Investors usually go down the stock picking route because they think they can outperform both the ‘market’ (typically the FTSE 100) as well as professional fund managers.  Of course there is an element of interest and even excitement in stock picking, but at the end of they day if you’re investing thousands of pounds in your own stock picks you’re doing it to make more money than you could elsewhere.

Since that’s the case, tracking your returns over the long term is important just to make sure your efforts are worth it and if they’re not, then perhaps you should either buy the footsie and find another hobby, or get someone else to make your stock picks.

In my case I started value investing in the middle of 2008 and so I now have a three year track record.  In that time I have learnt an enormous amount about both the technical and behavioural side of investing and I hope to put that knowledge to good use in the future.  You can see my results so far on the about page and you can see them in the table below too.

If you turn a somewhat blind eye to 2011 (where performance has been hit in the short term due to a number of speculative turnaround situations I bought into that still have a long way to turn) then the results are satisfactory, as Ben Graham used to say.
In his new book The Investor’s Manifesto, William Bernstein has said that investors who manage their own money must have four traits:

1. An interest in the process.
2. More than a bit of math horsepower.
3. A firm grasp of financial history.
4. The emotional discipline to execute their planned strategy faithfully, come hell, high water, or the apparent end of capitalism as we know it.

Although he concludes that “no more than a few percent of the population is qualified to manage their own money”, for those that are lucky enough to possess those four traits, the extra rewards may well be worth the effort.

For the vast majority that don’t possess all of those traits the answer may be to either find someone who does, or just track the indices and forget about stock picking altogether.

The model that makes up about 80% of my stock picking process has undergone several minor adjustments, one following quickly after the other. Since I have referred to it quite a bit recently I thought it might be useful to thrash out the details as well as its history.

The model detailed here replaced a previous effort which I used through 2008-2010. The old model focused almost exclusively on the balance sheet rather than on earnings, but eventually I had to admit that earnings might be important so I started this new one from scratch, basing it on the strongest research I could find.

Version 0.1 – Fair value and the Piotroski F-score
First I calculate an approximate fair value for the company and hence its shares. I do this by taking the average of ROE10, ROE5 and ROE3 (which in turn are the 10, 5 and 3 year ROE averages) and using that as an estimate of the average future ROE under normal conditions. By blending those historic averages I weight recent results more heavily than results many years ago.

There are various issues with this approach that need to be manually looked at when selecting a company.  For example, companies with extreme ROE figures in some years due to their book value being unusually small at some point. This might skew otherwise weak ROE results upwards and makes them look attractive.

I then assume that fair value is ten times my normal return estimate, which produces a target price from which I can calculate the upside from the current share price. This upside is the first factor in the model as it measures the capital gains you might reasonably expect in the long term.

Sorting companies by upside alone gives a top scoring decile (50 companies out of a universe of 500 with positive 5 year ROE) with these attributes: Normal ROE 15.8%; price/book ratio 0.64; Piotroski F-score 5.6; net gearing 45%; upside 234%.

I use the Piotroski F-score in an attempt to measure where the company is in the business cycle and therefore how far it may be from recovering and being re-priced back to normal levels. It’s better to have a company with 50% upside that may return that amount in 6 months rather than one that may take several years. The F-score may be useful here as it measures changes in returns, cash flow, leverage, liquidity, margins, and asset turnover among other things, all of which help define a positive or negative trend.

To factor in the Piotroski F-score I simply multiply it by the upside so that the higher the F-score the better the company scores in my model.

Sorting on this score gives a top decile with these attributes: Normal ROE 16.6%; price/book ratio 0.7; Piotroski F-score 6.0; net gearing 52%; upside 231%. This gives a higher F-score than before but somewhat higher gearing too. High gearing may or may not be an issue for companies that are well into the turnaround phase.

Version 0.2 – Adds net gearing
The previous version gives an average top decile net gearing of 45%, but this is the product of some companies with almost no gearing and many with over 100% or even 200% gearing. In the name of caution I decided to control this risk by adding net gearing as a factor. This is done by multiplying the version 0.1 score by POWER(2, -(net gearing/100)), in excel speak. This means a net gearing of 0% doesn’t change the score, 100% becomes ½ and so halves the score, 200% becomes ¼ and so on. Net cash produces a number greater than one and so increases the score. This helps bring down the average gearing of the top scoring companies.

