Fundamentally resetting reporting

The investment industry has always struggled to fend off short-term pressures that prevent it from being genuinely long-term, to the benefit of end beneficiaries. This despite much evidence to support the existence of a significant long-term investment premium – up to 1.5% per annum according to TAI research. A premium of this size can only exist if it is hard to capture. I assert that it is hard to capture for behavioural reasons, which are exacerbated by traditional performance reporting. As a consequence, many investment mandates being terminated for the wrong reasons and at the wrong time.

To rectify this and to promote a longer-term outlook, TAI has collaborated with members (particularly Baillie Gifford, MFS, S&P Dow Jones Indices and WTW) to devise a methodology and framework that allows portfolio evaluation to be based not only on market-value returns, but also on changes in fundamental attributes over time. This new attribution and monitoring framework – called Fundamental Return Attribution (FRA) – separates a portfolio’s returns into three main components:

• Returns arising from changes in market sentiment (multiple return)
• The growth of the portfolio’s fundamental characteristics (growth return)
• The change in these fundamental characteristics due to changes in the portfolio’s holdings (activity return).

In our view, decomposing returns into these three components enables a deeper understanding and assessment of how an investment strategy generates returns. Compared to more traditional attribution methods (that focus on explaining returns by reference to the performance of different groupings of securities), this approach considers how the decisions of the asset manager within their investment process generate the portfolio’s returns.

The approach separates out returns arising from changes in short-term market sentiment (essentially noise and, arguably, mean-reverting around zero impact over the long term), enabling a longer-term outlook by asset owners and asset managers when evaluating recent performance or setting future return expectations.

 The FRA methodology – which is described in more detail in our research paper – should allow all institutional investors to think differently about investment performance and how it is reported. And in turn should improve the quality of conversations between asset managers and asset owners about the long-term return drivers of an investment strategy, particularly during periods of underperformance. This may prove quite helpful in the predicted forthcoming period of significant turbulence. In addition, it should also help broaden the conversation to include how the quality of underlying decision-making can produce sustainable long-term returns.

This FRA framework can be applied to all asset classes but, as with any single measurement methodology, it may be more applicable to some mandates than others. Currently, it has been applied to portfolios using company fundamentals, but there is potential to apply it to other characteristics that investors increasingly wish to monitor or manage in their portfolio.

Some of our members are already making use of this methodology to assess equity managers and expect to widen that to other asset classes.

They have found it to be particularly helpful in understanding what has been driving performance when there has been a divergence in fundamentals and stock price performance in the wider market.

In future, we think this methodology will also be able to support investors who seek to align their portfolios to ESG objectives but are struggling to identify if a portfolio’s decarbonisation is, for instance, due to underlying companies reducing emissions or the divestment of high-emission companies. We believe this framework, and an enhanced version of the tool, could provide much needed clarity into how ESG objectives are being managed and achieved.

A significant part of the Institute’s mission is to influence change in the industry and we believe this framework can achieve this if widely adopted. To that end, we are open-sourcing on Github.com the underlying computer code as a way of making it easy for investment organisations to apply this framework to their own portfolios and to develop more meaningful reporting tools.

The genesis of this research was to find a monitoring tool that gave the asset owner sufficient confidence to retain a currently-underperforming-but-high-quality asset manager. That would counteract the behavioural forces pushing for termination and would, further, allow the capture of that long-term return premium. Our hope is that FRA will turn out to be a very valuable contribution to the investment industry and the end beneficiaries we serve.

Tim Hodgson is co-head of the Thinking Ahead Group, an independent research team at WTW and executive to the Thinking Ahead Institute (TAI).