I just read a great book – The Simplicity Cycle by Dan Ward. It articulates wonderfully a philosophy that underpins everything we do here at Mount Lucas, something that we feel is incredibly important for investors to understand, and that investors in general are moving away from. The book isn’t finance based at all, a quick and easy read. The basic premise is summed up with the quote below:
“…humans gravitate towards complexity, in our technologies and religions, our laws and relationships, because simplicity is so often inadequate to our needs. We require a certain degree of complexity in our lives, just as we require a certain number of calories each day. Accordingly, we add layers, gizmos, features, functions, connections and rules to the things we create in an attempt to make them more exciting, more effective, or otherwise better. This preference, too, becomes a problem when it spirals out of control and produces industrial-strength concentrations of complexity that surpass our needs by multiple orders of magnitude….Simplicity is great and important, to be sure, but let me say it again: simplicity is not the point. What is the point? In a word, goodness…Simplicity matters because it affects goodness, but it turns out the relationship between simplicity and goodness does not follow a straight line. This means an increase in one does not always correspond with an increase in the other. Sometimes making things simpler is indeed an improvement. Sometimes not. Life is tricky that way”
Over the past 10-15 years or so, maybe even longer if you want to draw parallels with the 87 crash or LTCM, the complexity level in markets has gone up – a lot. By and large it’s a good thing, computing power and access to information allows better, quicker decisions to be made, which helps the economy function in a higher gear. This has not escaped investing, with quant funds devouring more and more data, trading at faster and faster speed, and relying on ever more complex models. It’s in this area where we think people need to step back and pause. We think many of these products are sold rather than bought – a better mousetrap, a faster algo, more PhDs, the more models – the better.
“It is very hard to be simple enough to be good.”
-Ralph Waldo Emerson
When I was at Commodities Corp in the 80’s and 90’s, lots of people would come in search of capital. Frank and I called them “tomato suits”. The name came from an old schlocky TV show of the era, Let’s Make a Deal. The host, Monty Hall, would pick people out the studio audience to play the game, and audience members would dress up in ridiculous costumes to try and get Monty’s attention – in, for example, a tomato suit. Much of what goes on in the investing world reminds us of this – dressing up the presentation with PhD’s and equations to try to gain capital.
Investors need to understand what risks are being taken and why – an army of quants running risk models to 3 decimal places leads to statistical ex ante diversification, and encourages leverage. It’s both a micro and macro problem – high correlation in spread positions leads to very low VaR readings, very high leverage and a false sense of security at the individual trade level (cc Amaranth). As models and funds get more and more complex they can get less and less robust, and further away from common sense and ‘goodness’.
“An expert is someone who knows some of the worst mistakes that can be made in his subject, and how to avoid them.”
We have been around a long time and have a deep understanding of what we do and why. We focus on the core principal that investors are paid to take economic risk, and we develop models and strategies that can participate in that process. We understand the return distributions, know what economic forces drive them and how different strategies will work together in different environments. We don’t over engineer, over fit, over optimize, over complicate. The temptation is always there to move into more markets, more exchanges and products, more complex algorithms, and faster timing. When you start to look at the world through the simplicity and goodness lens, and step back from the minutiae of computing and comparing ratios, the decision framework alters. It is less about increasing a Sharpe ratio by a couple of decimal points, and more about whether the additional operational complexity is worth it, whether the liquidity constraints are worth it, and frankly whether the sleepless nights are worth it. The benefits of complexity seem only to amplify in bull markets and calm waters – but you have to think about the decisions in the context of unstable equilibria, where simple and good rule the day.
“Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it’s worth it in the end because once you get there, you can move mountains.”
Experience helps a lot here – and we feel being proponents and practitioners of both systematic and discretionary trading gives us an edge. I started out in 1979 designing quant systems. After 35 years of experience across asset classes, you get comfortable with the return distributions, and you experience in real time how markets can work well, and then can become unhinged – through the 87 crash, the savings and loan crisis, the dotcom bust and then through the biggest test of generations in 2008/09. It is very different seeing these events as long ago blips on a chart when you know the outcomes and the bounce back than it is living and trading through them – it’s the difference between sympathy and empathy. What it has led to for us is an aversion to over confidence, over parameterizing and over leverage. We do all the same research, read the same papers and have come to different conclusions. It is far better to be approximately right with things you can hold and understand, than it is to continue adding more and more complexity without accounting for the unknown blow up risks. When you get to the point where adding complexity starts to detract from goodness, you need to be careful.