Sorting on this score gives a top decile with these attributes: Normal ROE 16.1%; price/book ratio 0.7; Piotroski F-score 5.9; net gearing 23%; upside 223%. This group has slightly lower upside than before but half the average net gearing.

Version 0.3 – Adds absolute ROE
With the previous models, two companies with the same upside and gearing would score the same even if one had a normal ROE of 20% while the other could only manage 10%. After reading the Magic Formula book I was swayed by the argument that a higher ROA or even ROE is better regardless of price as earnings can be reinvested more efficiently. To factor in ROE as an absolute number rather than just in relation to the current price/book ratio version 0.3 multiplies the version 0.2 score by the expected normal ROE, so the higher the ROE the better the score.

Sorting on this score gives a top decile with these attributes: Normal ROE 19.2%; price/book ratio 0.9; Piotroski F-score 5.8; net gearing 24%; upside 218%. Once again the upside has dropped slightly but gearing and the F-score remain steady while average ROE has gone up by 3%.

In comparison, the universe of 500 companies has normal ROE 14.9%; price/book 2.3; F-score 5.9; net gearing 43%; upside -3%. So the top decile has better ROE, lower gearing, about the same amount of fundamental momentum and is lower than half the price (relative to book) of the universal average.
The upside of -3% across the whole universe shows that perhaps there is some sense to my estimate of fair value, given that on average the 500 stocks are about fair value.

One other telling metric is the current ROE in comparison to the expected normal ROE. The top decile has a current ROE some 28% below their expected normal level, which suggests that investors are pricing the companies on an excessively short timescale. The universe as a whole is down 16%, which makes sense as we are in the great recession. The bottom decile, containing the most overvalued companies, has current returns almost 9% above their normal average. This suggests that investors are perhaps overpaying for short term good results, something which value investors have been saying for almost a century.

Unfortunately the only way to know if the differences between these models makes any difference is to test them all together in real time going forwards, which isn’t going to happen. I think it’s likely that they would all perform reasonably well, but each adjustment makes me slightly happier with the selection of companies it produces, which is important if the strategy it to be stuck with over the long term.

Over the years there have been many studies into how different investment strategies affect your potential returns over the long term.  Often these studies involve the selection of companies based on almost childishly simple criteria which ultimately turn out to uncover some hidden truth about market efficiency and the value premium.  Since I use these simple screens to make the bulk of my investment decisions, it seems prudent to check that these simple formula still work when applied to the market as a whole.

Below is a graph of the returns of all companies* in the main and AIM markets in the UK over the last year, where the company had returns for the last 10 years (as I will be sorting by ROE10 shortly).  Sorted by the size of the returns the returns for over five hundred companies looks like this:

As you can see some did well and some did badly.  The average return was 23.7% so this subset of companies strongly outperformed the FTSE 100 and similar indices, but that’s not the point of this exercise.

According to much research (not cited here), sorting by P/B (price/book ratio) is likely to show some sort of trend where low P/B stocks outperform the average and definitely outperform high P/B stocks.  Sorting (descending) by the estimated P/B from one year ago** produces this:

The trend line does seem to indicate what the literature would have us believe – that on average lower P/B stocks have had better returns in the last year.  Breaking the results into five equal groups, the average returns of each group were:

Before getting too excited though, remember that low P/B companies tend to be smaller and less liquid, i.e. with a wider spread.  I think that the extra returns will be enough to outweigh the spread costs, but spread size is an important factor in low P/B and small cap investing.  Something to cover at length another day perhaps along with dividends.

Another point is the spread of returns.  In each group some companies did fantastically while others did terribly.  Unless you can spot the difference beforehand you need to be sufficiently diversified, otherwise you could end up with a massively under performing portfolio no matter which group you pick from.

