Those who fear a loss

But those who speak know nothing
And find out to their cost
Like those who curse their luck in too many places
And those who fear a loss – Sting, Shape of my Heart


Most people can accept that quantum physics is uncertain.  But I’ve been trying to explain finance to someone who is an electronics engineer.  He doesn’t understand how accounting numbers can be uncertain.  I suppose that’s why he’s an electronic’s engineer…

One of the weirdest ideas in finance is that the more certain you are of making money, the less of your own money you should use to back your judgement. It took me several years to get my head around this idea – and it’s certainly not taught like this. But if you are certain an opportunity will give you a decent positive return, you should use as little of your own money, and as much of other people’s.
An example from real life might help. Say that you found a house in an up-and-coming area 30 years ago. You were certain the price would rise, and you turned out to be right. If you’d bought the house with your own money and it trebled then the gain would 3x your money.

Smashed avocados on you!

Not so fast. Because if you’d managed to get a 90% Loan To Value Mortgage (ie you put down a 10% deposit, and borrowed the rest from the bank) …your return increases to something like 13x after you’ve paid back both the principal of the loan and the interest. *

Craft beers are on you!


Start End Increase
House Price 100 300 3x
Mortgage Principal 90  90
Mortgage Interest 80
Deposit / Equity 10 130 13x
House Price 100 300 3x

So if you are sure of a gain, you can borrow money to amplify your returns.

Those who curse their luck in too many places

The reverse is also true. You can also amplify your loses with borrowed money. This was what Long Term Capital Management ended up doing – they were overconfident, borrowing money to amplify their small arbitrage returns in Government bonds… until it turned out Government bonds were more risky than they realised. As an aside, I’m not really sure why banks were lending LTCM tens of billions of dollars to trade government bonds…other than the fact that banks knew that if it all went wrong they would be bailed out.

The second weirdest idea I like is that you can make an expected return even when you don’t know the specific outcome. I’ve just finished reading a book about Jerome Cardano, a 16th century gambler / mathematician / cryptographer / medical doctor / astrologer / renaissance man who “invented” probability, as well as discovering the “i” – the square root of minus one.

In Liber de Ludo Aleae – Book on Games of Chance Cardano defined probability as a fraction: number of favourable outcomes / total outcomes. IE there is a 4/52 chance of drawing any ace from a full set of cards. You don’t need to precisely predict when this happens, you just need to know when the odds are in your favour. The hidden law of a probable outcome. When the odds of a favourable outcome are in your favour, you should use as little of your own money, and as much of other people’s money. Easier said than done, despite inventing the maths, Jerome gambled away his wife’s jewels and even his marriage bed.

Value traps

Notwithstanding LTCM and Jerome’s occasional losses, the best opportunities should be financed with other people’s money. For companies, rather than people, the best opportunities would be the businesses with the most attractive margins or strongest competitive position. Maybe Google or Facebook for example. But oddly it doesn’t work out that way. Those high quality companies make so much money, they don’t want to borrow money – they make such high returns already they can’t use debt to amplify their returns. Instead, it’s often the companies with the lowest margins and deteriorating competitive position have the weakest balance sheets. Because of this, these companies tend to trade a discount (low price / earnings or high dividend yield). Carillion, now bust, is a good example. They are widely known as “value traps” – they look cheap, but actually these companies are cheap for good reasons.
Often but not always. Many people avoid these value traps, preferring growth. Or they say that there is no “margin of safety” – a core value investing tenet.

Bargains at the wrong price

The bargain valuation is almost always wrong – either Carillion equity is worthless, at which point the cheap valuation is still too high. Or the company can survive, and returns are likely to be hugely amplified. In the latter category I would put CVS (a business buying up vetinary practices). I looked at CVS a few years ago, another business where I met management in the pub / Seymour Pierce back office.

The chap who started the business was in the pub because he was fired from stockbroking by one of my friends.  They had stayed in touch – firing your friends happens all the time in stockbroking.  He’d gone on to be very successful and started CVS when he realised how much he was spending taking his dog to the vet. Then he had sold the business.  He mentioned that the leverage in the business came from the leasehold nature of the vetinary practices’ buildings, and he was a bit put off that since he’d left the new management had weakened the balance sheet further by borrowing money as well as operating the leasehold properties. It was over a bottle of wine, but I think my memory is correct and that’s why I decided not to invest. Despite the weak balance sheet the company went on to recover from poor trading to be a multi-baggers, increasing in value 15x.

An interesting question is not:

– what can you know in advance?


– what do you need to know in advance?

Obviously with those kind of extreme outcomes, it would be great to know what information you need to tell in advance what will happen. I’m not sure that the financial numbers help you. You already know that the company is in a precarious position, the equity could be wiped out. There’s an idea that more information should help you, there seem to be lots of people making claims that “data science” – is there any other kind of science? – is going to revolutionise fund management.  I’m less sure.  
Maybe you can do analysis on value traps…it’s not possible to predict what the outcome will be for a specific company, but it would be useful to know how many value traps fail. And how many go on to recover and increase in value more than 10x. Like knowing the number of aces in a pack. And then when the odds are in your favour, use other people’s money to back your judgement.
No one is trying to do this…except me, and I’m only dabbling. I lost a small amount in Carillion – but I managed my risk of loss with a stop loss. Despite losing, I still think that maybe the asymmetry was in my favour, even if it turned out to be loss making in this specific case. You can’t win every hand at poker. If the asymmetry is either 10% downside (my stop loss) or multi-bagging return – then that presents an opportunity. Maybe there’s a reason why no one else is trying this – I just think that most people find it hard to deal with not knowing. There’s a comment in the back of the book on Cardano about the human mind’s yearning for advice, however unreliable the source. The author refers to another book on Cardano where he suggests the modern equivalent of going to astronomers to seek certainty and predictions is now going to the economics “profession”.

Uncertain Circularities

Rather than listening to financial advisers and astrologers, I like to think about the weird kind of circularity of expected return. The assets with the greatest certainty of an expected return are deeply out of favour. And they are deeply out of favour because of the uncertainty attached to their expected return.
As for Cardano – he lived to almost 75 years old. Many years before he correctly predicted the precise date of his own death on 21 September 1576. How’s that for a certain prediction? Except some of his enemies claimed he was in perfect health: and he either starved or poisoned himself so that that his prediction of his own death would come true on the day he had predicted when he cast his horoscope. A certain kind of circular prediction.

Photo by Inês Ferreira on Unsplash

* A 5% interest rate over 30 years works out that you pay back roughly twice the amount you borrowed, because of interest payments. That’s why banks hate it when you pay off your mortgage early – they make more money when you are in debt for longer amounts of time.