What is Multi Smart Beta?

Smart Beta is simply a different term for factor investing. Ultimately, stocks are not weighted based on their market capitalization but on fundamental and technical characteristics such as balance sheet quality or volatility.

There is impressive empirical evidence, that over longer periods of time such factor portfolios show more attractive properties than the benchmark or randomly generated portfolios.

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Risk and return of randomly generated portfolios

The following graph displays the return-risk-combinations of 500.000 simulated and randomly generated portfolios from 12/31/2003 to 09/30/2015. All portfolios are based on the historical composition of the STOXX Europe 600. In addition, we calculate seven technical or fundamental factor portfolios. These portfolios focus on a specific, return relevant “topic”. For instance, the factor portfolio “balance sheet quality” contains 100 stocks from the STOXX Europe 600 with an above-average balance sheet quality. It is striking, how positively those factor portfolios deviate from the benchmark and the cloud of randomly generated portfolios with regard to their return.

Smart Beta is a hybrid

Smart Beta: active or passive?

Smart Beta is a hybrid. The approach is passive as smart beta portfolios are strictly rule-based and reproducible. There are no discretionary decisions. At the same time the approach is active as the strategy seeks a positive return compared to classical benchmark portfolios and exhibits few similarities in structure.

Which factors are there?

There is no such thing as “the ultimate” smart-beta-factors. However, in sciences and in practice there is broad agreement on seven factors which are sufficient to manage portfolios.

The table below outlines economic reasons and considerations derived from behavioural finance theory which explain why those factors are attended by risk premia.

  • The business model and therefore the share price potential is underestimated
  • An overreaction to news flow leads to temporary mispricing
  • Companies with high profitability have a stable and competitive business model which is a unique selling point and decreases the probability of bankruptcy
Balance sheet quality
  • Companies with high balance sheet quality have little debt and can easily pay interest rates from cash flows
  • Often those companies seem “boring” and are temporarily undervalued
Earnings revisions
  • Companies with positive earnings revisions are systematically underestimated regarding future earnings and can therefore provide positive surprises
  • Small companies typically follow profitable niche strategies; such companies are “leanerr” and more efficient
  • Small companies are more often mispriced as they are less analyzed by equity researchers
  • Less volatile companies are characterized by stable and unremarkable business development
  • Those stocks are overlooked by managers and investors as they do not promise any sudden share price jumps
  • Companies with positive share price momentum benefit from investors’ “herd instinct”
  • The underlying assumption is that the historical increase in share price must be based on valuable information which is not yet entirely priced in yet

Are there “better” and “worse” factors?

The answer must be “no”. In the past, there was no distinct pattern implying any systematic over-performance as can be seen in the table below. The table displays the annual performance data of various factor portfolios.

Should different factors be combined?

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It is certainly reasonable to combine different factors rather than selecting one single factor. However, the devil is in the detail.

Investing in different factor portfolios simultaneously is suboptimal. Single-factor portfolios are constructed by producing the highest exposure to one single factor. While there is also exposure to the remaining factors, this is uncontrolled. If single-factors portfolios are combined, the interdependencies produce dilution effects. A reason for this is conflicts of objectives between the characteristics of different factor portfolios. For example, an undervalued portfolio is generally more volatile than an expensive portfolio.

As a solution Warburg-Multi-Smart-Beta is optimized on portfolio level, with the result that the portfolio is highly and equally exposed to all factors.

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