The next well known and highly tested metric is market cap.  When sorted by market cap (descending) from one year ago*** the returns look like this:

And the quintiles again:

So market cap is still a very useful tool in the selection of outperforming companies.  However, the large spread issues are even greater here as by definition the smaller outperforming companies in group five are small and likely to have greater spreads, especially on the AIM index where most of these shares live.

Just from looking at the plot it seems that the variation of returns from each company is much less for big companies (on the left) than for small.  An efficient market proponent would probably say that’s part of the reason for the small cap premium, the variability of returns is that much greater.

The final metric is ROE10 (ROE averaged of the last 10 years), which on its own is most definitely not a value metric as it says nothing about price.  I’ve included it here though as it’s a GARP metric which is closely related to value investing, but more importantly I’ve started using it recently to sift for winners.  It can be combined with the size and P/B metrics to aid and perhaps enhance them.  Sorting by ROE10 (ascending) gives the following results:

And:

From this it seems that investing in high return companies turns out to have been more than worthwhile, regardless of the price paid for the shares, which is what growth investors have been saying all along.  Note also that the spread of returns in the top performers (right of the plot) seems to be far less than that of top performing small cap or low P/B stocks.  Interesting.

Now onto some combinations.  If I multiply size and P/B it gives:

and:

Which if we look at group five, the smallest lowest P/B stocks, we get the highest returns so far, 31.2%.  Of course this is just a spreadsheet based on data with things like survivorship bias and other reliability issues, but it’s still nice to see that combining size and P/B gives the expected outcome of higher returns.  Note though that group one is a bit of an anomaly (large cap high P/B stocks) with very few losses; perhaps this is the UK large company premium which has been found in a couple of studies.

Finally if I combine P/B and ROE10 I get this:

and:

In this case you have to ignore the first 115 or so companies (the first group pretty much) as they are all negative ROE10 companies where the results are messed up by the negative value.  However, I wouldn’t recommend investing in them anyway as a negative ROE10 is not a good thing.  The remaining four groups show a nice progression of returns up to a high of 31.6%.  What’s also nice about this group is that you get the high returns without always being in micro cap stocks.  The estimated average market cap of group five a year ago was 2.5 billion and less than half the companies are on the AIM index, which helps keep trading costs down via a smaller bid/ask spread.

In summary, value screening still seems to work; or at least it did last year.  Adding ROE or perhaps any measure of earnings into the mix probably does have some benefits.  Of course there are many more screens, as many as investors can dream up; but whether you use this approach, the Magic Formula, low p/e or some other system, screening definitely still has something to offer the rational investor.

* Data from Sharelockholmes.  5 companies from over 550 were removed as outliers returning over 400% in the last year.  Although keeping them in would have favoured the P/B ratio’s predictive ability, by the other measures they were random and skewed the data so I took them out.  Of course in the real world you can’t do that, so perhaps that’s a good reason to pick low P/B stocks, to increase the chances of picking up a mega-mover.

** P/B 1 year ago is calculated from the current P/B and the last years returns, i.e. assumes that book value and the number of shares was unchanged.  This is a naive assumption but I don’t think it is too unreasonable and hopefully it hasn’t skewed the results.

*** Market cap 1 year ago just relies on the number of shares on average being the same, which is a reasonable assumption I think.

Basing my company valuations on book value is nice and everything, and has a lot of historical and empirical support, but I’ve always had a nagging doubt about my core assumption in relation to earnings:

“”Any reasonably competent management should be able to produce returns at some point such that the company is worth its net asset value.””

This is the basis on which I expect to exit the companies I own.  Most companies that are priced well below book value do eventually end up back above it and usually via a higher share price rather than a lower book value.

Reading through some of the obligatory writings of a certain Mr Buffett however, highlights a consequence of ignoring earnings:

“When Buffett Partnership, Ltd., an investment partnership of which I was general partner, bought control of Berkshire Hathaway, it had an accounting net worth of $22 million, all devoted to the textile business.  The company’s intrinsic business value, however, was considerably less because the textile assets were unable to earn returns commensurate with their accounting value.  Indeed, during the previous nine years (the period in which Berkshire and Hathaway operated as a merged company) aggregate sales of $530 million had produced an aggregate loss of $10 million.  Profits had been reported from time to time but the net effect was always one step forward, two steps back.”

