The BBC business news recently posted a report about Warren Buffet’s Berkshire Hathaway that is a great example of the difference between adjusted and unadjusted prices. See Warren Buffett’s Berkshire Hathaway shares top $200,000, 15 August 2014.
The shares in Berkshire Hathaway surpassed $200,000 because Warren Buffet has never split the company’s class A shares. The class B shares are much cheaper because they have been split.
The screenshot below shows the adjusted price (P), unadjusted price (UP) and adjustment factor for Berkshire Hathaway class A (U:BRKA), class B (U:BRKB) and Google class A (@GOOGL). The Berkshire Hathaway class A shares have never been split so the price and unadjusted price are identical, while the class B shares were subject to a 50 for 1 stock split in January 2010.
The Berkshire Hathaway class A share/stock worth $87,900 on 31 December 2004 is the same as the one worth $188,124 on 31 July 2014. The class B share/stock worth $2,936 on 31 December 2014 is equivalent to 50 class B shares worth $125.43 on on 31 July 2014. The adjustment is always done historically so the class B share worth $125.43 on 31 July 2014 has an adjusted price of $58.72 on 31 December 2014.
- adjusted price (P) = unadjusted price (UP) * adjustment factor (AF)
- 58.72 = 2936 * (1 / 50)
The Google class A shares are very slightly different. The Google class A share/stock worth $192.79 on 31 December 2104 was “split” in April 2014 with shareholder getting one Google class C share for every class A share owned. The Google A share worth $579.5498 on 31 July 2014 has an adjusted price of $96.4885 on 31 December 2014. (The adjustment factor is not exactly 0.5 because of a small price difference between Google class A and Google class C stocks.)
The screenshot above is from a Thomson Reuters Datastream request table with 2 requests – the first producing annual values for the end-of-year from 2004 to 2104, and the second producing monthly, end-of-month, values for December 2013 to July 2014.
Both Berkshire Hathaway and Google are examples where the adjustment factor is less than 1 (adjusted price is less than the unadjusted price) but this is not always the case. The Price data in Datastream and Compustat post (researchfinancial blog, October 2104) has an example from American International Group where the adjusted price is much higher due to a consolidation (reverse split) in 2007.
The journal rankings based on articles published in 2013 are now available. (Update Nov 2014 – The EAJG (ABS) journal quality guide is now not expected until early 2015 – details below)
The best known journal rankings are the Journal Citation Reports (JCR) from Thomson Reuters. These are not available for free – staff and students from University of Manchester have access through our Web of Science (formerly Web of Knowledge) subscription.
Select the Journal Citation Reports link or select Web of Science and then the Journal Citation Reports tab. Once at the JCR home page select the Journals by Rank tab.
The primary variable calculated by JCR is the Journal Impact Factor (JIF). The new interface also offers a journal connection visualization.
The above screenshot is for Incites Journal Citation Reports – year 2013; category business, finance; and edition SSCI;
For more information – Journal Citation Reports Data Release 2014 (JCR 2013 data)
The SJR SCImago Journal and Country Rank – Journal Ranking, based on Scopus data, now have 2013 as their latest year.
The SJR indicator, developed by SCImago, is not as well know as the JIF factor from the Journal Citation Reports. However the metrics are freely available – they are based on Scopus rather than ISI Web of Science so more business and management journals are covered, and more business and management subject categories.
The screenshot below shows results for the subject area Business, Management and Accounting. There is a category Marketing in this subject area (see Journal ranking – marketing posted August 2012). The subject category Finance is in the separate subject area Economics, Econometrics and Finance.
The CWTS Journal Indicators are also based on Scopus data, and again 2013 is now the latest year available.
Google Scholar Metrics currently covers articles published between 2009 and 2013 (both inclusive) and are based on citations from all articles that were indexed in Google Scholar in June 2014. (details available via the learn more link)
Google Scholar does not appear to make historical metrics available.
There is an example screenshot in the Journal Ranking – August 2013 update post.
The EAJG (ABS) journal quality guide – ABS (the Association of Business Schools) Academic Journal Guide 2015 is now located at www.bizschooljournals.com [Updated 28 Feb 2015]
Thanks to the Academic Trends & Innovation blog for the latest JCR released post – a reminder that the Journal Citation Reports (2014 edition) is now available.
There is a datatype BETA available in Thomson Reuters Datastream but often this is not what researchers are looking for when they are looking for “company betas”.
The Datastream datatype BETA is static – only the current value is available – and it is also adjusts the raw beta value to make it a forecast beta.
There is a formula that you can use to get a time series of historic beta values: REGB#(LN#(X/LAG#(X,1M)),LN#(Y/LAG#(Y,1M)),60M). This uses the regression beta function with three parameters.
