DISCLAIMER: This should not be seen as financial advice to buy or sell stock!
Morning,
I'm a technical fan of Gulf Keystone Petroleum (GKP), but I'm going to put that to one side for the moment and briefly discuss the positive changes that have occurred recently that have made me decide to add to my long position here:
1. Independent Oil Sales:
- To quote the 29/06/2015 RNS: "Currently, sales of Shaikan oil comprise crude oil export deliveries by truck to the Turkish coast and sales to a domestic buyer under a new six months contract which provides for off-take of between 12,000 and 40,000 bopd."
- This suggests to me that we're finally in a place where the cash position can be allowed to either grow slightly and or remain in a neutral position.
- In addition to this, the chances of a placing being required to satisfy the bond holders of the company in accordance with the general overheads is now significantly reduced.
- If this 12,000-40,000 is sold at the rumoured market rate of $29/barrel (see LSE.co.uk), then this gives a daily revenue stream of between $348,000 and $1,160,000, which should certainly provide some stability to the company in the short term.
- Added to this, the rumour on the market (see LSE.co.uk) is that the current production rates are been split between this independent and the Kurdistan government at a 50/50 ratio, giving a daily revenue figure of £580,000.
2. Kurdistan Bond Raising:
- This is a possible fundamental change in the region that will allow for the possible repayment of debt to GKP by the Kurdistan government along with the future payment of oil produced - this begins to reassert the company's potential dominance in regards to both its production expansion and its asset size.
3. Kurdistan Vs ISIS:
- Kurdistan have proven themselves to be a very good weapon against ISIS in conjunction with US Army technical drone support, which places GKP in a much more geopolitically safer place toil companies in the region.
4. Recent Institutional Activity:
- According to Morning Star, the following funds have recently added positions in the company:
iShares MSCI EAFE Small-Cap
iShares Core MSCI EAFE
SPDR® S&P International Small Cap ETF
iShares Core MSCI Europe
iShares MSCI Europe Small-Cap
iShares MSCI United Kingdom Small-Cap
iShares MSCI Global Energy Producers
http://investors.morningstar.com/ownership/shareholders-major.html?t=GKP
5. Asset Sale Probability:
- All of these factors (especially the increased chances of an increase in payment consistency) add to the potential value of the company to potential bidders and a cashflow positive environment for the company would make GKP a significantly more viable bid for larger companies.
- We must also remember that they are sat on what can only be described as a "world class" asset, which under the current low share price makes GKP a screaming target for M&A in the Kurdistan region.
- On a balance of probabilities the chance of a significant increase in the share price seems more likely over the coming months and years than a major fall, but as ever, do your own research.
Enjoy,
The Masked Stock Trader
This is my commentary on general personal finance and specifically stocks listed on the UK financial markets, with a bias toward the AIM. I am not FCA authorised, so none of what I say is to be taken as financial advice.
Tuesday, 7 July 2015
Saturday, 4 July 2015
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.
- 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:
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
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
Labels:
AFR,
BOO,
CFDs,
Education,
PLUS,
QPP,
SBRY,
Short,
short selling,
Spread Betting,
The Masked Stock Trader,
TLW,
TUNG
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
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
Friday, 29 May 2015
Free Technical Analysis Tools
Below are a list of online tools that I have found useful as a (for the best part) technical swing trader of equities:
Free Chart and Candlestick Pattern Scanners:
http://stockcharts.com/def/servlet/SC.scan
https://www.britishbulls.com/Default.aspx?lang=en
https://www.americanbulls.com/Default.aspx?lang=en
Free Candlestick Pattern Statistics:
http://thepatternsite.com/CandleEntry.html
Free Chart Pattern Statistics:
http://thepatternsite.com/chartpatterns.html
Free Live Trade Data:
http://www.moneyam.com/
https://www.google.com/finance
Free Learning Resources/Idea Generators (UK):
https://www.youtube.com/user/zakmir1
https://www.youtube.com/user/TheMarketSniper
Enjoy,
The Masked Stock Trader
Free Chart and Candlestick Pattern Scanners:
http://stockcharts.com/def/servlet/SC.scan
https://www.britishbulls.com/Default.aspx?lang=en
https://www.americanbulls.com/Default.aspx?lang=en
Free Candlestick Pattern Statistics:
http://thepatternsite.com/CandleEntry.html
Free Chart Pattern Statistics:
http://thepatternsite.com/chartpatterns.html
Free Live Trade Data:
http://www.moneyam.com/
https://www.google.com/finance
Free Learning Resources/Idea Generators (UK):
https://www.youtube.com/user/zakmir1
https://www.youtube.com/user/TheMarketSniper
Enjoy,
The Masked Stock Trader
Tuesday, 12 May 2015
Long Glencore and Thomas Cook
I went long on Glendora and Thomas Cook yesterday morning.
Thomas Cook (TCG):
Thomas Cook (TCG):
- This is a volatility funnel trade (very similar to a symmetrical triangle formation really) on the daily chart beginning at the high on April 10th.
- I am looking to exit between 165p and 170p here and I'll begin to rethink/.reanalyse the position at the 150p level and exit at 145p.
Glencore (GLEN):
- This is simply a medium term upwards trend follow.
- I'm looking to exit between the 325p and 330p level. I will begin to reconsider/reanalyse this trade at 195 and probably exit at a break of the 190p level.
Enjoy,
The Masked Stock Trader
Labels:
Company Analyses,
FTSE,
GLEN,
Glencore,
Investing,
TCG,
Thomas Cook,
Trading
Friday, 1 May 2015
Swing Trade Portfolio (New Year)
Here is where I will be posting my track record for the main technical swing trade portfolio that I manage (note that I publish/have published technical analysis reports for all of the below trades):
Company/EPIC | Buy Date | Sell Date | Trade Gain or Loss/% |
QPP | 8/12/2014 | 12/3/2015 | 2.880232384 |
TUNG | 12/3/2015 | 31/3/15 | 7.18887598 |
WSG | 31/3/15 | 21/4/15 | 7.605917992 |
GKP | 21/4/15 | Active Trade | Active Trade |
GLEN | 11/5/2015 | Active Trade | Active Trade |
TCG | 11/5/2015 | Active Trade | Active Trade |
Labels:
AIM,
Company Analyses,
GKP,
Long,
QPP,
Swing Trades,
Technical Analysis,
TUNG,
Volume,
WSG
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