The risk to an investor like me is that a company will never sell at book value because it is just not worth that much even with the best management.  Looking at my own holdings, Northamber had produced average returns on equity of 3.8% over the past decade, 600 Group had managed 2% and MJ Gleeson 2.3% (according to Sharelockholmes).  Not exactly electrifying and not a return you’d want to leave the safety of a savings account for.

But does this matter?  Well, perhaps.  Looking back at my ex-holdings and plotting the annualised returns I got from buying and selling them against their 10 year ROE I get the following:

Unfortunately that’s not a lot of data,  but it’s a start for sure and does seem to imply what I’d intuitively expect – that those companies with higher average return on equity find it easier to return to book value more quickly and profitably.  I think it’ll be another year or two before I have enough data to draw a more solid conclusion though (unless there’s some research out there already).

But if ROE is useful then how should I integrate it into my system? 

As a starting point, I have decided that a company must have a minimum average ROE of 5%.  The goal with this is to skew my holdings toward the right side of the above chart.  It might also increase my dividends, but I haven’t check that yet.

In addition to that hurdle, I have adjusted my buying and selling price points.  Previously I’d sell if the price/book was 1.  Now I think I’ll sell when the price/book ratio is ten times the average ROE, or when it’s 1, whichever is lower.  The point here is that in my imaginary world most investors will settle at some point for 10% returns (after all that’s what the stock market historically makes), so a company with an average ROE of 8% should at some point sell for 80% of book value giving the shareholder a 10% return (assuming all earnings are paid out as dividends, but that’s another story).  But, if the company has produced returns above 10% then I take the pessimistic view that they may not match such lofty heights in future and that even if ROE has historically been say 15% then I will sell at price/book of 1 rather than 1.5.

The same logic applies to buying, where I will now only buy if I have at least a 50% margin of safety against ROE10 times 10.  So with the 8% ROE example above I’d have a maximum buy price/book of 0.528 (66% of 0.8) and a sell price/book of 0.8, instead of my previous 0.66 and 1.0 targets.  Of course if I can buy a company more cheaply than this then all the better.

Using this approach I have decided to jettison Northamber, 600 Group and MJ Gleeson from the portfolio, as they were all priced above their ROE10 times 10 valuation.  I’ve replaced them with AGA Rangemaster (average ROE of 8.7%), Barratt Developments (average ROE of 18.5%) and Vislink (average ROE of 9.5%).  A bit drastic perhaps, but at least none of the jettinsonees were sold at a loss (annualised returns of about 14.8%, 2.2% and 22.6% respectively) and both AGA and Barratt bring some well known names into the fold, which makes a change.

Last but not least, I sank some more money into Luminar just to thank them for not going bust yet.  Good work chaps, keep it up and perhaps I’ll get that 462% gain my spreadsheet says I’m due.

My current investing goal is to outperform an ETF tracking the FTSE 100 total return over any given five year period.  However, after reading some more about expected returns and the various sources of those returns I think that goal needs some adjustment.

Whilst I don’t believe the market is completely efficient, I do think that the market is efficient enough so that for most people the odds of adding value via stock picking are virtually zero.  This doesn’t mean that you have to settle for the returns of the FTSE 100 or All Share indices though, or even an international mix of indices.

The CAPM Three Factor Model says that the returns from a diversified portfolio come almost exclusively from Market Risk, Size Risk and Value Risk.  What constitutes a diversified portfolio is somewhat subjective, but according to Elton and Gruber’s paper “Risk Reduction and Portfolio Size: An Analytic Solution” a portfolio of 10 holdings will have about half the volatility of annual returns of a single holding.  More holdings reduce volatility by an ever reducing amount.  If you hold fewer companies then you are exposed to Concentration Risk, which according to the theory doesn’t have any associated return.

