The Doldrums

In the great series of historical novels about the British Navy in the Napoleonic era by Patrick O’Brian, and the associated movie Master and Commander, there is a poignant scene where the ship is stuck in the Pacific doldrums, sails limp at the mast for days. The crew looks for a scapegoat, a Jonas, to blame for their misery, and they find one in a hapless midshipman. For the good of the ship he grabs a cannonball and jumps over the side. A prayer is said, the wind returns, and off they go. Complacency is the buzzword of the day, but the winds will return as they always do, and the catalyst will be as much a surprise to the market as to the midshipman who found himself carrying a cannonball.

I am habitually early for meetings. The other day I had some time to sit outside the offices of a major investment bank at the start of the business day. It’s an evergreen notion for me … a scene repeated at all the banks and funds all around the world, hundreds of well educated, motivated, energetic young people all chasing the same pool of alpha. And I wonder, is there enough to feed all these hungry strivers? Risk premium is durable, varied and growing, alpha is zero sum and rare. At Mount Lucas, our approach is to own that risk premium in many flavors through our quantitative trading. Just this month we added a new flavor, a momentum based multi asset credit basket. It fits nicely with the other risks in our capital markets allocation. We continue to search for alpha in the realm of long term behavioral biases. I have to admit it’s tough going, particularly in the doldrums, but the opportunities are there, and we await a stiff breeze to see them realized.

 

Mount Lucas employs a number of different strategies each with their own investment objectives and risk profiles.  Any reference to a strategy or strategies mentioned above may or may not be indicative of all of Mount Lucas’ products.”

With Friends Like These…

There is a saying in our business,”the trend is your friend.” Given the recent downturn in trend following returns, I am reminded of another saying, “with friends like these, who needs enemies.” I was in a meeting recently with a consultant who asked a question we have heard many times over the years. How do you keep clients invested in managed futures in times like these? We know the history, the diversification benefits, the crisis protection, the long volatility profile…but, each time there is an extended period of challenging performance clients look to throw in the towel – because their equity investments are ripping up and managed futures is down. A good question, and the answer, I think, lies in the statement – it is a matter of faith.

Investors in the equity market have faith. They trust, and have been conditioned, that the market goes up over time, corrections are temporary. Participating in the capital formation of companies provides a risk premium to the investor and is an investment in the economic growth of a country.

Managed futures on the other hand is viewed as a trading strategy, it goes long and short, it is typically quantitative based. The perception is…I can’t have faith in a model, it can break. But this perception is misplaced, trend following measures a real economic risk premium in the market, just like equities (see older posts diving deeper on this topic, Portfolio Symmetry, Commodities are not Stocks, Benchmarking Alternative Beta). Investors in this market are rewarded by taking the price risk companies seek to shed. Faith should be in the durability of this premium, just like there is in the equity risk premium. Faith is gained by understanding this risk premium, when it works (periods of volatility and instability), and when it doesn’t (periods of low volatility and stability). Similar to equities, faith should be garnered from the underlying economics of the markets.

Algorithm Aversion: On Models and The Donald

Whatever your politics, one can’t help but be fascinated by the Trump phenomenon. One interesting aspect is how pollsters got Trump wrong. We can get insight into that mistake from Nate Silver at fivethirtyeight. To his immense credit, Silver admits he got Trump all wrong, and went back to have a look at the why and the how…. it boils down to a case of algorithmic aversion (see here and here).

Silver’s approach to forecasting, which has been extremely successful across a wide range of subjects, is based on aggregating data from multiple polls to build as big a sample as possible. It is a mechanical, quantitative, model based, statistical method. The model spits out an answer, and that is forecast. But in the Trump case, he over-rode the model. He had a bias, and in this instance he applied it to his forecast, and voila, a bad outcome. Even Silver, a devoted algorithmist if there ever was one, fell into the trap. He did not trust the model, even though it had been right so many times before.

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