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Timing Is Everything

It is no secret that I am not a fan of fund managers of any kind, be they the more exotic style of hedge fund that exists as an idiot tax for those who invest in them, the standard vanilla equity investment fund or the legally mandated rip off that are superannuation funds. My objection is simple, if you are going to take billions in fees  from people then you had better deliver something other than perpetually under performing the market. In a puff piece that looked somewhat like a marketing exercise Morningstar the ratings agency has named the top investment funds in Australia and the list was picked up by Fairfax and covered here. I have copied the list of top funds below.

1491953010731

Source – Fairfax

The article talks about the value of investing in the number one ranked fund since it has outperformed the index over the last 10 years – this point got me thinking about using 10 years as a point of comparison and the notion of starting points in general. As a general point I find selecting 10 years interesting since it makes certain that the funds are compared against the index during and post the GFC and it doesn’t take a genius to work out that the average return from the index since that time has been poor.

I decided to have a deeper look at the impact of starting times upon portfolios by digging up some data on the All Ordinaries Accumulation Index which is now referred to as Total Return Index since it includes the return from both gains in the index and dividends. Starting in 1960 I looked at what your average return would be to the present day if you had started investing at a given point. For example if you had invested in an index linked fund in 1960 your average return up until the present date would have been 13.53% whereas if you had begun your investment journey in 1994 your average return would be 9.99%. This might not seem to be a substantive difference but over time it adds up to a small fortune.

Capture

What interested me when I looked at this data was the remarkably consistent nature of the returns – they are all positive. Whilst, this is to be expected it is nonetheless interesting that the index doesn’t put together strings of negative years and this is shown in the raw data that I will look at later. What is also evident is that there seems to be a tailing off in average returns which is more obvious when this data is plotted as a chart.

r2

The reason for this drop off can be found in the raw data as shown below. This data is the true return for the index for each year in the sample.

r1

In this table I have highlighted each year where the return was over 25%. You can see a cluster of such returns in the 1970’s and 1980’s with a drop off in 1990 and 2000 and since 2010 there has not been such a year. In performance outliers count disproportionately and when they are lacking things look bleaker. I have no real explanation as to the rationale for the drop off in returns although I would surmise it may be simply due to a lack of funds flowing into the market due to the real estate boom. My recollection of the lift in 1991 and 1993 where due in part to the pent up recovery in the market post the 1987 crash but also that real estate struggle under the regime of high interest rates so we had an asset rotation underway.

Despite this drop off in returns over the past decade there is still no compelling reason to buy a managed fund. However, it is important to note that these are average returns over deep time – it in no way diminishes the importance of not being in the market when the market has nothing to give you. What also amazes me about fund managers is that they believe timing is so hard when in fact with simple mechanical rules it is remarkably easy as I have already demonstrated here using the ETF STW. Trading is only as hard as you make it or in the case of fund managers it is only as hard as you want to make it appear.

 

 

 

 

Winners and Losers

I have been thinking some more about the issue of short selling and the problem faced with the upward bias of equities. Armed with excel I decided to look at the average gain as a function of the average loss for the stocks in the S&P/ASX 200 – once I had the data it was a simple matter of dividing average gain by average loss for the past year and seeing what the data said.

Gain_Loss

I have colour coded the data in the following way – those coded blue are above average, those coded orange are below 1. The higher the number the better the performance of the stock in terms of its average gains versus its average losses over the past year – this doesn’t necessarily mean that the stock was a runaway winner in terms of trend trading but rather it had a strong propensity to make good its losses. It should also be noted that all this does is tell us a little bit about the past and nothing at all about the future. Ideally, if you were a stock picker you would want to look back and see a high number and a strong propensity to trend over the long term – the winner for this period of data is WHC.  In terms of losing stocks a ratio of 1 could be interpreted as the stock simply meandered during the year and congested and a ratio of below 1 is a bad sign.

What is interesting to me is the strength of the upward drift in stocks. However, it does need to be considered that the S&P/ASX 200 is a biased sample size since stocks are in effect selected for their upward drift. My guess is that if I were to repeat this list next year some 20% of these stocks would baring some miracle have been dropped from the index and replaced.

 

 

Even The Best Stock Pickers Cant Beat Bots

BlackRock shook the world of active management on Tuesday when it announced that it had fired five of its 53 stock pickers. BlackRock will also move $6 billion of the $201 billion invested in traditional active management to quant strategies.

