The performance function has always played important part in the investment management process, providing the feedback required to objectively evaluate the outcome of investment decisions. However, increasingly, teams are looking beyond the traditional ex-post delivery of reports in order to create an ex-ante feedback loop that helps to improve investment decision-making going forward.
Speaking at the recent Risk and Performance Summit, a panel of industry practitioners chaired by Bee Choo Ng, Performance and Attribution Manager at AustralianSuper, discussed different ways in which performance teams can query data sets to add more value to portfolios.
Andrew Kophamel, Head of Data Management and Performance Measurement APAC at Aberdeen Standard Investments said that, while looking beyond traditional performance measurement and attribution is not yet standard practice, the Aberdeen team does play out different scenarios to test the impact of alternative outcomes on an ad hoc basis.
For example, his team used Monte Carlo simulations to look at how allocations across asset classes and income versus capital assets would drive an individual investors expected pension, taking into account not only expected returns/volatilities, but also fees and expenses – something increasingly brought in to focus with the Regulatory Guide 97 Disclosing fees and costs in PDSs and periodic statements (RG97) regulations.
In another case, the Aberdeen performance team used trade cost analysis (TCA) to model the impact of behavioural biases on investment decisions – something often acknowledged but rarely quantified. In this case, detailed analysis of continued stock performance after securities were “topped up” or “sliced back” revealed certain behavioural patterns that were commonly held. Kophamel said the exercise allowed managers to be more self-reflective, cognitively aware and conscious in their portfolio construction.
“We investigated what would have been the impact over a particular period, bearing in mind the rationale for getting in with the size of the conviction and the market and outcomes at the time. I found that a particularly interesting exercise because it is out of the remit of our usual performance and attribution scope, but it was also very consequential in changing fund manager behaviour,” Kophamel said.
Performance teams – and indeed front office teams – can also reach out to their vendors to conduct further analysis. At FactSet, Marcus Burley, Analytics Specialist, said the team regularly deals with “what if” type requests on an ex-ante basis, particularly where ESG impacts are concerned.
Burley said questions around realistic carbon intensity targets and the impact of Modern Slavery are among the examples that pop up relatively frequently. “An example could be ‘if we choose a particular net carbon intensity target by 2042, what band of performance will we need to be prepared to tolerate?’ On the Modern Slavery side it could be ‘if you take a blunt approach and cull most high risk names from your portfolio, what is that going to do to our investment objective?” he said.
What if analysis, beneficial though it is, does come at a cost which can be challenging when performance teams are resource- constrained.
Kendal Mogg, Business Analyst at Resolution Life, said that identifying and prioritising those risks that are critical to the organisation is essential when faced with a long list of potential risks and analysis requests.
“There are so many scenarios and you have scarce resources, so where do you allocate the resources to conduct deeper analysis? Where do you get the biggest bang for your buck? The list is endless, but it is about what is right for your organisation and what really reflects the risks that the firm is facing,” Mogg said.
She added that it is critical that the performance function works closely with the investment teams so that there is mutual understanding of the processes and risks involved. “Having that open communication with other teams is key, you need everyone to buy in, be part of the process and open to discussion,” she said.
Whether it’s done internally or externally, a meaningful ‘what if’ analysis also requires access to quality data which can be quite a challenge, particularly where transactional data or look through data is concerned.
This is where thinking ahead and getting performance teams involved at the investment strategy level can add significant value.
“Taking away things like socially responsible investing (SRI) overlays are a great ‘what if’ analysis situation, but if you didn’t think about that three years ago when you structured your systems and your portfolios and you don’t have that layer exposed to play with, then it becomes very hard to then dig that out again. You need a bit of foresight about what aspects of the portfolio you want to have as a lever to pull on in any what-if analysis,” Burley said.
The multi asset challenge
The panel also discussed the challenges of multi asset-class attribution; the advantages and disadvantages of investing in decision-based attribution to capture the value add from investment decision processes vis-à-vis having several single-asset class attribution models to explain the source of value add for specific portfolio or product; and different ways to measure the benefits of diversification.
While often there is a focus on absolute performance, the panel agreed it is worthwhile measuring the impacts of diversification as this better reflects the way decisions in multi-asset portfolios are made.
At Aberdeen, Kophamel has spent some time quantifying the benefits of portfolio construction. “We were trying to sequentially articulate the impacts of a longitudinal investment process by separating the impact of ‘can I choose a good company’ versus ‘can I create a well-balanced diversified portfolio’. These are two completely different skills,” Kophamel said.
By separating these skillsets, selecting pools of quality companies and then managing those risk exposures to create a balanced portfolio, the team was effectively able to improve the portfolio construction process.
At FactSet, Burley said that to date, questions from investors have typically focused on understanding how similar two managers might be, rather than the benefits of diversification.
“That’s typically about making sure your active managers are providing active exposure when combined together, so they’re looking at overlap analysis and how similar the actual asset choices of two active managers are, but diversification is something that we do expect clients will want to take more control over,” he said, adding that FactSet is working on a multi asset class optimisation tool that will allow investors to pursue diversification as a line of inquiry.
“You can start to play with the composition of the portfolio and see what that does to your diversification or to your performance outcomes, so if you minimise risk or tracking error, what does that do to your diversification? Rather than capturing another statistic, it’s about better informing the process and making that part of the valuable feedback loop,” Burley said.
New technologies are undoubtedly changing the role of the performance function, but it’s a change that can only be seen as a positive outcome.
“Performance teams have traditionally done a lot of reporting. They know the data, they know the data limitations and they are kind of considered the source of truth. Using these new technologies that are becoming available opens up opportunities for the performance function to provide much more value to the organisation, to not just be seen as a cost-centre but to be a true value add function,” Mogg said.