation in the area of Accounting & Finance, a key consideration is ‘Research Feasibility’. This can be summarised by the statement:

 

Can I obtain the data I require, in a timely manner, to successfully complete my research?

 

A typical one year MSc course would allocate 3 months at the end, to complete the disseration. The gathering of company financial quantitative data, (from sources such as: Thomson Reuters Datastream, S&P Capital IQ, Bloomberg Professional, Compustat via WRDS: Wharton Research Data Service) is fundamental to the success of the research.

 

What can go wrong?

 

  1. Data is not available:  It is not contained within the databases the university subscribes to. The years required are not covered. The student is off-campus and the data is only accessible on-campus (as is the case for Datastream and Bloomberg Professional).
  2. Research Proposal:  This may be too ambitious. For example, a student reads an accounting/finance journal article and decides to try to replicate all or part of the research contained within the article. This can be problematic, as the academic probably spent two or more years completing the research – greater than the time available for an MSc dissertation.
  3. Topic:  The choice of topic can be influenced by a desire to work in a particular area of finance. Unfortunately, this may lead to the key difficulty when conducting research – Data is Not Available.

Data is the foundation on which any analysis is based. Where this is difficult to obtain, time pressures may result, leading to the possibility of failure to submit the dissertation on time.

Whilst it could be argued that the difficulties experienced by students in working on their dissertation are part of the research process, as a Librarian, my approach is different: how can I be most helpful, in assisting the student to successfully complete their research?

 

Helpful Suggestions

 

  1. Pilot Project: Essentially this means establishing the best source – there could be more than one available. Also, how to search the source productively. Also, whether all the years of data required are covered.
  2. Seek Guidance:  This follows directly from point one above. It may be that the most efficient method (shortest time to collect what is required) is not known to the student. Guidance from a Librarian can demonstrate the best source and search method, drawing on years of experience in supporting student dissertation research.
  3. Explore Resources:  With so many sources available to students, the difficulty is often one of familiarity – knowing which databases are available and how they can be accessed. A Library web site is a good place to start. The example below is the subject guide for ‘Business and Management’, at the University of Manchester.

 

Database Guide

Business & Management Guide

 

One of the sections is  for ‘Specialist financial databases’. These are useful for dissertation research:

 

Financial Databases

Specialist Databases

 

Summary

 

Making the best use of resources by seeking guidance from Librarians and planning ahead (pilot study) can help to ensure a dissertation is successfully completed. The key factor being, the ability to secure data, on which to base any analysis.

 

Previous related post, in the Library Research Plus blog:

Research Feasibility [18 February 2015]

 

 

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13 new ESG Scores released on Datastream

10 October 2017 Leave a comment

The following message is copied directly from Thomson Reuters content notification DN093509. It applies to Thomson Reuters Datastream, specifically Environmental, Social and Governance (ESG) data. There has been no change in the ASSET4 Excel template which can be used to access this data. The 2015 ASSET4 ESG data glossary (Excel format) offers an additional reference of the relevant datatypes. A copy of this message is also available as a PDF.

Thirteen new ESG Scores measures have been added to Datastream.

Thomson Reuters ESG Scores are an enhancement and replacement for the existing equally weighted ASSET4 ratings*. They reflect Thomson Reuters’ new strategic ESG framework.

* NB: We advise all users of the ASSET4 ratings to migrate to the new ESG Scores in the coming months, as we plan to retire the ratings in early 2018.

Key enhancements over the legacy equal-weighted ASSET4 ratings are:

  1. ESG controversies overlay
  2. Industry and Country benchmarks at the data point scoring level
  3. Automatically adjusted Category scores based on the size and impact of each category
  4. Percentile Rank scoring methodology where hidden layers of calculations are eliminated

The new scores are designed to transparently and objectively measure companies’ relative ESG performance across ten themes as shown in the chart below.

New ESG measures added to Datastream

A combination of the ten categories makes up the ESG Score, which is discounted when there were ESG controversies to calculate the ESG Combined Score. Where there were no controversies for a particular period, the ESG Combined Score and ESG Score have the same value. The ESG Controversies score is calculated per fiscal period, with the latest controversies being reflected in the latest complete period.
Thomson Reuters ESG Scores are calculated and available for all companies and historical fiscal periods in the ESG Global Coverage, consisting of 6,000+ public companies globally.

