Quibbles With Quants

Models are not Reality

When we model the world we simplify it, because we have to: to model the real-world accurately we’d need to have all the atoms in the universe and a few more. So, the globe of the world revolving gently on my desk afore me, is a highly simplified representation of the planet most of us live on, leaving out what many of us would consider to be most of the important details – stuff like people, beer, football, lively teenage daughters and the latest episode of House. You fill in your own details.

Quants, the purveyors of quantitative investment analysis, also model the world, although in a much more complex, mathematical way. Yet despite the sophistication and elegance of the mathematics they too make simplifications because they have to, and these matter to us all because they’ve brought the world to the point of financial meltdown thrice within a few years.

Models are Metaphors

What quants bring to investment analysis is a set of metaphors about the way the world actually works, rather than any kind of accurate description of what’s really happening. In fact the world is run by such approximations – models of average life expectancy, mean time to failure of aerospace components, the probability of Michael Jackson’s chimp contesting his will – and, in general, these inaccuracies haven’t mattered much to humanity en-masse. However, we’re now in a world dominated by mass computing power and intricately interconnected such that small perturbations in one area can have dramatic ramifications elsewhere.

From the 1980’s, when Portfolio Insurance turned out to be no such thing, to the 1990’s, when Long Term Capital Management became a glorious oxymoron, through to the 2000’s, when the securitised mortgage market turned into a series of financial time bombs in a greater game of pass the ticking parcel, the quantitative models that mathematically illiterate managements have relied on have given no warning of what was about to occur. Yet these models were created by some of the cleverest minds in the world and supported by some of the most serious back-testing that has ever been carried out.

Yet still they failed.

People Are Uncorrelated, Until They Aren’t

What the models failed to capture was that humans don’t behave in simple, predictable and uncorrelated ways. It’s impossible to overstate the importance of the way these models cope with correlation of peoples’ psychology. To sum it up: they don’t. Let me know if that’s too complex an analysis for the mathematical masters of the universe.

Anyone who’s ever been to a nightclub, a football game or even a very loud party will know that there are situations where we don’t act as individuals, buzzing about doing our own thing. These are occasions when we all suddenly stop being individuals and start doing the same thing – usually involving large quantities of drugs and some very bad singing. Although these sorts of events are specifically designed to trigger this behaviour – which is probably a deep evolutionary adaptation to sponsor group behaviour, useful when it comes to running down tasty antelope and dealing with giant, carnivorous sabre toothed beavers – it can also happen in other situations. Most stockmarket booms and busts are generated by similar group effects.

In general, people behave in an uncorrelated fashion right up until the point they don’t. Then we all suddenly do the same thing together. We stop taking flights in the wake of 9/11, we stop letting our children play in the streets because of a single, heavily reported abduction in another country and we start selling our shares because everyone else is. Fear is an awfully big motivator.

If Something Can’t Continue, It Won’t

Quantitative models don’t handle this sudden polarisation of human behaviour very well. Every so often something surprising happens that causes us all to scurry into the nearest hole and the models promptly fall over, usually accompanied by some whizz-kid earnestly explaining that this was a one in a million year event and that it was just bad luck it happened after three years and can he please have his bonus anyway?

Think about the booms and busts in stockmarkets compared to the relatively stable periods in between. In the stable times it’s possible to roughly model the way that people are going to invest, on average, making certain assumptions about the companies comprising the markets and general economic conditions. While these assumptions hold so do the models and this can go on for a long time, long enough to convince people that stability is the norm.

Only stability is not the norm. When the markets enter one of their periodic manic-depressive phases these general models break down – people start to cluster together in fear or greed and do the same thing. Quantitative models work on the basis that the stable times will last forever, but the reality is that they don’t and when they end they do so in highly unexpected and unpredictable ways. Worse still, if any model becomes too popular it will start to influence the real world, to swing the pendulum one way. The trouble with pendulums is that eventually they swing back.

Credit Rating Madness

We can trace the collapse of the banks over the past couple of years to the excessive risks they were taking in holding Collateralised Debt Obligations on mortgage securities, the idea being that if you took a lot of very safe mortgage debt and bundled it up with a bit of really unsafe mortgage debt you’d end up with a safe investment. Whereas, in fact, you ended up with a lot of really unsafe lending to people who were never going to be able to repay their mortgages.

