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The Great Idiot Tax Continues

It is at this time of the year when superannuation funds crow about how good they have done and of their inestimable benefit to mankind in general and this year was no exception.  So as is my now annual tradition I thought I would have a look at how good they have done and compare that to the real world where delusions about how good you think you are dont exist. From the article I linked to I took this table which looks at the average return of a a growth fund since 1993.

Screen-Shot-2017-07-03-at-1.44.22-pm

Source – Superannuation returns above 10% for the June Year

This piece acts as a good starting point for comparison with the market. For this I used the All Ordinaries Total Return index which used to be known as the Accumulation Index. It includes not only the price movement of the index but also folds back in the dividends of the index components so it is a good benchmark for simply passively holding an index fund or ETF.

Capture

When the chart of the average return of a growth fund is first viewed it does create an overall favourable impression – there are only three negative years and returns seem overall to be quite robust. It is only when you compare this active management with a passive benchmark that you realise how poor local managers actually do when compared to the index. Remember these are people who are paid to beat the index and as we will see they are paid staggering sums of money. Looking at annual percentage returns is quite crude and does lack a bit of fidelity, you dont actually know what the true performance differential is so I looked at the value of $1 invested into an average growth fund and into the index and got the following.

C2

The market leaves the industry for dead – the market investment would now be worth $9.87 versus the industries $5.91 and for this privileged investors have been ripped off handsomely. The chart below looks at what my guess of the annual fee intake of superannuation funds is. For this I have assumed an average fee of 1.5% to cover not only management fees but also advisor commissions.

c3

So to produce a theoretical return of slightly better than half what the market produced  in the period above the superannuation industry has collected probably close to $310B in fees. So to once again steal from Winston Churchill – never in the field of human endevour has so much been paid to so few for so little.

So What Does This Mean?

In my junk folder I have for the past upteen decades been getting random charts by a group called Chart of the Day. Surprisingly, I dont get them everyday – so the implication that you get a chart everyday that is interesting is perhaps a little bit of an oversell. This morning I go the following piece of wisdom –

c2

This chart as the title suggests looks at the S&P 500 PE ratio back to the turn of the century. Putting aside the obvious gaping methodological flaws such as the S&P500 was only started in 1957 I do always find these sorts of things interesting. Markets and their history should be a topic of investigation for every trader, simply because there is nothing new. Bubbles and crashes have been a feature of markets since they began and the driving force behind such things has always been the capriciousness of market participants. Curious as to what our own market looked like I dug up some data from the folks at Market Index and plotted the local PE ratio against the All Ords to see what I could see.

Capture

On the chart above I dropped a series of vertical lines – the three black ones denote a time when valuations according to the markets PE ratio could be considered extreme, the red one is the GFC. Pundits who look at valuation models work on the notion that markets or their component equities have a fair valuation and deviations from this point indicate that something is either overvalued or undervalued. Decisions are then made upon this interpretations. The first black line is easy to identify – its the 1987 crash.  The second one took me a little while to remember until I remembered the tail end of the 1991/2 recession combined with the banks nearly sending themselves under after property bit the dust.  The third black line is the tech wreck, The question when looking at any methodology is what value does it add to your decision making.  This is an important question since our decision making is bounded by the time we have to make the decision, the amount of information we have and our cognitive ability. None of these components can be infinite so our decision making is always somewhat half arsed. However, we need to add to this the notion of decision fatigue. It is estimated that during an average day we make anywhere between 20,000 and 25, 000 conscious and unconscious decisions and each of these decisions extracts a toll. Decision making is not a free ride, everything has a cost. Therefore efficiency of decision making is of paramount importance. If you have to force a decision then you are merely adding to your own mental loading without achieving anything.

As to whether the chart above tells me anything I dont already now about market extremes is doubtful As to whether it adds anything to my overall view of the world and approach to trading I am certain it doesn’t. But your mileage may vary.

Property Versus Shares

I was mucking around on the Valuer Generals site the other day searching for historical bits and pieces relating to my property when I noticed that the VG kept historical records on their estimation of the median house price in Melbourne. One of the things I have always found difficult in real estate is not the paperwork, the land rats, tenants, maintenance or the incredibly primitive way that houses are actually sold but rather the paucity of data that surrounds their instrument. Reliable and consistent data seems to be very hard to find and this was an issue I found when I was looking the the VG estimations – I couldn’t get them to tie in with other bits and pieces I found. However, only the VG site had any depth of historical information. Imagine trying to deal in a stock that had half a dozen conflicting prices from different sources, none of which you could actually deal in because prices are largely made up and then trying to find out what the price was five years ago only to get another half a dozen differing prices. It seems as if the real estate market is deliberately set up to be obscure and in some ways reminds me of an embryonic options market where those involved either didn’t understand their market very well or were being deliberately opaque.

