With no industry standard for measuring multi-asset portfolios to date, buy-side performance and risk teams are coming together at TSAM New York (June 23) to thrash out ideas of best practice. Could the answer come from the vendor marketplace?
We recently caught up with Stan Kwasniewski from FactSet, who took time to answer some of our questions on the matter..
Hi Stan, would you be able to introduce yourself and give us an overview of your role?
Sure. My name is Stan Kwasniewski and I’m responsible for the development of portfolio, risk and quant solutions at FactSet. I’ve been with FactSet for almost 20 years and have spent the majority of my career developing attribution models. I’m passionate about portfolio analysis and developing tools to help facilitate it.
Year on year, the analysis of multi-asset class portfolios moves higher up the agenda. In this, what difficulties do you see from within the industry? How can these challenges be tackled?
Over the years, the biggest challenge that we’ve seen performance and risk teams face is in finding a portfolio analytics vendor that is able to properly analyze portfolios consisting of multiple asset classes. Vendors typically provide broad depth of coverage for one asset class – usually for either equities or fixed income securities. The performance and risk of various asset classes in balanced strategies need to be analyzed together in order to properly capture the benefits of diversification. We’ve seen our clients try to overcome these challenges by manually combining analytics from multiple systems for separate asset classes. FactSet’s strategy to overcome these challenges has been to teach our products how to properly handle multiple asset classes together through our full global asset coverage, best-in-class analytics, and industry-changing remediation and processing services.
It’s clear that when it comes down to multi-asset attribution, using Brinson is likely to fall short in providing meaningful analysis. Is there a ‘best practice’ methodology? If so, what? If not, why?
We hadn’t seen a clear ‘best practice’ methodology out there, so we decided to develop our own. Our clients wanted to see a multi-asset class attribution solution that reflected the order dependent nature of investment decisions, as well as attribution factors that were relevant to how the various asset classes are managed. Therefore, we blended together our top down and fixed income attribution models to create an innovative and accurate approach. Our model strips out the impact of asset class allocation decisions before going on to explain the additional impact that equity, fixed income and currency decisions had on relative performance.
It’s a fact – end users of data always seem to come back asking for more! How valuable do you think quality multi-asset analysis is to the client?
Extremely valuable. Confidently knowing how much each asset class and investment decision contributes to relative performance will help identify both strengths and weaknesses in a portfolio. This equips our clients with the knowledge to make adjustments that will help improve returns moving forward. The challenge is making sure that the analytics for all instruments are clean. I’ve seen situations where the ability to analyze a portfolio was compromised because of dirty analytics from a single security. Quality control needs to be an integral part of any multi-asset class analysis. FactSet ensures quality data through our Portfolio Services offering, which provides our clients with robust and transparent analytics reconciliation.
In order to stay competitive with rival companies, what would you say are the top 3 value-adding capabilities modern Performance and Risk teams need to have?
At FactSet, we find that multi-asset class performance and risk capabilities that are based on rigorously calculated analytics and customized to the investment process add the most value. Being able to deliver these analytics to mobile devices is something that we see Portfolio Managers expecting from their performance and risk teams. We have also seen an increasing demand for look through capabilities for passive investments, such as ETFs.
Any final thoughts?
The topic of decision-based analytics is also hot with our clients. Decision-based analytics measures how much a Portfolio Manager’s buying, selling and position sizing skill impacts absolute and relative performance. I think there is a great opportunity for innovation in this area, especially when it comes to multi-asset class strategies. Many of our clients are currently focused on decision-based analysis for equity-only strategies, but I could see this concept expanding into fixed income strategies in time.
By Jonathan Wiser, Head of Content, Osney Media.