How equity attribution can help active managers identify sources of alpha

The headwinds for actively managed equity funds are formidable. 

After too many years where few managers were able to beat their benchmark, investors are increasingly voting with their wallets. The AUM of passive investment products such as ETFs and tracker funds is forecast to double over the next two years. It is easy to understand why active investment strategies are not always the media darling. Although the additional cost of active stock or sector selection manifests itself in increased management fees, the same clarity does not always apply to excess returns. Passive strategies — which simply “track” a market index — seem to make most of the headlines and continue to attract a higher proportion of fund inflows. As the difference between high and low performers is narrowing, the expense ratio of investment management products is under scrutiny. If superior investment performance is elusive how can managers justify the premium that discretionary management has always enjoyed?

Both strategies need robust performance measurement tools, but it is especially active managers who need additional attribution analysis, as well as the ability to drill down to fund constituents. Almost two-thirds of asset management executives view performance measurement as a high value technology area, recognizing its growing role in demonstrating alpha to investors. It is also a powerful tool for managers of investment teams to distinguish market effects from investor skill in portfolio construction, stock selection, or trade execution.

The challenge that portfolio managers and quants face is clear: demonstrate alpha and excess returns or get out of the market; but as strategies and fund structures multiply, scalability is becoming a challenge. Replacing manual workarounds and legacy platforms is now a critical priority for firms. Consuming a large volume of data and analytics is also putting pressure on the ability of analysts and managers to interpret and act upon the data. It is no surprise that best-in-class performance measurement platforms have invested heavily in data visualization as well as remote deployment and SaaS capabilities.

Unlike most back-office tasks, performance measurement does not have to reinvent itself to be relevant to fund managers and analysts. Accurately measuring investment returns and analyzing which decisions contribute to alpha is germane to pre-trade analytics and asset managers’ core competency — managing investments. Surprisingly, existing practice for performance measurement has not always reflected this critical role. In many firms it remains a complex, administrative post-trade function for standardized and undifferentiating reporting to asset owners. The reliance of performance measurement on complex valuation and attribution logic comes straight out of investment theory, and the academic nature of the underlying calculations has allowed insular domain expertise to flourish, without benefiting from broader software innovation trends.

However, that picture is rapidly changing, driven by the information needs of managers, analysts, and asset owners.  They need access to a much wider range of analytics, with the ability to drill down into the details of every performance and attribution variable. Flexibility of deployment and adaptability to specific investment strategies are also core — as more stakeholders in risk, finance, client reporting, and sales need to have easy access to shared and trusted performance data.

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