Out of curiosity I downloaded the VG’s median house price data just to have a look at the trajectory. Because I am frequently bored I like to look at the history and structure of various markets – too few people are actually students of the markets they operate in. As such they miss out on a large number of free lessons that can short cut their process. No one makes original mistakes in their investing, everyone has made the same mistakes before you and the lessons from these mistakes can often be found in the data. Whilst mucking around with the data I remembered that the ASX often produces a comparison between the returns that are generated by various investment categories. I have always thought that these comparisons had a flaw in that they relied upon simple average returns, looking at averages is fraught with danger because they can be extremely misleading. Which is why managed funds constantly quote them.

As an extreme example consider the following investment scenario. I discover a magic fund with brilliant marketing material and on day one of year one I invest $100,000. In the first year the fund makes a return of 100% and I think I am a genius. In the second year the fund loses 50% and naturally I think the fund manager is an idiot but I am consoled by the fact that the year before I made 100%. When I present this scenario to people I ask them what the average rate of return is for those two years and most people answer correctly – it is 25% (100%-50%/2). I then ask how much have I made on my original $100,000 and I generally get an answer in the ball park of $100,000 x 25%pa. These guesses range from $125,000 to $150,000 as people try and do a compound interest calculation in their head. The truth is I have made zero – in the first year I doubled my money and in the second year I halved my money thereby returning me to my starting point. Yet my average return is 25%. This is why when looking at returns we have to be careful about using a long term average to generate an idea of how much we would have made. It is better to look at each individual piece of return data and assign a dollar value to it. This way you can build some form of equity curves which gives you a lot more information as to the trajectory of the value of your investment.

For a bit of fun I decided to take the data from the VG’s site and apply the returns from the All Ordinaries Total Return Index to their initial starting capital of $75,500 and see what the comparison between the two was. In effect I built an equity curve for the median house price and an identical investment into a surrogate ETF.

hp1

I have to admit I was a little surprised at the size of the differential because when you hear talk of comparisons between the two investment vehicles the impression you get is that the returns are quite close and that with the runaway bull market in housing that property has been the place to be for long term passive investing. Plotting data like this enables you to get a sense of the trajectory of price and to me two things are immediately apparent. Equities are more volatile in terms of a passive investment and this volatility is apparent in the impact of the GFC. Property moves a little like a truck, slow and steady whereas equities tend to throw themselves around a little. However, the shocks are not as severe as I thought they would be, 1987 is a blip that doesn’t appear and the tech wreck was a mild impediment. What did do the damage was the GFC and this is the problem with a simple buy and hold methodology.

To compensate for this volatility and to give a more real world flavour to our surrogate ETF I dropped the loss from the GFC to 10% from the historical 40.38% which is reflective of what actually happened when our macro filters kicked in and dropped us out of the market. The result of this simple fix is interesting.

hp2

The dramatically different result is simply a function of controlling runaway losses and not allowing them to have a detrimental impact upon your equity. Such a technique  is not rocket science but it does seem sufficiently difficult that it eludes all professional money managers.

Despite what the data says I am doubtful that it will convince die hard property advocates of anything – people with firm opinions are immune to data and it is hard to break the emotional bond that people have with actually owning something. And that is not really the purpose of the exercise as the advantages of equity investing over property investing are many , manifest and quite easy to elucidate. But is does serve as a salutatory lesson in what the differing mechanisms of presenting returns can tell us. It also tells us in no uncertain terms as to why  the worlds second richest individual is a share investor and not a property investor.

 

 

Where Do Returns Come From?

With the market making a valiant effort to push past 6,000 points I have been pondering where the gains in the market have come from over the past few years. In the past I have looked at the distribution of returns across groups of shares simply from the perspective of demonstrating that within a universe of instruments the majority of returns come from a few entities. Naturally the same is true for trading systems – a few trades each year provide the bulk of the returns. This feature of trading is one of the hardest for new traders to adapt to since they assume that trading is like other jobs where you are rewarded at the same rate for the same amount of effort.

I thought about broadening my horizon to look at the balance of returns that occurs between price movement and dividends across a given market since this data is reasonably easy to obtain and therefore manipulate.  I took a look at the difference between the All Ordinaries index and the All Ordinaries TR index.  As a simple raw observation the All Ordinaries hit its nadir post the GFC on 13/03/09 when its low hit 3090.80, its last full weekly close was on 21/04/17 when it closed at 5885.60 – this is gain of 90.42%. The All Ordinaries TR had a low of 20,858.64 on 6/3/09, since then it has climbed to 55,605.18 – a gain of 166.58%. There is a substantial difference between the long term rate of return of the two indices. Unfortunately, this differential is often seized upon and used by the buy and hold brigade to offer the mantra of simply investing for dividends but I don’t think that is what the data is showing. What the data shows is the naturally higher rate of compounded return from simply folding back dividends into the equation. It doesn’t offer sufficient evidence to support the line of investing simply for the sake of dividends. If it does offer anything it gives a glimpse into the usefulness of a sensible index ETF strategy.

