Insights

Discount rates declined in November, retracing, in part, some of their steady climb northward this year. In November, the discount rate for the Callan illustrative plan (representing a typical shorter-duration corporate DB plan), which compares to the liability duration of FTSE’s Pension Liability Index–Short, fell by 56 bps. In November, long AA corporate spreads, as measured by the Bloomberg Long Corporate AA Index, narrowed by 19 bps. Interestingly, the last time long corporate AA spreads tightened this much was during November 2020, which hosted both a presidential election and the announcement of not one but two viable COVID-19 vaccines. Interest rates also fell, with the 10-year Treasury note falling by 38 bps over the month to 3.69%, after reaching a high of 4.23% on Oct. 24.

What Drove the November 2022 Discount Rate Changes

Part of the rally in spreads and rates was related to Chairman Jerome Powell’s statement that the Federal Open Market Committee (FOMC) will seek to “moderate the pace of rate increases,” as the Fed approaches the level needed to bring inflation down. It should be noted that the meaningful uptick in rates, or increase in borrowing costs, has slowed the volume of financing across many spread sectors.

For institutional investors, data are the bedrock of their investment programs, and they need completely accurate and up-to-date information about their data—a single source of truth. How can they achieve this?

Callan has developed the concept of the institutional investor “Data Vault,” a repository where data is collected, cleansed, aggregated, and curated. We look at the vault as a data continuum with each building block connected by underlying principles of a single data (the “god particle”) enriched for specific purposes based on what decisions to take.

Selecting benchmarks for target date funds (TDFs) has long been a challenge. Most TDF providers build a custom benchmark for performance comparisons. While this approach is useful in measuring two key variables in TDF performance—manager selection and tactical positioning—it does not capture differences in glidepath design and asset allocation that are the major drivers of relative performance across the TDF peer universe.

To address this issue, Callan pioneered the creation of TDF benchmarks that seek to identify a “consensus” glidepath design for the entire TDF universe so that the asset allocation effect can be captured in manager returns relative to this consensus benchmark. S&P institutionalized this concept with the creation in 2008 of the S&P Target Date Index series, which provides the TDF industry an objective third-party benchmark and which has been adopted by a number of major TDF providers.