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

What is Short Selling?

In my experience, the process of short selling securities (making money from the security in question falling in price) tends to be a pretty contentious issue around bulletin boards for popular mid to small capped UK listed stocks.

In part this will be because we all have an inherent desire to find anyone but ourselves to blame when we make an investment mistake and often short sellers of the securities in question take the brunt of this.

I should make my stand point clear here and say that I have no issue with the actual process of short selling, but I do have a particular dislike for coordinated short selling attacks based on lies, which I feel aren't as widely dismissed by the investment community as "pump and dump" market manipulation is - see Quindell plc for an example of a great company that's been trashed by coordinating short sellers.

Now, there are actually many different ways in which you can effectively bet on markets falling in price - Spread bets, Contracts for difference, etc.

How the short selling of shares works:

The easiest way to look at this is to reverse a usual share transaction (excluding commissions, tax, etc):

Let's assume that you purchased an asset for £100 and sold it for £1,000. 

- Profit = £900

Now, we'll turn this around and sell our asset for £1,000 and then buy it back at a price of £100.

- Profit = £900

More specifically, it works like this:

                        Hedge Fund                             1,000 Shares                          Pension Fund 

                                 or        <------------------------------------------------------          or 

                      Asset Manager ------------------------------------------------------> Large Bank 

                                                                         

1. I  borrow some shares, for a small fee, normally from a pension fund, because they have lots of shares that just sit around doing not a lot. 

- By allowing shares to be shorted the pension fund can make a little bit of money effectively risk free.

2. I sell the borrowed shares into the market.

- E.G. I sell 1,000 shares (in a company of your choice) at £20 per share.

3. I buy back the borrowed shares.

- E.G. They're bought back for £10 per share.

Profit = £10*1,000 =£10,000 (excluding the pension fund's fee).

4. Return the shares to the pension fund.

Naked Short Selling:

This is the process of utilising the settlement delay on trading contracts, to make up for the fact that you're selling shares into the market that you haven't been able to borrow from anyone - it's an uncovered bet effectively.

Dangers:

The biggest danger with short selling shares is that you may not be able to repurchase them in the market if the position begins to go against you. This is known as a short/bear squeeze and can be pretty devastating, as you can lose a vast amount more than the long equivalent of the position (someone buying shares only has a maximum risk of 100%, while short sellers can risk more than this if the price rises more than 100%).

Banning Short Selling:

Regularly, people call for the banning of short selling and in 2011 four European countries did implement this temporarily regarding the stocks of major banks, but in reality this didn't work for a couple of reasons:

- A ban needs to be pretty much global or the hedge fund just move to jurisdictions where they can legally short sell.

- Also, without the ability to short sell, you suffer from a very large component of the hedging tools available to funds disappearing instantly.

- It would really need to be done on all forms of short selling (via derivatives), not just the short selling of shares.

- Banning short selling is also just inherently silly, because if a share price is falling then it's going to fall anyway - bad business practices cause falling share prices. However more importantly than this, if you remove a very large aspect of the stock markets then you're going to reduce the total amount of trades and thereby increase market volatility.

- In order for a ban to be effective it has to cover all stocks, not just sector specific ones, or it just moves short selling pressure elsewhere.

Enjoy,

The Masked Stock Trader.

Quindell - Pseudo-Automatic Market Makers and Algorithms

Good evening,


I've discussed before my ardent love for Quindell plc, so I'm going to put that to one side and focus on a short selling strategy that the likes of Roble S.L and others could well be using to manipulate the market and increase their profit potential.


I actually discussed the concept of Automatic Market Makers in a post from this morning that can be found here for those interested and this leads nicely on from that:


http://themaskedstocktrader.blogspot.co.uk/2014/11/what-are-market-makers.html


As I said in that post, Automatic Market Makers (AMMs) are part and parcel of the world of High Frequency Trading (HFT) and are effectively used to force large orders that have split up and put through via algorithms to execute towards the higher end of the price ranges sent by the algorithm in question.


My theory regarding Quindell is that parties with major short interests are performing biweekly "rinse and repeat" procedures on the stock, in part through the use of preventative orders (refilling the order book with sells after significant purchases to prevent the SETS system from ticking up the share price substantially), but also via the use of pseudo-AMMs.


With having a sort of pseudo-AMM in place (I'm calling it a "pseudo-AMM", because it's not actually used in the market making process in this case, but operates on the same principals), institutions with a short interest in the company could take advantage of the third party showing of trades and increase their profitability:


Trades are reported to the stock exchange accurately as buys or sells, but the third party platforms that many people use take the trades and the spreads through the day, to come up with an assumed buy or sell reading depending on the price of that trade and its position within the bid/ask spread at that point.


By using some form of pseudo-AMM, large institutions can ping back and forth to make sure that their "real" buy trades are filled at prices that fit the mid point or below of the spread, thus making them appear as sells, or unknown trades to the majority of retail investors.


Combined with filling the bid side of the order book to cause downwards pricing pressure, this allows the three following points:


1. The subtle accumulation of large numbers of shares through split algorithmic orders (being on the other side to an AMM, as it were).

2. The accumulation of shares within price ranges that misrepresent their real status in the order book.

3. The suppression of the share price and thus the demoralisation of retail investors.


Food for thought...


The Masked Stock Trader