Problems with smart beta

Before ESG investing came along, “smart beta” was the next big thing.

Smart beta strategies involve an investor tracking an index, much like traditional index investing. Where smart beta differs from index investing is in the composition of the index being tracked.

Smart beta strategies track indices which have been weighted in some other way than market capitalisation, which is the traditional “passive” way of weighting indices. These smart beta indices usually increase weightings to factor premia, such as value stocks, small cap, momentum, low volatility, etc, in the hopes of outperforming their passive brethren.

Smart beta has been growing rapidly in recent years, with smart beta products boasting a 5 year annualised growth in AUM of 33%, according to ETFGI. This has been caused by two major trends in the industry:

1) A relentless focus on fees – smart beta is usually cheaper than traditional active management, and

2) The realisation that much of what used to be called active management’s “alpha” has now been found to be factor exposure.

Investors have realised that many funds’ historic outperformances are less to do with their managers’ skilful stock picking, and are often due to nothing more than overweights to well-known factors.  

To get one point clear at the outset, while smart beta and factor investing are related, smart beta is not the same as factor investing.

Factor investing involves investing in traditional long-short academic factors (as defined by Fama-French etc). Smart beta involves investing in a different kind of factor exposure – one which is usually long-only, usually only in large caps, and usually with much lower tracking error. The factors are defined by the index provider.

For some background on the academic factors which smart beta products are based on, please refer to this post.

Some of the problems I’ll go through in these posts will be related to factor investing, some will be related to smart beta, some will apply to both. As there’s quite a bit of information to go through, I’ve split the posts up into more manageable chunks:

1. The cyclicality of factors
2. Defining a factor is hard
3. Factors can change
4. Factors can decay over time
5. It’s impossible to know when a factor stops working
6. Factor dilution
7. Academia isn’t real life
8. Backtesting

Without further ado, let’s dive into the first problem with smart beta.