28th May 2012
So enter the increasingly fashionable world of Smart Beta where investors have to decide whether attempts to beat passive funds but without the costs of active management work or whether they are another example of the Texas sharpshooter fallacy. This is an easy to understand example of using back-testing results to prove an hypothesis moving forward.
In the fallacy, the shooter blasts away at a barn wall, notes where the majority of the shots land and draws a target around that point, proving, with hindsight, how successful the gunnery has been.
January becomes December
The existence of this fallacy has been known for decades. But it does not stop investment firms trying to discover new tricks to supercharge portfolios. In the past, there have been attempts such as the January effect or theories buying the ten shares in an index which have the highest dividend payments or the lowest price/earnings ratio or any one of a score or more such constructs.
The problem with all is that they work with back-testing while they nearly always fail going forward. Savvy investors moved in ahead of January and bought in December while the trick of selecting shares on numbers from the past rather than fundamentals for the future meant it was easy to replicate – and once everyone did it, it ceased to have value.
Investing in the stock market exposes investor to two risks. One is the overall risk of the market driven by features such as interest rates, the economy, political events at home and abroad and a variety of other factors. The second is the risk of the individual company selected for investment – the chief executive might have been cooking the books.
The beta of a stock is its volatility relative to the index in which it is quoted. So a share which has a beta of 1.0 will replicate the index; one that is 1.5 is more volatile while a stock at 0.5 is less so.
Capturing beta with a tracker
Reproducing beta is easy with a tracker fund or passive ETF. The trick with smart beta is to squeeze more out of the tube without either pushing up the beta to a higher level or exposing investors to more volatility or increasing costs. How they claim to do it is not so easy to describe as there are a number of strategies. But the essential is that they add value to the index tracker fund at less cost that going for alpha, the idea of beating the market through stock picking.
Some suggest it is bargain basement alpha with the added advantage of investors keeping within known risk parameters by applying a systemic tilt. Others say that it effectively replaces one benchmark (such as the index) with another (the index plus or minus a facet or two ) so arguably, you have a new indicator and a new beta – effectively a bespoke index so the fund can always claim a beta of 1.0. Tilts can involve value or dividend or price/earnings or price to book or any other quantitative measure.
Proponents of smart beta believe it offers investors a choice midway between beta and an alpha which is increasingly difficult to achieve without undue risk in developed markets where so much is known of individual stocks. They suggest that there is now little to choose between alpha and smart beta – and that if you really want to beat beta, you have to go way out into the realms of stock picking without any reference to volatility.
The selling point for institutional investors especially is that costs are around a quarter of an actively managed funds, saving perhaps 35 basis points (0.35%) a year. All those basis points add up over time, making it even harder for the active manager to compete.
Emperor's new clothes for the naked investor
But it could all be emperor's new clothes, according to Jeffrey Molitor of passive investment specialists Vanguard Asset Management.
He says: "Referring to these strategies as "smart" suggests they represent superior segments of the broad market. But in reality, markets are too efficient to ever really offer magic rules-based bullets. There are simply too many smart people looking to identify and exploit perceived inefficiencies. The rules often define portfolios that represent attractive answers to what would have worked extremely well over recent history. You can compare it to preparing for the last war."
He divides smart beta strategies into four:
Strategies generally fall into one of four categories: rules-based active strategies, factor beta, strategy beta and data-mining wonders.