- The return of the market over one month – LN#(X/LAG#(X,1M)
- The return of the equity over one month – LN#(Y/LAG#(Y,1M)
- The time period – number of observations in the regression – 60M
The screenshot below shows the historic beta values for the June 2004 FTSE 100 constituents yearly from 31 December 2000 to 31 December 2013. The market return is the FTSE All Share – LN#(FTALLSH/LAG#(FTALLSH,1M). The equity return is LN#(X/LAG#(X,1M) – X will be each of the list constituents in turn, and the time period is 60 months.
The results in the screenshot come from two entries in a Datastream request table
- Static request for constituent list LFTSE1000604 and datatypes NAME,ESTAT,TIME,WC09802,BETA
- Time series request for LFTSE1000604 and the beta formula REGB#(LN#(FTALLSH/LAG#(FTALLSH,1M)),LN#(X/LAG#(X,1M)),60M)
The results show that care is required for dead companies. The formula continues to generate results long after the last valid price data (shown by TIME) so for dead companies the beta returned is always zero once the company has been dead 5 years (60 months).
The Worldscope beta datatype (WC09802) just gives the latest value (see Worldscope manual for details). If you use this in a time series request then you just get the same value repeated. In contrast the static datatype BETA gives an error if used in a time series request.
You can use the local index datatype (LI) rather than explicitly choosing the index in the beta formula.
This will give the same values as displayed above as X(LI) is FTALLSH for all these LSE listed shares.
Beta values on Thomson ONE.com (April 2014)
Beta values for companies (March 2010)
A query about finding the top 30 US multinational companies from 1975 onwards has turned out to be very difficult.
Since we are looking at US companies WRDS is the place to start. CRSP Compustat Merged (CCM) provides both the stock price data (from CRSP) and the accounting data (from Compustat) and provides excellent historical data.
However, after some investigation we could find no easy way of finding multinational companies using WRDS-CCM or WRDS-Compustat. We were looking to be able to rank the companies on foreign/international sales and then select the top 30 for each year.
Thsomson Reuters Datastream does provide a foreign/international sales dataype (WC07101). As a test of large US companies we select a historical S&P 500 constituent list (LSP500I0901 – S&P 500 constituents September 2001) and get sales, international sales and foreign/international sales % of total sales for 31 December 2001.
This screenshot shows the results ordered by international sales and certainly has companies that we would recognise as large US multinationals. However, scanning the results include many companies where there are no sales figures and some where only (total) sales available.
Further tests for international sale and total sales for the September 2001 S&P 500 constituents (LSP500I0901) shows that Datastream has no data before 1980. Further checking has shown that there is another better S&P 500 constituents list with 12 additional years of historical data (LS&PCOMP0989 – September 1989, LS&PCOMP0901 – September 2001) see notes below. (However, the results in terms of sales and international sales data are the same.)
In summary, Datastream has some useful data but it is incomplete, and only goes back to 1980.
Returning to CRSP Compustat Merged on WRDS (CCM) and selecting a small number of companies by hand we can check that CCM does have total sales from 1975 onwards
By now we have realised that something that sounds easy, finding large quoted multinational companies, is not. If US companies only have to report total sales in their accounts then databases such as Compustat and Worldscope/Datastream will only have foreign/international sales if the companies choose to report this. We can check this by getting the annual reports for individual companies.
If something is harder then expected it is also worth looking at related work to see exactly how they have identified US multinational companies.
As a check I had a look at Capital IQ. This was similar to Compustat in terms of the datatypes (variables) available, which is not surprising as they are both products from Standard and Poors (S&P), but more limited than Compustat in terms of the historical data available.
Bloomberg – I have still to check – however I don’t expect it to be better than Datastream in terms of historical data or in terms of the not available data.
S&P 500 Constituents
While preparing this post, I have discovered that there is more that one S&P 500 constituent list on Datastream.
- LS&PCOMP from Standard and Poor’s, LS&PCOMP is the current constituents, LS&PCOMP0989 is the September 1989 constituents (oldest available), LS&PCOMP0901 is September 2001, and LS&PCOMP0714 is July 2014 (newest on 4 August 2014)
- LSP500I (no source provided), date is unclear since several members are acquired, merged or delisted. LSP500I0901 looks to be a correct constituents list for Sept 2001.
Datastream changes: S&P Historical Indexes (posted June 2010 Financial Databases and Research) confirms that LS&PCOMP is the best constituent list for the S&P 500.
Compustat – North America – Index Constituents on WRDS will also give the S&P 500 constituents – use GVKEYX 000003 or TIC I0003. Historical data is available from March 1964. See Constituent list in Compustat (posted September 2010 Databaser blog) for more details.
In fuller response to a comment on Finding inactive/dead companies on Datastream (posted Feb 2012)
Although it is good for worldwide historic company data, Thomson Reuters Datastream does not give a quick way of getting a historic list for all companies from a specific country.
