Goodwill Explained: Quindell Context

I'm not an accountant, so to put it rather crudely, Goodwill is basically the difference between what you pay for an asset and its net asset value at the time of purchase.


e.g.

I buy a company for £100m, but the net asset value is only £80m. This means that the Goodwill figure in this example is £20m.


In theory, Goodwill is meant to represent the hard to value intangible assets such as: employees, brand name, market share, expertise, etc.


In the case of Quindell, who are having their accounts scrutinised at the moment and are also in the midsts of an FCA investigation, Goodwill is likely to play an important role in the up and coming release of their revised accounts, purely because it has been historically a pretty large percentage of their balance sheet.


If we look at Quindell's Report Year ending 31 December 2013, we find this statement:

"Goodwill recorded in the Statement of Financial Position at the end of December 2013 totalled £235.6 million of which £181.4 million was in relation to the Group’s Services Division and £54.2 million in relation to the Solutions Division."


Now, it's not surprising that Quindell has had some large Goodwill figures in its balance sheets, because they were a very heavily acquisitive firm in the early stages of the company. Nevertheless, I felt that I ought to issue a warning to other shareholders (like myself), because I suspect that there's a decent chance that we could see some impairment charges to this Goodwill figure (downward revisions).


In this case, it's therefore quite likely that we could see a "faux-drop" in the total company equity in the "financial statements" section of the results. If this happens, it's worth remembering a few things:


1. The Quindell we have now is the important focus for longer term holders.

2. The sale of the Professional Services Division (the historic big earner) means that the re-publishing of the results are in my opinion of little relevance going forwards.

3. Accountancy regulations dictate that Goodwill can only be recognised if you pay for the asset - a home-grown brand can't have a Goodwill figure, making the situation potentially very confusing when looking at the company's "true" value.

4. Goodwill is horrifically subjective (who's to say if you payed too much for a company or not?), meaning that you can make a pretty good argument for ignoring any revisions within five percent of the figure.


Have a nice day,

The Masked Stock trader

Short Selling Statistics (UK) - When to go long...

Disclaimer: I don't have a licence to give financial advice, so don't view any of the bewlow content as thus.


THIS POST IS UPDATED PERIODICALLY WITH MORE DATA AND ANALYSIS!


Morning (01/07/2015),


I've put together some statistics regarding well known short positions across multiple sectors in UK markets. This data can be used to help determine the levels at which investors could consider going long on other stocks in similar positions.



Known Issues:


1. Historic market capitalisation levels are calculated using the latest shares in issue figures (clearly this number can change and for companies under short pressure I would argue that this is more likely to change than for companies that are not in the same position).


2. I have excluded well known shorted companies that have had the positions taken out as hedges against other positions - the positions I have chosen are aggressive short positions.


3. Data errors can exist and although I have tried to avoid them as much as possible people should be aware of them.


4. Some of the shorts listed below are still active, which means that if another down leg takes place (past the share price low in the below data) then this data will all change.


5. There really need to be hundreds of data points to give a really solid study - so view this as only rough.

Company	Market Cap Peak/£bn	Share Price High	Share Price Low	Percentage change/%		Mean Fall/%	Mean Fall Companies under £1bn MCap Peak/%	Mean Fall Companies Over £1bn MCap Peak/%
Quindell	3.036852	682.50	24.10	-96.47		-68.3010826720286	-74.5074087409454	-65.1979196375702
Tungsten Corp	0.513867475	409.75	52.488	-87.1902379499695
Tullow Oil	14.6821707	1611	278.10	-82.7374301675978
Afren	1.89171248	170.80	1.28	-99.2505854800937
BooHoo	0.626144975	55.75	21	-62.3318385650224
Plus500	0.8972909	781	198	-74.6478873239437
Sainsbury	8.2264596	428	221.10	-48.3411214953271
WM Morrison	8.056.095	345	150.6	-56.3478260869565
Carillion	1.7397029	404.3	294.025	-27.2755379668563
Ashmore Group	3.04106961	429.9	249	-42.079553384508
Nanoco	0.471046245	199.275	83.155	-58.271233220424
Lancashire Holdings	1.8493926	933.00	506	-45.7663451232583
Ocado Group	3.66998335	623.5	216.8	-65.2285485164394
Monitise	1.7903459	82.75	9.53	-88.4833836858006
Blinkx	0.9445401	234.75	23.25	-90.0958466453674

I intend to update this post with graphs confirming or denying any correlations between the peak market capitalisation level and the mean fall of stocks that are being short sold.

Analysis:

1. The mean percentage fall suggests that for companies that are in a bear environment, long positions should be avoided until the company has fallen by at least 50% if you are a buy and hold investor prepared to top up on the way down.

2. Be aware that as you reach the point when you should consider going long, average daily volumes are likely to increase in conjunction with intra-daily price volatility, as short positions exit and long or volatility traders move in and out on swings.

3. Although the data above only gives one example of this, it is generally notable that companies with lower floated share prices fall less under short pressure (I image that this is to do with the implied extra volatility per every 1p change that exists - each penny change in the share price carries more significance for company's value).