Instead the returns come from the market return multiplied by the percentage of stocks in your portfolio (the stock/bond split) and the weighted average beta of those stocks, the weighted average market cap and the weighted average price/book ratio (and a few extra bits about the risk free rate which I won’t go into here).  The lower the average size and price/book, the higher the expected returns. Given that my benchmark is a tracker of the FTSE 100 which is full of large companies and many growth companies and that my portfolio consists exclusively of small value companies, it doesn’t seem fair to just beat that benchmark and claim myself victorious since the model says a dart throwing chimp could do the same.

As yet I don’t have figures for the UK, but there are a number of sources that have figures for the expected return from holding small value companies in the US.  For example, in Mark T. Hebner’s active investor bludgeoning “Index Funds, The 12 Step Program for Active Investors” (available for free at his rather excellent site), he cites the return in the US from 1927 to 2006 from holding the smallest 30% of companies relative to the largest 30% of companies as 3.13% per year, and the return from holding the 30% of companies with the lowest price/book relative to the 30% with the highest price/book as 5.11% per year.

My holdings have a weighted average market cap of about 25 million pounds, which puts them in the bottom 20% of the All Share index in terms of size, so I should expect the full size premium over the FTSE 100 (which by definition is full of the largest companies).  The weighted average price/book of my holdings is 49%, which puts them in the bottom 10% in terms of ‘value’ (ignoring negative book value companies).  The FTSE 100 actually has a fair spread of price/book ratios, so on that basis I think I can reasonably expect to see half the value premium which would be about 2.5%.

Putting that lot together I think a more appropriate target is to produce returns equal to the FTSE 100  total return multiplied by the UKVI fund’s weighted average beta, plus an annual 3% size premium and 2.5% value premium over the long term.  That’s a bit of a mouthful, and given that the UKVI beta is currently very close to 1 and I’m virtually 100% in stocks, I could simplify it and say:

I expect to beat the FTSE 100 total return by about 5% annually over the long term. 

Given that the FTSE All Share has returned about 7% capital gains plus about 3% from dividends and the FTSE 100 is likely to be similar, I would expect a total annual return in the region of 15% with somewhat more volatility than the benchmark due to the additional risk I’ve taken on in order to get the extra returns.

Remember that even if I match this performance it does not show any proof of skill since the assumption is that by throwing darts at a board of small value companies (or hiring a chimpanzee to do it) I could achieve the same results.  Only by beating that target can I claim some semblance of an apparently ‘socially useless’ skill.

Finally, to aid in the general excitement I’ve added a discrete period performance table, showing monthly performances for me and the benchmark, as well as year to date figures to the about page.  Discrete yearly figures will appear when I’ve been around long enough to gather them.

As you will see, despite underperforming the benchmark by about 5% this past 6 months I’m still in the lead for the year by over 6%, but there’s plenty of time to fall behind yet.

I thought I’d say a little something about how I decide to buy and sell companies, and what my rationale is behind each trade. There is some discretion involved, but not much, and this is certainly a fair summary of what I do.

Let’s say I start with £1000 in cash.  I look for a company where I can pay £1000 for something worth at least £1,500. ‘Worth’ is a slippery term, but to me it means shareholder equity or book value, and I prefer tangible real assets to intangible assets. I realise that book value isn’t always the actual net value of the company assets, what with ‘cooking the books’ and all. However, I don’t have the time or interest in digging out all the details so I imagine that the good and bad net each other out. To be on the safe side I use a wide margin of safety.

So I head out into the market and find some companies where I can buy a pound fifty of book value for a pound. These companies are typically quite sick, often making losses, often unloved by almost everybody. Because they are often losing money they need to be able to weather their current problems. They need a bomb-proof balance sheet, or as near as can be. Typically this means they don’t have a lot of debt and have at least fair liquidity.Debt is often what gets a company killed. If the banks refuse to lend to a company which is dependent on debt it’s game over and the companies I buy are not top of many banks lend-to lists.  Debt can be measured in many ways, but I tend to use net gearing, which is gearing based on net debt, which is interest bearing debt minus cash and equivalents. What exactly is low debt is debatable and I don’t have a hard rule, but certainly less than 100% of tangible equity.