Below are the corresponding Datastream datatypes, titles and definitions.

DS Datatype DS Title DS Definition
TRESGS ESG Score ESG Score is an overall company score based on the self-reported information in the environmental, social and corporate governance pillars.
TRESGCS ESG Combined Score ESG Combined Score is an overall company score based on the reported information in the environmental, social and corporate governance pillars (ESG Score) with an ESG Controversies overlay.
TRESGCCS ESG Controversies Score ESG Controversies Score measures a company’s exposure to environmental, social and governance controversies and negative events reflected in global media.
TRESGENRRS Resource Use Score Resource Use Score reflects a company’s performance and capacity to reduce the use of materials, energy or water, and to find more eco-efficient solutions by improving supply chain management.
TRESGENERS Emissions Score Emissions Score measures a company’s commitment to and effectiveness in reducing environmental emission in the production and operational processes.
TRESGENPIS Environmental Innovation Score Environmental Innovation Score reflects a company’s capacity to reduce the environmental costs and burdens for its customers, thereby creating new market opportunities through new environmental technologies and processes or eco-designed products.
TRESGCGBDS Management Score Management Score measures a company’s commitment to and effectiveness in following best practice corporate governance principles.
TRESGCGSRS Shareholders Score Shareholders Score measures a company’s effectiveness in the equal treatment of shareholders and the use of anti-takeover devices.
TRESGCGVSS CSR Strategy Score CSR Strategy Score reflects a company’s practices to communicate that it incorporates the economic (financial), social and environmental dimensions in its day-to-day decision-making processes.
TRESGSOWOS Workforce Score Workforce Score measures a company’s effectiveness towards job satisfaction, healthy and safe workplace, maintaining diversity and equal opportunities, and development opportunities for its workforce.
TRESGSOHRS Human Rights Score Human Rights Score measures a company’s effectiveness in respecting the fundamental human rights conventions.
TRESGSOCOS Community Score Community Score measures the company’s commitment to being a good citizen, protecting public health and respecting business ethics.
TRESGSOPRS Product Responsibility Score Product Responsibility Score reflects a company’s capacity to produce quality goods and services, incorporating the customer’s health and safety, integrity and data privacy.
ESG chart automobiles

The ESG Controversies Score is calculated based on 23 ESG controversy topics and measures a company’s exposure to environmental, social and governance controversies and negative events reflected in global media

For more details, you can click here to refer to the full methodology paper. In particular, you can consult page 12 for a high-level comparison between the two scoring methods.

Categories: Business Databases Tags: ,

Comparing Company Share Price Performance

Datastream is useful to be able to search for multiple companies (Series) and datatypes, in terms of quantitative data.

For example, Tesco PLC, J Sainsbury PLC and Marks & Spencer Group PLC are UK supermaket groups, each within the FTSE100 Price Index. One measure of company performance is Share Price. This quantitative data can be represented in chart form.

 

Search Procedure

 

Data Category is the starting point. For company related data, this would be ‘Equities’.

For Analysis, this would be ‘Time Series Data’.

The Series can be identified by using the Navigator function, activated by clicking on the ‘Find Series’ button. The code displayed in the Navigator search, when selected, gets copied into the search screen. For example, TSCO for Tesco PLC.

The Datatype, for Share Price, searchable via the Navigator (Datatypes button) is ‘Price (Adjusted – Default)’, represented by the code: ‘P’.

Time Period can be selected from set date ranges, such as ‘-10Y’, which represents the last 10 years. Alternatively, a specific date range can be entered by clicking on the ‘Time Period’ button, giving the option to enter a Start and End date using the format:  DD/MM/YYYY.

The frequency of data can be selected by clicking on the Settings button. This allows choices of ‘Daily, Weekly, Monthly, Quarterly and Yearly’, with a default of ‘Daily’. Daily is normally used for Share Price data.

Finally, click on the Run Now! button to execute the search.

The results of this search for Tesco PLC Share Price data, in Datastream 5.1, gives the following output:

 

Datastream Search.

