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Summary Part D: Implementation

12-01-2015 | Research | David Blitz, PhD, Pim van Vliet, PhD
The fourth part of the book discusses how low-volatility strategies can be implemented. In order to do this, various implementation approaches and related practical aspects are studied. The articles also explain how Robeco’s own specific approach, Conservative Equities, was developed and how client portfolios can be customized and optimized to achieve the best possible results.

Ten things you should know about low-volatility investing
Low-volatility stock portfolios can earn high risk-adjusted returns, but the methods used to construct them are quite technical, and not widely known. In this first article the most important aspects are narrowed down into a ‘top 10’ for easy reading. ‘Ten things you should know about low-volatility investing’ will surprise those who view this as a 21st century technique. For example, the low-beta anomaly was discovered many years before the size, valuation and momentum effects were documented.

Benchmarking low-volatility strategies
Investors who are convinced that low-risk stocks tend to earn high risk-adjusted returns over time still need a way of measuring the performance of their low-volatility asset manager. In this second article the authors explain why simply benchmarking an asset manager’s fund against an “appropriate” low-volatility index is not necessarily the answer. The problem for low-volatility investing is that a unique Minimum Variance Portfolio (MVP) which could act as such a benchmark exists only in theory as a collection of strategies and is not investible. Comparing a fund’s results against it would be artificial and arbitrary. As a solution, the authors suggest benchmarking against a standard market-cap weighted equity index, but adjusting for the level of absolute risk. Jensen’s alpha should be higher than the market and also higher than a low-volatility index.

Applying the low-risk anomaly to corporate bonds
The low-risk anomaly long seen in equities is also prevalent in credits. In this article the authors argue that it can appeal to long-term investors who want superior returns throughout the credit cycle. The anomaly exists because evidence shows that investors are willing to overpay for higher-risk securities, believing they will earn higher returns. Market segmentation discourages investors from selling out of one asset class ‘silo’ such as investment grade bonds for better returns in another. The empirical research shows how exploiting the low-risk effect can generate superior returns. The Robeco vehicle for achieving this is the Conservative Credits strategy, which can deliver higher returns with lower risk. This strategy is suitable for long-term investors who want to earn the credit premium with lower risk. It is especially ideal for insurance companies under the new regulatory regime of Solvency II, which favors shorter-dated and higher-rated bonds.

Long/short factor investing
Factor investing is gaining in popularity as investors seek the higher risk-adjusted returns offered by the value, momentum and low-volatility premiums. But is it better to invest on a long-only basis, or adopt a mix of long and short? In this third article both approaches are compared. Investment strategies based on the most widely acknowledged factor premiums in the equity market - the market, small-cap, value, momentum and low-volatility premiums - were considered. A long-only approach worked better in most scenarios, after accounting for practical issues such as benchmark restrictions, implementation costs and the eventual decay of the factors. The results are slightly contrarian as the study showed that a long-short approach is superior in theory, though not in practice.

Client-optimized portfolios
Taking a ‘one-size-fits-all’ approach to asset management might well suit the manager, but it’s not necessarily in the interests of clients who have different objectives but use the same strategy. In this final article, we explain why. As of 2013, the Robeco quantitative equities team manages more than twenty client accounts and runs each portfolio separately instead of applying one single model portfolio to all of them. Clients often ask why Robeco does this, since running a single model portfolio would be easier and more efficient for an asset manager. The answer is that client-optimized portfolios generate better, fewer and more liquid trades, and efficiently integrate client requirements. This results in lower transaction costs and higher net returns compared with a single model portfolio. So it actually pays to optimize each client portfolio separately.
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Author

David Blitz, PhD
Head Quantitative Equities Research


Author

Pim van Vliet, PhD
Senior Portfolio Manager



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