While excess performance is highly desirable, it does not define investment skill per se - Patrick Braun, MSCI Barra
With the arrival of 130-30 products, the ‘value added’ debate between active long-only managers and their hedge fund colleagues is heating up again. As the convergence of many financial products becomes clearer to all parties, a new question arises: Beyond potential higher returns for investors, could the success of an active fund manager’s business stem from showing clearer product excellence?
As the development of rigorous alpha engines becomes the cornerstone of active investment, for many fund managers, setting up systematic back-testing of their alpha generation process may be the next priority.
There is little disagreement that consistent performance in excess of benchmark returns should be rewarded with high fees. The definition of this benchmark is, however, less clear. Sponsors may define their own benchmarks, and beta calibration, ahead of ex-post performance discussions with their asset managers. The asset mix decision between alpha and beta is associated with liabilities, and therefore remains the sponsors’ responsibility. Once the beta terms are defined, the quest for alpha should be the focus of the active fund managers.
In mean-reverting equity markets, alpha opportunities often exist for limited periods. Regardless of the horizon of market analysis, the constant search for new sources of alpha is a dynamic process. It is about reaching a rapidly moving target before it disappears into the beta world, or out of the mandate’s boundaries.
For many active equity fund managers, this search for alpha aims at achieving superior returns in excess of a benchmark. While excess performance is highly desirable, it does not define investment skill per se. Positive risk-adjusted performance, like, to some extent, high information ratios, could define investment skill, and luck.
As 130-30 products are publicised more widely, higher risk and higher fees may only be justified by alpha-related results. In the world of active equities, as other asset classes, only investment skill is worth being leveraged.
Institutional alpha products have often become ‘portable’. This suggests they can be added as independent layers of alpha onto existing core portfolios. Only sponsors can really assess the independence and the value added of a new strategy to their existing portfolios and liabilities. While active fund managers may flag the independence of their alpha products to main market indices, it is equally important to describe their scalability. The question of capacity matters to both sponsors and fund managers. How scalable is a fund over time?
Clarke, de Silva and Thorley helped the debate in 2002, when they defined the transfer coefficient (TC) of an equity portfolio as “the correlation between active weights and forecasted residual returns”. While the information coefficient gives insights into the ability of a process to forecast returns, TC measures how well expected alphas are passed into the invested portfolio. Like performance attribution, an analysis of TC could be investment process-dependant.
The most popular example of TC usage features the impact of a portfolio constraint – such as short-selling – on the expected information ratio of a strategy. TC can also be used to simulate the scalability of an investment idea, to better understand a fund capacity.
Innovation is often a simple improvement of what now exists. The systematic usage of back-testing tools can help ongoing innovation in risk management, financial engineering and active fund management.
Encouraged by regulatory bodies globally, even when not mandatory, back-testing is used to test whether risk management processes work effectively. These include risk and valuation models, and their implementation.
The visualisation of new financial products also benefits from back-testing analytics. With high frequency data available, financial engineers can analyse risk/performance profiles of their alpha products. This enables them to assess the business sustainability of new funds, including cloning risks.
For active fund managers, back-testing tools are used to fine-tune existing investment strategies. This applies to running simple tests on portfolio legacy constraints, to the validation of new information feeding the alpha generation process.
In a business environment where the best performers take it all, there are few choices for active managers. In the quest for alpha, can they aim at anything else but the winners’ circle?
• Patrick Braun is vice president, product management, MSCI Barra
© fe July 2007