Yet at the time the models investment analysts were relying on simply didn’t identify these risks. Indeed the models of the credit rating agencies were explicitly changed to take into account the quantitative models showing that such securities weren’t risky.

The sheer nuttiness of the credit rating agencies changing their risk models purely because a quantitative model existed that indicated that the risk of these securities collapsing like dominoes in the event of isolated defaults was remote is still hard to believe. It’s not that the models didn’t indicate exactly that. Nor is it that the mathematics behind the models was particularly stupid. Nor was it that the analysts who dreamt up the models were doing anything obviously wrong.

No, it’s none of those things. It’s the fact that a bunch of smart people can possibly believe that any computer model can accurately reflect the real risks in a world dominated by stubborn, irrational, fearful humankind. You’ve got to ask – did none of the overpaid executives running the world’s financial corporations and regulators actually stop to wonder whether someone might have, just possibly, failed to predict everything that might happen in the real world? Did none of them look at the collapse of LTCM and wonder?

We Need Bridge Builders, Not Quants

Well, oddly enough, some of them did. Back in 2006 when the CEO of Citigroup was still dancing in the last chance sub-prime disco the risk management team at Goldman Sachs got together and solemnly inspected their VaR models which told them that risk levels were still low. Then they inspected their brains – and bailed out. Whether that was luck or judgement is still to be decided.

The great Victorian engineers built bridges that endure to this day because they couldn’t exactly model the risks. They built with a margin of safety not with a bonus on margins in mind. Remember this because the quants are not dead, they’re out there yet. They will rise again.


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Why The Growth of India and China Means Our Kids Should Do Media Studies

Software Isn’t Hi-Tech Any More

Last year I visited China in my role as an IT guy and, as usual, got into a discussion about the additional software services we might sell in addition to our products. The manager I was trying to talk to just smiled and beckoned me to follow him. We wandered down a few corridors and passed through a door that opened up into an aircraft hanger of a room filled, end to end, with serried cubicles staffed by young Chinese writing software.

The point, of course, was that there were no software services I could offer that the Chinese couldn’t support themselves, cheaper. The West has yet to fully appreciate the impact of the transition of China and India to fully industrialised nations. Our children need to start looking for new sorts of jobs, now, or spend the rest of their lives stacking shelves in supermarkets.

Transitioning from Agricultural Societies

Estimates suggest that around 1.2 billion of China and India’s 2.3 billion combined population still works outside the industrial sector. First world economies use approximately 3% of their available labour to till the land so that would imply over a billion people spilling into the globalised industrial economy at some point in the next few decades.

These countries are throwing out engineers, scientists and IT people at a rate far beyond what we in the West can achieve. Meanwhile our media obsessed younger generation shows a marked disinclination to engage in these areas which, as it turns out, may be a pretty intelligent decision. In competition with people at least as well educated as themselves but paid ten times less the opportunities for such skills are likely to be significantly reduced over the next twenty years.

So what’s left for the rest of the world if China, India and other South East Asian economies are going to become the global IT engine room? Where does this leave us as investors?

Global Resources

A second consideration is about the resources needed to fuel this growth. The development of the global media exposes the have-nots of the world to that which the haves, have. A Chinese friend of mine recalls walking out of LA airport in the late eighties and standing, stunned, at the sight of more cars than he’d ever seen in his entire life before: a lifetime of indoctrination was broken in a moment.

Yet the realities of global economic growth dictate that the world can’t support its poor becoming wealthier. For all Indians and Chinese to attain first world wealth we would have to strip the planet of its minerals and energy sources in an unsustainable frenzy of global proportions. In the words of Worldwatch:

…if by 2030 China and India alone were to achieve a per-capita footprint equivalent to that of Japan today, together they would require a full planet Earth to meet their needs.

http://www.worldwatch.org/node/3894

This isn’t going to happen. Yet the invisible hand must work and the redistribution of global wealth will happen. If India and its cohort can’t attain first world wealth then the latter must drop to meet the competition coming up. In short – we in the West, or at least our children, are going to be poorer on average.