The announcement may not sound earth-shattering, but it augurs a larger trend: Traditional active management is dying, but perhaps not for the reason you might think.

 The evidence has piled up in recent years that the vast majority of active managers fail to beat the market net of their fees. A common reaction is that beating the market is too difficult and that it’s therefore a waste of time and money to try.

But just the opposite is true. As I’ve previously noted, the problem is not that active managers fail to outperform the market; it’s that they keep that outperformance for themselves through high fees. In the meantime, index providers have turned traditional styles of active management — such as value, quality and momentum — into shockingly simple indexes run by computers. Those indexes have beaten the market and are now widely available to investors as low-cost smart beta funds.

Smart beta has proved to be a popular alternative to traditional active management. According to Morningstar, investors pulled $313 billion out of actively managed mutual funds over the last five years through 2016. At the same time, they invested $314 billion in smart beta mutual funds.

More here – Bloomberg Gadfly

PS: This is not so much fear the bots as fear the model. It has long been known that humans cannot beat simple models that can be run on home computers. Stock pickers or analysts generally do not have a model for stock/instrument selection rather they have a very loose aggregation of factors that are based around the need for a compelling narrative. And narrative is the least reliable mechanism we have for making a judgement since it more often than not flies in the face of data.

WTF Is All The Fuss About

This article is apparently doing the rounds and it purports to look at the supposedly new development of predatory short selling and uses the attack on Quintix by the US group Galucus as proof of this and along the way we get the usual dose of perceived wisdom from Gerry Harvey. Whenever such a piece on short selling appears it is predicated on a few basic assumptions.

  1. Short sellers drive down the price of instruments thereby engaging in a form of pseudo market manipulation
  2. Short sellers tend to target decent businesses and decent people and are therefore un-Australian
  3. Short sellers know what they are doing and are always profitable.
  4. Knowing which stocks are being shorted will give you an edge.
  5. Predatory short selling is a new development.

The article identifies a series of stocks that are among the most shorted on the ASX and I have reproduced this list below since it gives me a starting point for looking at some of the actual data surrounding these stocks.

shorts

What I wanted to look at was some of the performance figures that you might derive from shorting these stocks. The first thing I did was assume that exactly one year ago 1 shorted $1 of each of these stocks. I then valued these stocks as of last nights close and generated the following table.

value of $1

The current value of this basket of stocks is $10.9, so in a year I have made $0.10, if I had simply bought the index and held it passively for the same period I would have made $0.11. Speculation has to be worth the effort, particularly speculation such as short selling that exposes you to substantial risks and can be regulatory and management nightmare. However, this sort of comparison is unfair since short selling is a trading strategy – it requires active management. So it would be more appropriate to look at the peak to trough movements in these stocks over the past year and this is what the table below tracks.

up_down

As can be seen some of these stocks have had substantial movements in the past year and there are only three where movement to the upside outpaces the move down. Interestingly, as a statistical fluke the average gain and average loss sits at 31%. From a trading perspective there always needs to be a recognition that stock prices move in both directions – unfortunately for passive investors fund managers only seem to accept that stocks prices move up. The value of short sellers is the knowledge that markets move in both directions and that this provides an opportunity for profit. However, this raises the additional question of whether short selling has both an influence on price and is utilized to make a profit. For this to occur large short selling positions need to be put in place whilst the stock is stagnant and then used to drive prices down. Therefore we should see an increase in the number of shorts before a stock falls and for this number to accelerate as pressure was brought to bear. To test this assumption I looked at some charts from the Shortman.com.au site which is used as the basis for the first graph in this piece and I have reproduced them below.

table

To be honest I am buggered if I can see a relationship between the lift on the number of short sellers and a decline in price. What I see is a mixed bag of short sellers being late, being early, not being there at all and getting lucky. Granted using the old Mark 1 eyeball is a dangerous thing and I cant extract the data to look at the true correlation between short sellers and price. But if it isn’t obvious then crunching it statistically to find some form of relationship isn’t reliable. So we come back to the basic questions I posed above and it is worth summarising an answer to each –

Short sellers drive down the price of instruments thereby engaging in a form of pseudo market manipulation

Not from what I can see. In fact if anything short selling is a boon to the market since it aids in liquidity, price discovery and as ASIC found much to its chagrin during the GFC it dampens volatility.

