In an environment where passive strategies look set to dominate the future investment landscape, are vendors providing technology solutions that meet the needs of today’s asset managers?
According to a recent Forbes article, investors have withdrawn an estimated $1.2 trillion from active U.S. equity mutual funds and invested more than $1.4 trillion into U.S. equity index funds and ETFs since the end of 2006. Estimates from Morningstar suggest that passive funds and ETFs investing in U.S. equity stocks now hold approximately 48% of market assets. Bloomberg recently reported that if current trends continue, it expects this to rise to above 50% by the end of 2019. While this trend has not been mirrored as strongly across all markets globally, a 2018 report by the Investment Association (IA) shows that the proportion of assets invested in index tracking funds and ETFs continues to rise among UK-based investors, with more than a quarter of all assets now invested in passive strategies. What does this switch to passive investment mean for the world of performance attribution?
Impact on performance attribution
Traditionally, active managers have used performance attribution to explain their investment skill by breaking down the excess return over a market index into the various decision-making steps of their investment process. Active managers make specific allocations to asset classes, countries or sectors, specific stocks, or fixed-income portfolios to optimize the impact of decisions made regarding duration, yield, currency, or credit exposure. Various models, intended to help managers explain their outcomes, have been developed, tested, and adopted over the past few decades. So how can performance attribution help the passive fund manager when a portfolio’s investment strategy is intended to replicate the performance of the underlying index or market in which they are invested?
Many underlying variables are hard to predict
While not typically an issue for U.S. mutual funds and ETFs, in European markets it is often necessary to adjust for the difference in timing from when a NAV is struck at the close of the market. Similarly, if not adjusted for, fair value pricing policies can have an impact on relative performance. At a more granular level, there is a range of other factors that can commonly cause a fund to diverge from the index being tracked. High on the list are the impact of manager fees and expenses, and the explicit costs and timing impact of trading the portfolio to maintain alignment with the underlying index. The use of futures or other derivatives to facilitate index replication can also lead to a divergence in investment outcomes. “Cash drag,” where a fund is forced to hold cash or cash equivalents that are not present in the index, can be either a negative or positive contributor, depending on the direction of market returns. What does this mean for the typical performance attribution solutions currently offered by technology providers (e.g. Brinson-Fachler and Brinson-Hood-Beebower)?
Traditional models may now need to be customized
Where the requirements are more granular and there is a need to capture factors beyond allocation and stock selection effects, greater customization is required. SS&C’s market-leading Sylvan™ performance & attribution software addresses this challenge. Sylvan’s proprietary User Defined Attribution (UDA) provides a comprehensive and flexible framework that enables users to easily define and implement their own custom attribution models. In combination with Sylvan’s highly configurable class scheme models, and the ability to carve out segments of portfolios as well as define and maintain an unlimited number of security and portfolio properties, Sylvan’s UDA is fully capable of supporting the detail required by a “passive strategy” approach to analyzing performance attribution. Sylvan supports these custom class schemes and properties across all asset classes and for all equity, fixed income, and multi-asset class attribution models. Whether a manager wishes to measure the impact of holding cash, isolate and analyze the cost of trading, or break down the impact of different fees and expenses, Sylvan’s flexible, data-driven approach and highly configurable analytical tools can help today’s passive managers understand the drivers behind their portfolio tracking errors and the underlying market.
Asset Management, Research, Analytics, and Consulting, Wealth Management