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What’s hot: a report on the Axioma Quant Forum

This autumn’s Axioma Quant Forum in London drew some 140 portfolio construction and risk modelling specialists from asset management companies, institutional investors and investment banks.

This autumn’s Axioma Quant Forum in London drew some 140 portfolio construction and risk modelling specialists from asset management companies, institutional investors and investment banks.

Sebastian Ceria, Axioma’s CEO, kicked off the event with a talk on his work in the field of multi-period portfolio optimisation. Practitioners tend to use constrained one-period portfolio optimisation to take into account long-term views and stop optimal portfolios from becoming over-concentrated while over-exploiting asset return correlations. Multi-period optimisation is a much more elegant and formal solution to the problem, but its complexity has deterred practitioners. Axioma sees it as an important axis of continuing research and development. We shall stay tuned!

I was kindly invited to present our paper “An integrated risk-budgeting approach for multi-strategy equity portfolios”. This describes what we believe to be a more effective way of constructing portfolios that capture the beneficial factor premiums of smart beta indices, such as value, size and low volatility, while avoiding the problems commonly found in combinations of such indices. These include:

  • Uncontrolled multiple factor exposures that vary over time
  • Uncontrolled active, and often large, risk
  • Strong biases towards sectors or countries that aren’t necessarily wanted
  • In some indices, liquidity issues that put too much weight on the smallest cap stocks
  • Too often a degree of non-optimal turnover, in particular when there is a combination of smart beta indices, in which case the netting of positions is not possible

The problem of turnover reduction; the trade-off between rising returns and falling turnover

These topics were discussed by Massoud Mussavian from Cantab Capital Partners and Peter Korteweg from APG.

Massoud proposed ways to reduce turnover in well-known systematic strategies based on factors, e.g. momentum and value. He showed how to assess how much turnover is generated simply by market drift, and how this can be minimised without adversely affecting the strategy performance before transaction costs and market impact. But if removed, turnover can have a significant positive impact on performance if transaction costs and market impact are included. He showed how turnover in equity value strategies tends to concentrate around the dates of publication of earnings while the turnover of equity momentum strategies increases around market peaks and troughs.

Peter Korteweg then highlighted that pension funds like APG are committed to wasting as little as possible on unnecessary transaction costs and market impact. APG uses measures of marked liquidity to help reduce such costs by adapting the way it implements its strategies. Peter’s analysis showed that equity markets are most liquid on Thursdays and least liquid on Mondays: the largest transaction volumes are seen on Thursdays and the smallest on Mondays. He also showed that volumes are predictable to some extent. When volumes increase they tend to stay high and when they fall they tend to stay low. Volumes tend to increase around earnings announcements and stock inclusions/exclusions in/from indices.

The management of active share in active portfolios

Ioan Mirciciov from Macquire Securities Group discussed a topic that is currently ‘hot’ with investment consultants: the management of active share in active portfolios. Active share is a measure of how much a portfolio deviates from a reference benchmark index. It was introduced by Cremers and Petajisto in 2009, who showed that active funds with high active share tend to outperform. Ioan Mirciciov proposed a framework wherein active share targets can be considered in the problem of portfolio optimisation. He showed that including active share constraints in the portfolio optimisation problem acts as a form of robust optimisation, where portfolios are optimised to maximise excess returns over a benchmark index for a given level of target tracking-error risk. In his view, active share targets should depend on the skill and on the number of stocks and concentration of the benchmark index.

Smart beta indices compared

There is, it can be argued, growing recognition that smart beta indices can prove to be rather clumsy tools for building portfolios strongly exposed to factors like low volatility, value or size. Picking up on this theme, Christopher Cheung from State Street Global Investors dissected a number of well-known smart beta indices and detailed their strengths and weaknesses. He concluded that none of the indices is an optimal solution for all investors: all smart beta indices present pitfalls that some investors may not tolerate, for example too high a tracking-error risk, over-concentration or undesired factor exposures.

Other presentations

  • Jung Hun Kim, Pioneer Global Asset Management: Targeting individual liabilities for defined contribution pension funds
  • Amadeo Alentorn, Old Mutual Global Investors: The benefits of market neutral strategies
  • David Jessops, UBS: Portfolio construction and How to make most of the insights contained in one’s return forecasts
  • Simon Lansdorp: Factor investing
  • Siebert Kruger, Credit Suisse HOLT: Different ways to generate excess returns in equity portfolios based on the depth of analyst coverage

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