I wanted to take a deeper look at the differential between the weekly returns from the two indices to see if it told me anything deeper about the relationship between the two and the actual stage of the market. The graph below demonstrates the differential between the two dating back to 1996.

differential

As you can see the data is fairly noisy but there are one two points that you can generate from it. There is a distinct scalloping in the data in the early part of the century, my interpretation of this is that this is a natural function of a market running hard. In fast moving markets the majority of index gains come from the generation of dividends. As you move beyond the GFC you can see an expansion in the differential – dividends as a source of internal return have become more important. This is to be expected in lacklustre markets. My feeling is that the downward pulses that you see post the GFC are in part due to price attempting to recover but also are a function of the cyclical nature of dividends.

Whilst interesting I am not certain it tells us anything we didn’t already know. However, when I was preparing this I did have a recollection of an analysis I used to do by hand before the age of boundless and often needless information began to distract me. In the past I used to had chart the All Ordinaries dividend ratio and use it as a measure of market energy and I though ti should be easy enough to see if some clever clogs had done the work for me. And courtesy of two seconds on Google I found someone had. The chart below is from Market Index a group that provide and absolute plethora of markets statistics.

Yield All Ords

As you can see it presents a similar but much clearer picture of the ebbs and flows of the actual dividend yield of the All Ordinaries. As can be seen when price is running strongly the relative impact of dividends decreases – that is the overall yield drops. When markets are doing poorly the average dividend climbs as price collapses. I will leave it to each individual to see if this sort of information adds anything to the veracity of their macro trading decisions.

 

Compounding – if you live long enough to enjoy it.

I have just finished reading Edward O Thorps autobiography A Man For All Markets which is an excellent little read and a good addition to any traders library. In the book Thorp talks about he value of compounding returns. There is no doubt that success is trading or investing is based upon compounding your gains over the long term. Compounding is a wonderful tool in that what seem to be small quanta of difference can over time lead to an enormous difference in returns. For example an investment with a return of 10% compounded annually for 10 years yields $259,374 whereas the same investment compound at 11% yields $283,942. Extend the holding time to 20 years and the figures becomes $672,750 and $806,231 respectively. Time is the key to compounding and this is a point Thorp makes, he also makes the important point that most lack the patience to do this.

However, there is a sting in the tale of compounding that I have noticed that those on the sell side of the business either abuse or simply do not understand and that is one of scale. You will often see very long term charts of an index or an instrument and it shows a wonderful upward trajectory (well you wouldn’t show things that didn’t work) and the message is that you simply have to hold for whatever the requisite time is and you will eventually have a small pot of gold. The key word here is eventually because what is often overlooked is the time to achieve these mythical gains. There is no doubt at all that compounding is a very powerful tool and when combined with consistency and patience achieves remarkable things.

However there is always a but we need to be aware of. To demonstrate this I found a centuries worth of data on the All Ords and using $1 as the starting investment plotted what the return would be over the next 116 years.

$1

If you had started with $1 in 1900 and simply let the compounding returns of the index take its course you would have $487,801.23. At first glance this is quite impressive – the markets very long term rate of return sits at about 9% and if you let it do its thing for a long period of time then you get an impressive number at the end. However, there are two things to be aware of in viewing this data. Firstly, the time taken to achieve your goals, not only is the time itself a problem but the erosion of the value of your investment over time is a problem. I had a cursory look for long term inflation data but couldn’t find much dating back beyond the 1940’s but if you assumed an average inflation rate of 4% then this puts a large hole in the real end value of your investment. The second issue that is not addressed is the trajectory of the journey – the chart above is not of a capital guaranteed term deposit but of an index. The somewhat linear trajectory of the graph is deceiving since it does not take into account the extended and deep bear markets that were experienced. There were years when the market went nowhere and these events are testing for even the most hardened buy and hold advocate.

Time is both the ally and enemy of those who understand how to use compounding and it is this dualism that we need to be aware of. The practical implication of this is to leave your money in your trading account for as long as possible before taking it out and spending it. The impact of large withdrawals is quite remarkable in the damage it does to accounts but some people cannot resist spending in the short term to ensure they live in poverty in the long term

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.

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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.

 

 

General Advice Warning

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.