4. Statistical Analysis:


- Before you read this, it should be noted that I am not a statistician or mathematician.



- If we have a look at correlations in the data, the Pearson Correlation Coefficients for the data sets (Peak Market Cap vs Percentage Fall) look like this:


Companies Valued Over 1Bn: R= -0.1506

Companies Valued Under 1Bn: R= -0.4886

All Companies: R= -0.0435

- This works between -1 (negative correlation) and +1 (positive correlation). The closer the number is to 0, the weaker the relationship.



- I don't feel that I can safely comment on this data fro reasons I will place in my evaluation, but the data is there for people who find it useful.




- The mean data for share price falls in the table above does suggest however that larger companies (peaking over £1bn in valuation) do fall less than smaller ones (under the peak £1bn market cap).

Evaluation:


This study does sadly have some rather large holes in it:


1. The data sample is very small - 15 companies out of the 1231 companies listed on the LSE (excluding Venture Capital Trusts and Investment Trusts) is hardly a fair study.


- This being said manually sourcing data is hard and time consuming and added to this in the grand scheme of things, there aren't a vast number of short positions over the 2.5% threshold I used (many short positions are merely intended to hedge long positions and can be quite small). Therefore, you could argue that this 2.5% threshold helps to limit the sample size issues.

- It is also worth noting that newer companies are unlikely to quickly build up shorts of over 2.5%, which realistically brings this total sample size down again.



2. There are so many possible variables that I would question if knowing R values is really that useful.

- Also, there are twice as many larger companies in this data set than smaller companies, which again brings into question knowing about the R values and the mean values



Conclusion:

Regardless of the issues with this little study, I think that I personally have learned to avoid trading companies with shorts over 2.5% on the long side until a fall from the peak market cap has been achieved of 50% (across all companies). For smaller companies it does seem that looking for around a 75% fall is sensible, but on balance I would rather trust the larger data set for companies valued at over £1bn.

Enjoy,

The Masked Stock Trader

Free UK Chart Scanner - Candlestick Patterns and Chart Patterns

GENERIC DISCLAIMER: While none of this is designed to be malicious software, in the event that it does do something bad to your computer, I take no liability for this.



I've mentioned Tom Bulkowski's free chart scanner before, but my friendly programmer has just sent me a data downloader that I feel I ought to share with the wider world - nevertheless I'm going to post an overview here of the program and how I make it work on my Mac:



Tom Bulkowski's Free Chart Scanner (Patternz):


http://thepatternsite.com/patternz.html



This is designed to work on Windows XP, but according to his instructions people have been able to make this run in newer versions of Windows and on Linux and Macs. I only have experience running this on my Mac, but I believe that his support for Windows users (most of you) is pretty good.


I run this program via an emulator called Wine on my Macbook Pro:


A download for the version of wine that I use can be found here (I use an .app bundle to save myself a load of time compiling Wine manually):


http://winebottler.kronenberg.org/downloads



After you've downloaded Wine, you'll need to run the SETUP.exe for Patternz, which will install the program for you (for Mac users, simply install it in the C path destination that Wine suggests).


My Daily Data Downloader:


This was made for me by an old school friend. It downloads historical data from Yahoo's API for the stocks listed in the Tickers file - I have scanned all of these stocks for errors and have removed any that cause known issues (which are invariably due to delisting).


If you change the data in the tickers file you can then change what data the program downloads.


This file is a .exe, but I run this through another emulator called Mono through my terminal. It can be downloader here for Mac users:


http://www.mono-project.com/download/



Once Mono has been installed, you will need to actually download and run the data downloader in Terminal:


You can download the program here:


https://drive.google.com/open?id=0B0wd9XTIWftmflprMFNfdG1DYVZ0TXU5RWlTZHJUYi0zYmJDSXZuMk1IWGtraTZzSy1tY0E&authuser=0


1. You need to tell the terminal where you are running the program from:

- Drag and drop the folder where the downloader exists into your terminal window.


2. Press return once or twice to check for errors and also to make a new line.


3. Type "mono" (with no quotation marks).


4. Type "chmod +x <drag and drop the .exe here>" (with no "" or <> marks).


5. Press return a couple of times to check for errors and also to make a new line.


6. Type "mono <drag and drop the .exe here> tickers.exe" (with no "" or <> marks).

- You need to add the tickers file at the end so the program knows what data to get (drag and drop into the terminal window or just type its name if you haven't moved it out of its folder).



Hopefully this should now just run and if so EPIC codes will appear down the terminal window - if something goes wrong it will fire an error message at you.



Changing the names:


In Mac's OSX Yosemite this is really easy: Navigate to the folder with the data in, select the all of the files and right click and pick the rename function for all of them. Chose to replace the ".L" with blank space - the ".L" simply tells the program to search for stocks listed in London.


If you have an older version of OSX I know that some people have had success with using excel to remove the ".L" tag.



