By continuing on this site you have agreed to cookies being placed and accessed by this website. More information and adjusting cookie settings.
Robeco Enhanced Indexing invests in global developed markets equities, and has a low tracking error against its benchmark, the MSCI World index. In recent years, performance has been strong. In this article we focus on one element that distinguishes Robeco’s strategy from those of others: our short-term stock selection model (SHOT).
Low-volatility stocks are known to lag in rising markets and lose less in falling markets. On average this is true, but is it always the case? Examining the historical evidence we find that unlikely scenarios – both positive and negative - do occur once in a while. Low-volatility investors should therefore not only focus on averages, but consider a broader range of possible outcomes.
Generic strategies designed to harvest a certain factor premium regularly conflict with other factor premiums. We find that the premiums associated with these strategies tend to shrink, sometimes even to zero, in these periods of factor disagreement. But enhanced factor strategies avoid stocks that are unattractive on other established factors and continue to deliver when generic factor strategies struggle.
There is a shift towards allocating to the factor premiums momentum, value and low volatility. However, since common factor indexes are a suboptimal way to harvest factor premiums, this paper shows the improved results of a more sophisticated approach. Factor strategies developed by Robeco lead to higher returns, while lowering the risks, resulting in higher Sharpe ratios.
Robeco’s quantitative duration model drives the performance of quant duration solutions such as Robeco Lux-o-rente and Robeco Flex-o-rente. We monitor the performance of the model and regularly investigate in which circumstances the model performs well and which conditions are more challenging.
In 1999, fifteen years ago, Robeco found that quantitative stock selection techniques known to be effective in developed markets are also able to deliver superior investment results in emerging markets. What are the biggest takeaways from the research done and how does the model work in practice?
Investors increasingly embrace “smart beta” investing, by which we mean passively following an index in which stock weights are not proportional to their market capitalizations, but based on some alternative weighting scheme. Examples include fundamentally-weighted indices and minimum-volatility indices. In this whitepaper we first take a critical look at the pros and cons of smart beta investing in general. After this we successively discuss the most popular types of smart indices that have been introduced in recent years.