Datastream 5.1 Search

 

It is then possible to add this data into a chart view, by selecting Multiple Series/Flexible Chart, then Comparison Line Chart then Rebased.

By clicking on the plus [ + ] symbol, the Series is copied into the chart summary box on the left of the screen.

Go back to ‘Time Series Data’ Analysis option, run the search for the next company’s Share Price and repeat the process, to include all those required in the chart summary box:

 

Analysis - Charts

Datastream – Analysis: Comparison Line Chart (Rebased)

 

Execute the search by clicking on the ‘Run Now!‘ button at the top right of the screen.

 

Rebased Chart

Datastream: Comparison Line Chart (Rebased)

 

By virtue of specifying ‘Rebased’, this represents the different series as an index, beginning at 100. This allows a relative view of performance. Hence, a movement from 100 to 95 represents a 5 per cent decrease in the share price of a company. All three companies are showing a value of about 40 (as at 24/3/2017), indicating they have lost approximately 60 per cent of their value, as expressed by Share Price, over the last 10 years.

 

Price Index Comparison

 

By comparing a number of companies within a particular Price Index, it is possible to get an appreciation of how the companies have performed relative to the whole index. Tesco PLC, J Sainsbury PLC and Marks & Spencer Group PLC are all part of the FTSE100 Price Index.

Using the Analysis option ‘Comparison Line Chart – Rebased to First’ gives a scale relating to the first series (FTSE100). To do this, run a search for the FTSE100 data first and subsequently the companies also part of the index. Changes to the search above include:

Data Category: ‘Equity Indices’, Datatype: ‘Price Index’ and run the search for data.

Next, change back to the settings for Companies (Data Category: Equities, Datatype: Price (Adjusted Default), run the searches for data and add to the chart summary box [ + ].

 

Chart summary box.

Datastream: Chart summary box.

 

Next, click on the ‘Run Now’ button to execute the search.

 

Datastream Chart.

Datastream: Price Index vs Companies (Line Chart Rebased to First).

 

This chart gives a clear graphical representation of the relative performance of company Share Prices and the FTSE100 Price Index. The competition from low cost retailers such as Aldi and Lidl is a factor in the poor recent performance of Tesco PLC and J Sainsbury PLC in particular, reflected in the above chart.

 

Datastream is available to current students and staff of The University of Manchester.

 

 

Categories: Business Databases Tags:

Finding ESG data in Datastream using the ASSET4 template

25 October 2016 Leave a comment

A detailed source of environmental, social and governance (ESG) data can be found in Thomson Reuters Datastream.

Instead of choosing the appropriate datatypes in a regular Datastream time series request, you can download the ASSET4 template. This is hard to find in the InfoBase support platform (replacement for Extranet) so I suggest you get it from the Datastream Excel add-in toolbar, although this method is not quite as easy as you would like.

Open Datastream in Excel the usual way (remember the desktop icon “DSSetup – Shortcut”). Click on the Datastream ribbon tab, go to the Request Tables group and click Sample Sheets. Tick the button ‘Equities : ESG ASSET4 – Sector Industry  analysis’ then click the Download button.

ASSET4 - find the template

Find the ASSEST4 template with the ‘Sample Sheets’ button and download it.

The Download & Open button does the same as the Download button, it doesn’t open the file.

ASSET4 template location

ASSET4 template downloads to a hidden folder.

The template takes the form of a macro-enabled Excel workbook and is downloaded to a hidden folder. Click on Start > Computer, click in the address bar and type the following:
C:\ProgramData\datastream\datastream advance\User

Note that ‘ProgramData’ is not the same as ‘Program Files’ or ‘Program Files (x86)’, it is a hidden folder. As you type the rest of the path, Windows should suggest auto-completions, which you can accept.

ASSET4 file location

ASSET4 file location, in the hidden C:\ProgramData folder.

Find downloaded ASSET4 (animated)

ASSET4 file location (animated)

From here, open the file and accept any warnings about enabling content.

ASSET4 intro

ASSET4 introduction

There are many sheets (tabs), starting with Home. Click on ESG Filters to select your search criteria. Choose (1) a sector or industry such as Telecommunications Services and (2) criteria across the environmental, social and corporate governance categories such as Water Use Total, Women Managers and Size of Board. When ready, click the Go button.