Using these programs in tandem:


Now, assuming that the downloader worked for you, you now need to open up Patternz (right click and run in Wine.app for Mac users) and you will need to configure the settings for the English date format (the fourth setting down under the settings tab I believe).


Then using the navigation bar built into Patternz, navigate to the data folder and select your files.


All going well, this should now work!


For Windows users, this should be a lot easier and both programs should hopefully just run without input from emulators (being a Mac user I can't confirm this).



Known Issues:


1. 

Sometimes, Wine claims that it can't find the source data files for the program (not the data downloader).


If so, simply remove the wine prefix (click the wine icon on the top toolbar, click "Change Prefix" and click the "X" button next to the prefix.

Next, delete the Patternz folder and reinstall it (you don't need to reinstall Wine).


For me, this fixes the issue for a few more runs of the program.


2. DO NOT DRAG THE DATA FOLDER INTO THE PATTERNZ FOLDER!

Doing this is a certain way to cause the glitch described in point 1 above.








I hope this helps someone,

The Masked Stock Trader

Free UK Technical Analysis 07/04/2015

DISCLAIMER: I am not FCA authorised or authorised in any sense to give financial advice. Do not regard any of the following links, or information as investment or trading advice.

N.B. Currently FireFox does not support Google Drive and therefore these reports may not open.

Today's Analyses:

https://drive.google.com/open?id=0B0wd9XTIWftmfkRPeVFOZTBIa1E5OWlNUjRRMmRPSi1Oblo5WUlNRDdMUUdhLWdHTXhwajQ&authuser=0

How to use these reports:

http://themaskedstocktrader.blogspot.co.uk/2015/03/technical-analysis-instructions.html

More information regarding this project can be found here:

http://themaskedstocktrader.blogspot.co.uk/2014/11/my-experience-with-quantitative-finance.html

Quindell - The Stages of Growth.

A quick post today,


Now, the idea for this post isn't original, as I pinched the premise from a bulletin board post that was emailed my way! Nevertheless, I feel that it's a good representation of where Quindell is relative to its past-self.


I'm going to begin this "story" (for want of a less patronising word) back on November 15th 2013, when news was released to the market regarding the oversubscribed placing "to fund growth opportunities" for £200m.


From here I'm going to allow the table below to express the majority of the story (these are figures that have either been plucked from RNS' or the Quindell website:

Position in Year	Gross Revenue/£m	Total Cash Position/£m
2013 H1	163.3	35.2
2013 Q3	92.1	23.3
2013 FY	380.1	199.6
2014 Q1	162.9	150
2014 H1	357.3	85
2014 Q3	200	78.9

Now, the danger here is that we forget a couple of things prior to our analysis of these figures:

1. Companies cost money to run and this constantly eats into your cash position.

2. Quindell paid off some £6.5m of debt between the H1 and Q3 results, which again, eats into cash.

3. These revenue figures aren't consistently accumulative in this table, so if a low number for one quarter sticks out you need to add it to its previous half yearly result to put it in a yearly perspective (comparing quarters and halves can get confusing if you're not switched on). 

Analysis:

1. We know there's a time lag of between 6-9 months on the majority of the contracts that Quindell takes on and this goes a long way to explain the falling cash position from the 2013 FY results onwards, because obviously the company will still have outwards expenditure in this period of lag.

2. Quindell became cashflow positive around Q4 of 2013, which means that in the next FY results (to be released in January I think) should be significantly stronger in terms of cash - especially if Quindell continue their ability to outperform their own targets!

3. To make this story easier to understand, let's pretend that the cash position in 2014 H1 and Q3 is the same (we're effectively discounting the debt they paid off). If we do this it then becomes clear that we're at the end of this lagging period and we can expect a significantly improved cash position in the next set of results (along with better profits, revenues, etc).

4. Thus, if you jump twelve months forward in your head, you can see that there's still a vast amount of potential for the company, which is simple not represented fairly in the current share price:

- With a market cap of just under £300m Quindell is currently worth less than half of the revenue it's expecting to take in the whole of 2014 (companies almost always trade a premium)! 

- When ordering UK listed stocks by PE ratio Quindell is around 38th out of all of them listed (although this is using Google's Stock Screener, which I think is a bit questionable, so I recommend you play around with it)!


https://www.google.co.uk/finance/stockscreener

Before I sign this off, I would implore people to read this explanation of the "sale and repurchase agreement", which everyone seems to be misunderstanding (possibly intentionally):

http://themaskedstocktrader.blogspot.co.uk/2014/11/quindell-loan-agreement-what-is-repo.html

All the best,

The Masked Stock Trader

About Me

I'm an ex-grammar school (not that this matters) trader and investor with a passion for finance and in particular the stock market, after having opened my first trading account shortly after my eighteenth birthday.


Currently I trade physical shares with a bias towards the AIM and sub penny stocks, but I have an ambition to move onto trading CFDs and other forms of derivatives when I feel I have amassed more experience and furthered my education regarding these exciting and potentially dangerous products.


I was formerly known as "The Masked AIM Trader" and all of that past content can still be found on this website.



Other Websites:

http://quanttools.blogspot.co.uk/