For WSCOPEFR we do a static request including:
- ESTAT – company status
- BDATE – base date
- TIME – latest valid price data
- EXDSCD – exchange code
- MAJOR – major security for company
- ISINID – primary quote
Using the results we filter to get companies listed in 2002
1837 – original Worldscope France list (WSCOPEFR)
1503 – removing companies that died before 2002, TIME < 01 Jan 2002
1015 – removing companies that listed after 2002, BDATE > 31 Dec 2002
You might want to further trim the list: only companies listed on the Paris exchange (EXDSDC = PR), only equities (TYPE = EQ), or only major securities (MAJOR = Y).
Rather that using the Worldscope list as a starting point you could use the Datastream lists FFRA (Active French companies) and DEADFR (Dead French companies), or do an explicit criteria search in Datastream Navigator.
All UK listed companies (part 3) (posted June 2013) gives details of the different approaches for the UK market. The first question about “all French companies” is – all companies with their primary listing on the Paris exchange, or all companies headquartered/registered in France whereever they are listed, or all French registered companies with their primary listing in Paris.
From the research enquiries of students gathering data for their dissertations we know that data on company ownership can be difficult. Recent investigations suggest that Capital IQ from Standard and Poors (S&P), though not perfect, may be a good choice for many research projects.
The usual way to use Capital IQ is to use a screen to select the companies of interest, then add some additional variables, and finally download the results as an Excel file.
The screenshot below shows a company screen with two criteria:
- Companies with their primary listing on the London Stock Exchange (LSE)
- Companies with a market capitalisation (aka market value) greater than 1,000 million UK £s on 31 December 2013
This gives a total of 268 companies – since this is a test we want to be well within the Capital IQ download limit.
Next use the Customize Display Columns tab to add extra information to the results.
There is a good selection of variables that can be selected from the ownership section. For this test we choose:
- CEO – Number of shares owned [Latest Quarter – 2]
- CEO – Value owned [Latest Quarter – 2]
The only options for historical data are in terms of latest quarter – the oldest being latest quarter – 40. Selecting the CEO value owned column the results can be reordered to show which CEO’s of large LSE listed companies have the most wealth in their company’s shares.
Downloading the results is just a question of selecting Excel and go in the export section just below the screening results header, and waiting while Capital IQ formats the results and returns a download link.
The selection of Latest Quarter – 2 was an attempt to choose the Q4 2013. However, advice from the Capital IQ customer help desk suggest that this will give Q3 2013. The ownership data is updated when the company files the relevant data, usually 4-6 weeks after the end of a quarter. On 16 July we are just in Q3 but the Q2 data will not be available yet. This makes the Latest Quarter Q1 2014, and so Latest Quarter – 2 is Q3 2013.
There is company ownership information available in other databases, but they do not handle the combination of a list of companies and historical data as easily as Capital IQ
- Thomson Reuters 13F data from WRDS (only data for US companies)
- Bloomberg – good for the ownership of one company
- Thomson One.com – detailed ownership for worldwide companies but with restrictions on the number of companies that can be investigated at one time, and results often need significant reformatting.
- Fame, for UK and Irish companies, and Amadeus, for large Eur0pean companies, – can work with lists of companies but variables restricted to the owners holding the most shares.
Company ownership information may only be available for the last few years, or if historical information is available then it may be restricted to the largest shareholders.
Acknowledgements are due to Phil Reed and Xia Hong who explained how to use Capital IQ and noticed to availability of ownership data.
Global Financial Database (GFD or Global Financial Data) provides access to financial and economic time-series data with more than 6500 series covering 150 countries worldwide. Two key characteristics of GFD:
- Long historical time-series data – e.g. for most countries GFD provides GDP data going back 100+ years. (screenshot below)
- Ease of access – available on any University of Manchester PC (and off-campus using VPN)
Using the GFD Filter Search is one way of getting an overview of the data available. A GFD Filter Search – GFDatabase: Country-UNITED KINGDOM and Series Group-Economic – gives results including
- United Kingdom Retail Price Index – Years 1209 – 2014
- United Kingdom Consumer Price Index – Years 1800 – 2014
- Great Britain Unemployment Rate – Years 1855 – 2014
The Screenshot below used a combination of a keyword search (Name contains “dividend”) and filter search (GFDatabase: Country-G-20)
Just select the linked name or a download button to get the page for downloading data.
The UK FT-Actuaries Dividend Yield is the FTSE All Share series that GFD have extended to give a time series that starts in 1926. (For full details see the description.)
GFD does not (with the University of Manchester subscription) provide data on individual stocks, but it does provide a wide range of series covering bond and equity market indices, commodity prices, exchange rates, interest rates and macro economic series.
Thanks to the research student, looking for historical UK dividend yield, who mentioned that a paper had got data for UK aggregate stock market from “Global Financial Data”.
This is essentially an edit and re-post of Global Financial Database (posted June 2011) following a check that the GFD interface had not changed significantly in the last 3 years, and that the UK aggregate dividend yield was part of the University of Manchester subscription.