It is common today to hear the phrase ‘smart beta’ discussed alongside ETFs at industry conferences or in the financial press.
This is not surprising given there are approximately 200 smart beta ETFs listed in Europe. The total assets under management in these European ETFs exceed US$31bn (£19.9bn) as at 15 July this year, having increased by US$8.6bn (£5.5bn), or 38 per cent, since the start of last year. Most of these assets – in fact 93 per cent of AUM – are equity-based ETFs.
Most ETFs track market capitalisation-weighted indices which weigh individual components by their market capitalisation. This must be based on the belief that weighting stocks by market cap gives the highest return for a given level of risk.
However, this belief is now being challenged. An analysis of performance demonstrates that market capitalisation weighting may not always be the best method of indexing. In fact, according to Cass Consulting, a research-led consultancy service provided by Cass Business School, returns of traditional, market capitalisation-weighted incices are lagging behind alternative – or smart beta – indices by as much as 2 per cent a year from 1969 to 2011.
So from my perspective, the difference between ‘beta’ and ‘smart beta’ may be the idea that smart beta seeks to provide an exposure with the potential to outperform the market, isolate or accentuate a certain characteristic of the market, or generate better risk-adjusted returns than the market, rather than merely measure the performance of all investable stocks in an equity market.
How are ETFs using smart beta to get better returns? Over 200 ETFs exist today in Europe which track smart beta indices. These smart beta indices generally fall into the following categories:
Fundamentally weighted indices:
Components are selected to provide broad exposure to an equity market, but companies are weighted by fundamental factors such as aggregate dividends or earnings, price-to-book ratio or free cashflow.
Equal weight indices:
Components are often selected from established incices such as the S&P 500, but are equally weighted so that all components have identical weights when rebalanced.
Factor-based indices:
Components are selected based on one or more fundamental factors that define risk, return and correlation, and span more than one asset class.
Low volatility indices:
Components are selected because they have exhibited lower volatility than the overall stock market and/or are weighted based on their historic volatility.
Of the US$29.3bn (£18.8bn) in smart beta equity ETFs listed in Europe:
■ the two largest groups are dividends with US$17.5bn (£11.2bn) or 60 per cent of AUM, followed by low volatility with US$4.1bn (£2.62bn) (or 14 per cent) of the AUM; and
■ the two largest regions are European large cap with US$6.7bn (£4.3bn) [23 per cent] of AUM and Global large cap with US$5.8bn (£3.7bn) [20 per cent] of the AUM, with US large cap and real estate equity closely behind at more than US$5bn (£3.2bn) each.
It is not surprising that dividends are by far the largest category of smart beta ETFs given that a) many investors buy
certain stocks or funds because they are after the income, and b) in today’s low-yield world – in which fixed income would traditionally pay returns of 5 per cent a year but now pay at little over 0 per cent – investors now have to source yield and income from other asset classes such as equities.
Smart beta indices incorporate a passive rules-based discipline to rebalance exposures to a fundamental metric of value. The rules and methodology will generally cover:
1) Screening and selection (which stocks to pick).
2) Weighting (how to weight the individual stocks chosen).
3) Rebalancing (when to reshuffle, that is, re-screen and re-weight the basket).
We will now look at how a smart beta dividend index might work. An index’s initial screening and selection process could use dividend yields as a metric to filter the highest yielding stocks from the universe. It may next choose to weight the basket of highest dividend yielding stocks by the dividends paid over the last 12 months to minimise potential value traps. The annual rebalance methodology then adds or deletes stocks to ensure the constituent stocks consistently meet the index criteria.
The potential advantages of smart beta ETFs therefore include:
■ enhanced portfolio returns for a given level of risk;
■ reduced portfolio risk for a given level of return;
■ increased dividend income (in the case of dividend ETFs); and
■ the benefit from more complete diversification, since only buying funds based on market cap indices may not be optimal.
Why does smart beta work with ETFs?
■ Smart beta ETFs in Europe are set to remain on their current growth trend as the investors fully appreciate both the potential benefits of smart beta and the efficiency of an ETF.
■ ETFs are extremely liquid. ETFs are as liquid as the underlying market, since extra units can be issued according to demand. Additionally, being listed on an exchange, ETFs can be traded throughout the day. Many comparable funds may only trade at the end of the day, week, month or quarter.
■ The minimum investment is low. Investors can trade as little as one ETF share which could cost as little as £5 or £10 a share. Most traditional, non-ETF alternative strategies have minimum investment requirements that can be prohibitive.
■ It is cost-effective. Smart beta ETFs are generally cheap to trade (0.20 per cent a year a year to 0.50 per cent a year for most smart beta ETFs), while they can often outperform active fund managers.
■ It is transparent. Because smart beta indices are passive rules-based methodologies, investors can easily understand what is being bought, as fund holdings are usually disclosed daily. Non-ETF alternative strategies may disclose holdings as infrequently as every three months or even annually.
Nik Bienkowski is co-chief executive of WisdomTree Europe
Key points
Market capitalisation weighting may not always be the best method of indexing
Smart beta indices generally fall into four categories
ETFs are as liquid as the underlying market
