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Is Fund Management a ‘Monkey Business’?

Is fund management a ‘monkey business’?
Published on Apr 22, 2016

Is Fund Management a ‘Monkey Business’?

1973 might have been a year of mixed emotions for humankind. However, it surely was a great time for dart-throwing monkeys. Princeton professor Burton Malkiel had just started to propagate dart-throwing monkeys as professional ‘fund managers’ by publishing his bestseller A Random Walk Down Wall Street.

This influential book on stock markets did not only popularize the ‘random walk’ hypothesis and became a frequently cited source for supporters of the efficient market theorem, but it consequently also raised a critical question: Are blindfolded dart-throwing monkeys better fund managers than highly paid human experts? Though this question may sound silly, academics and practitioners quickly strived to find the rationale behind the theory by conducting experiments. They apparently revealed that monkeys don’t perform that bad at all, when it comes to managing funds.

The monkey business attracted so much attention that the famous Wall Street Journal carried out its own experiment in 1988, which revealed that professional fund managers won against their blindfolded simian opponents in 61% of the 100 rounds – not too impressive considering that the experts were allowed to publish their tips at the beginning of the contest, which might have biased markets in their favor. Other famous examples of monkeys making profit include Lusha, the Russian circus chimp, whose investment portfolio is said to have outperformed 94% of Russian fund managers, while Raven, the chimp star of Babe, Pig in the City, created a portfolio rising up +95% in six trading days by choosing 10 stocks out of 133 internet-related companies in 1999.

SG Analytics 60 simulated monkey

Let’s go get our on monkey advisors, right?

Well, I personally wouldn’t do that. Let’s take a look at another examples: While it remains unclear how Lusha’s portfolio performed in the long-term, we know what happened to Raven’s investments. Her ‘fund’ suffered bigger losses than any of the ones built by human experts during the dotcom burst in 2000, almost annihilating its complete value.

However, some people might argue that Raven just ran out of luck or that someone else had chosen the pool of 133 internet companies for her, thus, inevitably making her prone to failure.

Some people might even point at seemingly countless other instances, where monkeys actually managed to beat professional fund managers, for example, a study published by Research Affiliates in 2012. Leaving personal opinions and prominent examples aside, we will need a more sound approach to go further.

How does the ‘monkey-throws-darts’ game work?

There are usually only two steps involved: The first one is that someone creates a pool of stocks containing companies of all different sizes and risk profiles, while a monkey chooses a fixed number of stocks out of this pool for its portfolio and weights them all equally. It doesn’t sound much of an advantage for the monkeys, but it actually is. Here is why: Any given stock market will have a discrepancy between big and small stocks regarding market cap. The majority of companies are smaller than the average e.g. 20% of the DAX 30 stocks containing almost 45% of its market cap. For this reason, any randomly constructed portfolio is bound to include mostly smaller companies.

The important point to notice is that small-cap companies are riskier than their big competitors:

  • They may not be well-known, so their brand is not as valuable
  • They may only have a few products, thus, being more exposed to concentration risk
  • They may not be well capitalized and may not have large distribution networks for their products

Knowing this, you would expect them to pay high returns to compensate for the additional risk. Well, the so-called small-cap premium is widely recognized in academia today.

Summing this up, most of the monkey portfolios get boosted by utilizing the small-cap premium, therefore, naturally outperforming all cap-weighted portfolios. Most fund managers replicate these indexes only adjusting them in nuances and hence get beaten by their monkey counterparts. However, monkeys lose more money, when the market turns bearish (although in my DAX 30 example they still won because they simply didn’t buy Volkswagen shares that often).
In the end, it remains a matter of faith. If you believe that the efficient market theorem holds true, you can ask monkeys for investment advice, because their random choices would be as good as any other selection. However, if you think that market movements are not completely random and that an experienced fund manager can predict future prices, even if to the least possible extend, you should consult human experts on this matter.


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