Once I have added a nice cheap strong company to my portfolio I only check on it’s market value once a week. Each week I take a quick look to see if the market value has reached the book value. The answer is usually no. It’s usually no for many months if not longer. Sometimes there will be a dividend, for which I am truly grateful, but these aren’t that common since many of my holdings are loss making. Something has to happen to move the market price, so I sit and wait for something to happen. Alba was a good example of this. They sold the Alba name to Argos and de-listed down to the AIM. They completely restructured the business getting rid of all sorts of non-core bits and that was enough to make Mr Market happy. The share price shot up and I got out.

And talking of getting out, if I can sell a company and turn its book value into cold hard cash then I will. Once the market price equals the book price I see no sense in hanging on. During my holding period the original £1,000 has turned into £1,500, perhaps with some small dividend paid out in the year or three I had to wait. Now I have £1,500 cash in my hands, so I go right back to the market looking for that pound fifty on sale for a pound, or in this case £2,250, at which point it all begins again.

As you can see, the focus is always very much on building up the total book value of my holdings.  Of course, it isn’t always a happy ending. Sometimes the managers manage to burn a big chunk of my book value up. Sometimes I wake up and the new annual report says my company is worth 30% less than it was yesterday and suddenly the market price is above book value. It might even be worth less than I paid for it. From here there are two courses of action. I can ignore the paper loss, turn a blind eye and say “I will only sell if I have a gain”. But this is not logically consistent. It smacks of making up the rules as you go along and one of the keys to investing I think is to make up the rules and then stick to them! So what I should do – and have done so far on the one occasion it’s happened – is to sell at a loss, try to work out where it all went wrong, swear at the management and start looking for the next unloved but robust company to back.

After reading a post on The Div-Net, I started to think about how I differ from dividend investors and why.  The first point to make is that I’m not a dividend investor, in fact I consider myself a trader rather than an investor.  An investor to me is someone who buys something with no explicit intention to sell it.  This typically means they are either buying it for the income (dividend investors, landlords, Warren Buffett etc) or perhaps they are buying it to let the capital appreciate for decades or to let the kids inherit.

So why would I trade rather than invest?  Well, there is some evidence that the returns are better if it’s done properly (which I’ll try to cover at some point), and more importantly it’s a better fit with my personality.

Since I’m buying with the intention to sell, how long do I expect to hold my stock?
It usually doesn’t take long for someone reading up on value investing to realise that it’s usually a long term game.  As Ben Graham said in The Intelligent Investor:

The fact that both the favorable and unfavorable situations are part of any normal long-term picture (and as a consequence both should be accepted without undue excitement) is evidently not part of the stock market’s philosophy.  The latter seems to be grounded on the feeling that, since nothing is really permanemt, it is logical enough to treat the temporary as if it were going to be parmanent – even though we know it is not.

So the stock market’s view is short-term, the next few quarters or perhaps a year.  Current earnings are bad, a new competitor has arrived, the CEO has quit, etc etc.  Mr Market is depressed about the company and wants to get shot of it now since it is unlikely to produce a good return, and may even go down further, in the next six to twelve months.  The intelligent investor steps in, happy to buy such a ‘poor’ investment.  How long will it be before things start looking up and Mr Market is knocking on our door offering a fair price for the company?

One study that does much to show how value shares outperform over a longer time horizon, but perhaps even more importantly, that they do not usually outperform over short time horizons and may even underperform in the months after your purchase, is Time and the Payoff to Value Investing.  This study of South African value stocks splits the market by current P/E (a poor but easy to use measure of value) and holds the various portfolios for periods from six to thirty months.

The graphs clearly show how there is no meaningful difference in performance between the high and low P/E stocks within a six month timeframe.  But by eighteen months the expected returns of low P/E stocks are clearly better.  Their Figure 2 shows how the lowest 10% of stocks by P/E, over a 30 month period, outperform the average of their sample on an annualised basis by about 20%.  That’s 20% annualised outperformance.  Of course the standard deviation is higher but I (like many Grahamites) don’t use that as a measure of risk; perhaps the subject of another post.

Looking at my own Trade History, my average holding period has been 199 days.  Somewhat shorter than a year, but that’s probably largely to do with the huge bounce in FTSE shares since March 2009.  On top of that I’m still holding several companies which I bought in late 2008, where the holding period is now approaching eighteen months.