ASSET4 search criteria

ASSET4 search criteria

Wait a few minutes while the data is downloaded to the Data Table sheet.

ASSET4 data table

ASSET4 data table

The tables and charts of the many other sheets are automatically updated to reflect your search (except the Data Fields definitions sheet). For example, the Bottom 5’s sheet.

ASSET4 example results

ASSET4 example results

If you find a datatype you would like to use in a regular time series request, make a note of its code.

See also earlier post Environmental, Social and Governance (ESG) Data from July 2013.

Use pairs in one VLOOKUP with historical exchange rates from Datastream

20 July 2016 Leave a comment

One of the most useful Excel functions I help students with is VLOOKUP – extremely useful to automatically bring in data from one table to another. If you have company accounts data from Compustat Global (via WRDS) for multiple companies in multiple currencies, you will need to bring in the change rate for each currency to show every field in US Dollars.

A B C D E
1 Company Currency Total Assets Local Exchange rate Total Assets USD
2 Co. X AUD 100 =VLOOKUP(B2, currencies, 2, FALSE) =C2*D2
3 Co. Y PLN 400 =VLOOKUP(B3, currencies, 2, FALSE) =C3*D3

Where ‘currencies’ is a named range elsewhere in the workbook:

From Currency Rate
AUD 1.3158
PLN 3.95685
USD 1

The VLOOKUP command looks for the currency code in the first column and returns the rate from the second column (use ‘FALSE’ to ensure an exact match). The conversion is simply a multiplication. (Note that you can convert from USD to USD at a rate of 1.0.) But what about making sure that the exchange rate is correct for the date of the data, and what if you have data from multiple years?

Performing VLOOKUP when matching a pair of variables

Thanks to Professor Marie Dutordoir for suggesting this kind of technique!

Usually you will want to look at accounts data over several years and for several companies. If you are working with several currencies then you will need a more complicated solution to this VLOOKUP exchange rate table, considering a day/month/year for each rate-currency pair. You do not need a second lookup table or other Excel functions, you just need to have another variable of date and a variable of currency-date pairs.

Global company accounts data

Global company accounts data. Given column G (currency) and column H (year), create new column F (map = currency&year).

The new column F (mapping) is formed from currency and year, so F2 contains “=G2&H2” (see image above). The ‘currencies’ named range now begins with a different first column produced in the same way (see image below). A VLOOKUP always matches on the first column of its range, and now this one pulls the rate from the fourth column, so rate is “=VLOOKUP(F2, currencies, 4, FALSE)” for row 2.

In the ‘currencies’ named range, I have combined the exchange rate calculation and lookup into one formula (column K). Repeat this for each data type that you wish to convert the currency for. Remember to have an entry for USD at rate 1 for each year.

paired-vlookup-lookup

Stacked historical exchange rates in a named range ‘currencies’. Created column A (map) from B&C.

This example only has the average exchange rate for each year, you may wish to extend this approach for monthly or even daily rates. If you do this, you will need to take extra care with the format of the mapping cells, but this exceeds the scope of the post.

Where to find historical exchange rates?

Use the Datastream Navigator to find exchange rates

Use the Datastream Navigator to find exchange rates. Start by searching one category (Exchange Rates), limit it “To Currency: United States Dollar”, then use the search box for the source currency.

 

Company Identifiers in Datastream.

Identifiers can take many forms (e.g. Company Name, Ticker, CUSIP, SEDOL, Datastream Code, ISIN) and be national, such as CUSIP for US / Canadian companies or international, such as ISIN (International Security Identification Number). The ISIN code incorporates the national identifier. For example, for Tesco PLC: GB0008847096, which includes the SEDOL (UK company identifier) code: 0884709.

 

Company Lists and Datastream

 

In seeking to further their dissertation research, MSc students often make use of more than one research database. Consequently, a typical scenario involves a request to import a list of company identifiers into Datastream, then conducting further searches to secure data, prior to analysis. The ‘Create List (From Range)’ function is useful in this regard.