Investing for the Future

Leaving aside the issues of planetary destruction and the inevitable decline of western society for a moment, we need to consider what difference this makes for us as rational investors. The obvious answer, investing directly in these economies, isn’t as easy as we’d like.

As we’ve seen before although investors are, as a whole, pretty good at figuring out which areas or stocks will outperform they are, as a whole, uniformly bad in avoiding underpaying for them. Value stocks appear to outperform growth stocks because investors overpay for growth rather than underpaying for value (see Clairvoyant Value). Investing in high growth, but expensive, Eastern stocks is likely to be a losing play, long term.

The Commodity Play?

The growing economies – especially China – are relatively short of commodities to fuel their growth. The search for sources of these will no doubt continue but the potential or actual impact of this saw oil and other commodities spike alarmingly in 2008.

Commodities generally obey the marginal laws of pricing deduced by David Ricardo. Simplistically, if supply of a commodity exceeds demand then the price of the commodity will tend to the cost of production: if it goes lower than this companies will eventually stop production entirely. However, if demand exceeds supply even marginally suddenly the producers are in a position to charge excessive prices.

The OPEC Effect

We saw this happen in the 1970’s when the creation of OPEC suddenly restricted oil supplies causing the price to spike because demand exceeded supply. The consequence, over many years, was that industrialised nations moved to reduce their consumption of the black stuff until OPEC was no longer able to force its members to cut supplies any further and the price collapsed back to its cost of marginal production.

Something similar happened last year when emerging economy growth drove demand up without a significant increase in supply – although whether this was a genuine increase in demand or purely a speculative reaction by hedge funds (as suggested in Hedge Funds Ate My Shorts) and other investors is still not clear. Whatever, the effect was a sudden and dramatic spike in oil and other commodity prices.

If China and India do continue to industrialise at the current rate then commodities are a way of investing in that growth. However, it’s a risky play: price rises will drive the world to look for ways of reducing consumption of oil and minerals. We’ve been given a warning, which is unlikely to be forgotten quickly. Still, these types of effects take years to play out so there’s a trade off between the speed with which industrialisation takes place and the rapidity of the reaction to price rises.

Buying the West

The psychological trap that investors typically fall into is chasing the next growth story. Checking where the investment industry is feverishly offering new funds is as good a sign as any. Guess what they were marketing a couple of years ago? Looking at closed end funds in emerging markets trading at big NAV discounts may not be a bad idea, if you trust the fund managers not to merge the funds out of existence.

However, the best way of investing in these countries may be simply to invest in undervalued Western companies that are using their cheap labour and finding ways of selling into the East. Given a choice between expensive Eastern stocks and cheap Western ones the latter will provide investors with better returns even if the former grow much more rapidly than the latter.

Unfortunately, as far as I can tell, there are no passive funds that allow such an investment. For long-term active investors with a value mindset focusing on such companies should offer very decent returns: almost certainly far better than buying companies on high multiples focusing on the trendy areas of climate change and alternative energy.

Services and Skills

On the local level we’re back to services. Some of this is relatively high-end stuff as well – power generators, infrastructure management (water, airports, etc), doctors and lawyers for instance. Lots of it, though, is simply box shifting. As far as I know you can’t easily get someone in India or China to stack UK shelves.

For our kids there’s no easy escape from the equalisation of the global economy. They need to develop language and design skills, focus on doing things that can’t be transferred abroad and, above all, rely on their parents for handouts while they get established. For us it’s an investing opportunity but for them it’s going to be a crisis.


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Adventure Gaming

For adventure gamers like myself – that strange subset of humanity who like playing computer games involving solving fiendish puzzles with nothing more than a magnifying glass, a notebook, some chewing gum, a piece of tape and seventy-seven apparently useless and inconveniently placed household objects – the Sam & Max series by Telltale Games is the pinnacle of perfection. Now, sure, the basic concept of a pair of freelance detectives played as a six foot dog and his little buddy, a small (but extremely violent) rabbity-type creature, is conceptually a bit difficult for people whose preferred persona is Sherlock Holmes or Hercule Poirot. But the plot is funnier than a stoat in the snow.

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