Friday 26 June 2015

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



Saturday 13 June 2015

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