 

Create List (From Range)

 

This function within the Excel Add-In version of Datastream is extremely effective when working with lists (up to 5,000 Series [companies] per list). This enables Company Identifiers to be copied and pasted into Excel and saved as a List on the specific computer being used (Store List Locally) or saved to the Datastream mainframe computer (Upload List) – accessible from computers with Datastream installed.

The code generated to represent the list of companies can then be entered directly into a ‘Static‘ or ‘Time Series‘ request search screen in Excel. Hence, one or more Datatypes can be obtained for an entire list of companies and the results would be displayed in a single Excel sheet.

Company Identifiers which work with the ‘Create List (From Range)’ function include: ISIN, Ticker, Datastream Code. Both Company Name and CUSIP don’t work, even though CUSIP is meant to.

 

Example Search

 

Within Excel, with the Datastream tab selected, enter (paste in) the company identifiers. Next, Select the identifiers (ISINs below) and then click on ‘Create List (From Range)’. To illustrate the process, a short list of two US companies will be used (Apple, Microsoft) – this could of course be a list of many hundreds of companies.

 

Datastream - Create List (From Range)

Datastream – Create List (From Range)

 

From the ‘List Creation for Excel’ dialog box, the default option is ‘Store List Locally’ (on the computer being used at the time), with ‘Upload List’ as an option.

 

Create List - Store Locally

Create List – Store Locally

 

This generates a confirmation message – click ‘OK’.

 

Create List - Confirmation Message

Create List – Confirmation Message

 

The ‘List File Name’ [ New_0032.LLT ] is entered in the Series/Lists field in this Static Request (as at 03/06/2016) to locate: Company Name [NAME], CUSIP [WC06004], Ticker [WC05601], Datastream Code [DSCD] and Market Value [MV].

 

Datastream - Static Request

Datastream – Static Request

 

Results:  widen columns as necessary, to display data.

 

Results

Results

 

It would be possible to repeat the above process, to create lists with different identifiers         (e.g. Datastream Code, Ticker) and also select ‘Time Series’ request for historical data. For Ticker identifiers, it is advisable to format the cells in the Excel column to ‘Text’ (before identifiers are pasted in) where US companies can have an ‘@’ symbol as part of the identifier (e.g. @AAPL, for Apple). If the cells are not formatted as Text, the ‘@’ symbol will be interpreted by Excel as the start of a function.

 

Incompatible Datatypes

 

If a list contains both US and UK Ticker identifiers, this can cause a problem where an incompatible datatype is specified in a search request. For example, if CUSIP (datatype: WC06004) is included, this means the search will fail (i.e. it gives no results), as UK companies do not have CUSIP codes.

Converting from Ticker to Datastream Code identifiers is a way around this difficulty. The Datastream Code identifiers could then be used to create a new list: for Apple (992816), Microsoft (719643), Tesco (900803) and J Sainsbury (926002).

A Static Request (03/06/2016) search for datatypes:  Company Name,  CUSIP and Market Value is successful (i.e. it gives results) and merely has a blank cell under CUSIP for Tesco and J Sainsbury.

 

 

Datastream Code List - Static Request Results

Datastream Code List – Static Request Results

 

US tickers to Datastream mnemonics

31 March 2016 Leave a comment

A handy summary for those wishing to use a list of US companies Compustat in a Datastream query. In summary, a well-chosen prefix to the ticker symbol can be systematically added in Excel before creating a static or time series Datastream request. All you need to know is if the company is listed on Nasdaq or elsewhere. Thanks to EDSC for this post.

EDSC manuals, tips & tricks

If you have US tickers as output  from e.g. Compustat index constituents and you want to get stock prices from Datastream that’s possible. You can use a ticker to create a Datastream mnemonic. You have to add country code, so “U:” would do the trick. You can easily do this in Excel by concatenate U: with the column with ticker.

This solution works fine for all but the Nasdaq firms. Those will need a “@” sign in front not “U:” So just to be sure you have everything and you don’t miss any data do both so a list with “U:” and one with “@”.

Example

Screenshot_USticker_mnemonics_v2

The ones that don’t make sense will give errors but this way you won’t miss any. So with Ford U:F will work and give data, @ F won’t it will give an error. Similarly Micosoft @MSFT will work and give data, U:MSFT won’t it will give an error

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