So next time I buy into a company, only to see if fall, and fall, for months on end, and then for it to flounder somewhere slightly below where I bought it for a year or more, I can look back at this article to assure myself that the odds are on my side and to quit worrying.  That’s the theory at least.

Over the past 6 months I’ve worked on my approach to finding good investments and I think I’m quite happy for now. I started out just looking at price to book, which often gave me companies with lots of debt, i.e. Ennstone, which then fall over at the first sign of trouble. Then I looked at liquidation value and cash flow, to protect against such a failure. However, I’ve now simplified it so that I pretty much just look at liquidity (current and quick ratios) and debt to equity ratios. Once the companies are filtered by those criteria I just buy whatever is cheapest to book, with half book being the most I’ll pay.  The ratios I use aren’t set in stone, but they are ball parks to get me started and the amounts come from various texts as ‘reasonable’ amounts.

I think it can be difficult to learn anything without actually living it. So handily Ennstone, my first purchase of a value stock using not much more than price to book, has fallen over into the abyss. This is good for a number of reasons, although of course not so good for the staff.

The collapse of Ennstone has helped me re-think my approach to value investing and most importantly helped me to clarify to myself what it means to me to invest at all.

Risk to Returns and Principle. I’m beginning to think that’s what it’s all about. For example, let’s say I have some money to invest, ignoring fees etc I could invest it in:

1. My matress – risk to principle of fire or theft, but no risk to income as there isn’t any.

2. A bank savings account – risk to principle is none as the government guarantees deposits, risk to the about 2-3% income is small and varies with interest rates.

3. Government bonds – no risk to principle and no risk to the about 4% income.

4. Corporate bonds – now here’s the first big risk to principle. If I give my money to a company where the assets don’t cover the debts then if the company goes bust I’ll only get back a fraction of my principle. In a worst case scenario I could get back nothing if assets are mostly intangible. The risk to income is if the company goes bust.

5. Company shares – Of course this can carry the greatest risk to both income and principle. A company can easily cancel income to shareholders, the dividend. You can also easily lose all you’re principle if the company goes bust since any fire sale of assets goes to bond holders first. Shareholders only get what, if anything, is left.

That fear of loosing the principle is where the net net or liquidation value approach to investing comes. If there’s enough assets to probably pay everyone back in the event the company fails then the risk to principle is as controlled as it can be for a shareholder. Unless of course you invest in large ‘moat’ companies that are unlikely to fail in your lifetime.

So my first investment rule, which I had been kind of using from a while back and which would have barred Ennstone from entry to my portfolio, is:

A company must be trading for less than the value of 100% of its current assets plus 0% of its fixed assets minus all debts, or 80% of it’s current assets plus 50% of it’s fixed assets minus all debts.

Both of those are reasonable estimates of the liquidation value of a company. Depending on the ratio of fixed to current assets sometimes one is higher than the other. If a company passes either test then I’m interested. However, a slight caveat is that I’ll also consider companies slightly above this level if the company is generating enough cash.

Once I think my principle is reasonably safe, I’ll look at the cash generated and returned to shareholders over the last 5 years. If the company returned 15% cash returns at the current price to shareholders and had cash flows greater than that (i.e. they weren’t paying out to shareholders more cash than they were making) then I’m interested. The 15% is a number I read that Mr Buffet was happy with, so if it’s good enough for him then it’s good enough for me.

So I end up with a company that has enough assets to privide me with some reasonable downside protection to my principle, and has historically returned 15% to shareholders over the last few years, my assumption being that the next 5 years will look something like the last few years. Without my crystal ball I cannot assume anything else.

At 15% returns most investors would love to own such a stock. The idea is that when confidence returns for this company then investors will pile in. Once Mr Market offers me a price such that I can buy more assets and earnings power elsewhere (perhaps if he offers double my purchase price) then I will sell. If no such offer arises then I’ll sit and hold hopefully getting my 15%. If I don’t even get that then I’ll sell out after 5 years and go panning for gold again.