Performance Attribution: A Conversation with Steve Miller of S&P Capital IQ’s Leveraged Commentary & Data

April 4, 2014

steve_millerSteve Miller manages S&P Capital IQ’s Leveraged Commentary & Data (LCD), the authoritative source of leveraged-finance news and information. Among his many career milestones, he managed the team responsible for developing Gold Sheets, the Goldman Sachs/LPC Loan Index, and he was the co-founder and CEO of Portfolio Management Data LLC, a firm that pioneered statistical analysis of leveraged loans. In 2000, Standard & Poor’s acquired PMD, which later became LCD. Additionally, Steve writes commentary of the leveraged loan market for LCD’s wire service and is a regular contributor for publications such as Forbes and Business Insider. Steve is the Chairman of the Board and an investor of Black Mountain Systems.

Let’s start with the basics. Can you explain the difference between Performance Measurement and Performance Attribution?

Performance measurement is the calculation of performance, ideally using industry standard methods outlined by GIPS. This includes period return calculations along with geometric linking methods to minimize the impacts of portfolio size on return. Performance attribution is the analytical comparison of a portfolio’s performance to a benchmark and the breakdown of its excess return to a range of factors or “attributes.” In some cases, investors will view portfolio returns relative to a broad market index. In others, portfolio construction will be proscribed by certain limiting factors – e.g., caps on issuer, sector or rating concentrations – and therefore managers will use tailored sub-indexes that use similar constraints to benchmark returns.

Can you do one without the other?

You can measure performance without attributing the results to certain aspects of the management of the portfolio, however that latter point is often the primary driver for measuring performance. On the other hand, it is hard to attribute performance without the ability to calculate returns, since attribution typically requires the returns be recalculated on the underlying data based on the specific attribute being analyzed. So ideally, a system will handle both simultaneously.

In your experience, what distinguishes—or should distinguish— performance attribution modeling of leveraged loans from other asset classes?

Loans have many unique aspects that make benchmarking difficult. For instance, some investors buy primary in the new-issue market but benchmarks tend to introduce loans once they break into the secondary market and therefore the price at which a manager may buy an asset – the new-issue offer level – and where it breaks into the secondary is often different. As well, loans are typically pre-payable at any time by the issuer for either little or no prepayment fee. Therefore, measuring duration and prospective yield of the portfolio is difficult. Another unusual feature of loans is lengthy and varying settlement periods and therefore cash movements are not as regular as they are in instruments that trade on an exchange. Finally, loans can receive various fees during their term such as amendment fees and extension fees that can be difficult to capture in a benchmark.

Why has the Syndicated Loan market struggled to find a Performance Measurement and Attribution system that can handle the complexities of loans?

A major issue is non-standard data (e.g. market prices, fees, unfunded balances for revolvers and delayed draw term loans, frequent need to adjust historic transactions). Traditional players have not had to deal with these issues across the systems and data sets used for our industry.

Tell us a little bit about the S&P/LSTA U.S. Leveraged Loan 100 Index. How is it moving the needle forward on this issue?

The Loan 100 Index was created to provide a view of the more tradable, liquid names in the loan market. This slice of the broader S&P/LSTA Index benchmark constitutes, as the name suggests, the 100 largest facilities. Many loan mutual fund and CLO managers focus on these larger-cap names and, thus, the 100 Index provides a more relevant benchmark for these players, similar to the work the S&P 500 does for large-cap equity managers, in comparison to broader benchmarks like the Wilshire 5000.

What are the benefits (or necessities) to implementing a performance attribution system?

For a firm that is raising money in the retail or institutional space—as opposed to structured finance—attribution is a critical tool to help investors and prospective investors learn how they perform relative to a benchmark. It also reveals the various ways in which they are achieving alpha versus the overall market, whether it is by overweighting certain sectors, products, issuers, or other attributes. In the wake of the 2008/2009 credit crunch, investors are far more focused on the “how” of performance. It is no longer enough for managers to say they outperformed their benchmark. Investors want to understand how they did so and what are the potential risks of that strategy.

For those interested, here are a few more resources on the topic:

S&P’s Leveraged Commentary & Data
Investment Performance Measurement (Frank J. Fabozzi series)

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