Short sellers tend to target decent businesses and decent people and are therefore un-Australian

People who complain about short selling fail to understand the basic mechanics of all trading is to elicit price discovery. The marekt then votes on its future view of this discovery – markets look forward not nackswards. So when you see the price of groups such as HVN get the wobbles it is the market voting about what it perceives to be the future prospects of this company in light of changes in technology, consumer bahvious and competition.

Short sellers know what they are doing and are always profitable.

Not from what I have seen

Knowing which stocks are being shorted will give you an edge.

See above – also consider the most you can make is 100% and that is functionally impossible. Simply Google best performing stocks of 2016 and this will give you an idea of the side of the market you want to be on.

Predatory short selling is a new development.

From my historical perspective I would say that short selling now is harder than it used to be. There are restrictions on naked short selling and the settlement system we operate under makes it hard to game the system. Back in the day when we had 14 day settlement you could short sell a company and buy it back before settlement and if you were careful no one was any the wiser. With instantaneous settlement this is actually very hard to get away with. As I said from a simple back office perspective short selling equities is a pain in the arse.

 

 

 

 

I Think This Says Americans Have Gotten Fatter But Not Smarter….

Does News Move Markets….Sort Of…Maybe…Well No Actually

I was chatting the other day with someone who was having trouble with their trading system. Their approach was based on trading news events. Such a plan is predicated on the notion that news events move markets in certain ways and whilst this movement might not be wholly predictable it will at least generate some form of activity. Such a trading system has a single giant assumption – that news and news related events move price. If this maxim does not hold up then the system is a bust.

It has been sometime since I looked at this question and I had a vague recollection of research done in the 1980’s that looked at this question and found that news as a source of trading ideas was a bust. So armed with the dimmest of memories I went looking through my archive and found what I was looking for. David Cutler, James Poterba and Lawrence Summers produced a working paper titled What Moves Stock Prices for the Department of Economics at MIT in 1988. This paper looked at the 50 largest single day moves in the US market since World War Two – I have included the events from the original monograph below.

Event 3

If you take a cursory look at the events above you could argue that news events do move markets. However, there is a glitch in that some movements defy explanation – there is simply no event that can be seen as a casual trigger for a market move. Cutler et al stated that news events could really only be useful as an agent for movement in about half of all cases of the variance in stock price movement and in my world half is a fluke.

The interesting side issue with the work of Cutler et al is that it puts another hole in the Efficient Market Hypothesis because stock price movements according to the EMH reflect the assessment of investors to new information. If markets move without the the addition of new information to the system then something else is happening that is not explained by the EMH. And it seems in the case of broad brush analysis as performed by Cutler that prices move without any significant input.

This initial work has been expanded upon by Ray Fair at Yale University who looked at outsized movements in the S&P500 futures contract. This new work had much greater granularity to it in that it looked at five minute data, something that would have been difficult in the original work by Cutler and crew simply because the available technology would not have allowed it. Fair compared what he defined as big movements with news items emanating from the Dow Jones News Service, Associated Press and New York Times. The upshot of this investigation seemed to be that the majority of large events have no news based driver. They were only able to attribute a news item to 69 of the 1159 big moves that were examined. Recent  flash crashes seem to support this notion of significant market moves  occurring without a notional driver.

So we come back to the original assumption that news events drive markets and that these moves offer opportunities that can be traded. It would seem on the evidence available that this notion is false.

Nothing To See Here

With a free afternoon I decided to look at the individual performance of stocks that make up the ASX 200 since the beginning of the year. What I did was assume that you invested $1.00 into each on the first trading day of the year and then see what their current valuation was. The table below maps them from highest to lowest.

table

It doesnt take a genius to work out that you will get a spectrum of values ranging from the very good – BGA to the very bad – ISD. The count is mildly positive with 109 stocks being at breakeven or above for the period. You can get a better sense of the distribution by looking at the frequency distribution of values below.

table 2

As you would expect there is a fat hump in the middles and two reasonably even tails. Some did really well, some did really badly and most didnt really do much However, this once again raises the question of the value of this sort of analysis and I would say outside of curiosity there is none. But it passed the afternoon and satisfied my curiosity.

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The Trading Game Pty Ltd (ACN: 099 576 253) is an AFSL holder (Licence no: 468163). This information is correct at the time of publishing and may not be reproduced without formal permission. It is of a general nature and does not take into account your objectives, financial situation or needs. Before acting on any of the information you should consider its appropriateness, having regard to your own objectives, financial situation and needs.