Study 2: Can You Break Down the PPCI to Explain Changes?
Each quarter, we calculate the PPCI from the instruments valued in our automated systems. However, we also produce other aggregated statistics, such as weighted average spread or coupon. An examination of the relationship between these metrics and benchmark rate and average price can explain the market dynamics and the differences between public and private credit instruments.
Component Metrics
- Coupon is the coupon used to determine the cash flow for each instrument and does not include the benchmark rate. It is calculated as a principal weighted average. The entire instrument cash flow does include benchmark rate in the valuation calculation.
- Spread is the rate added to the benchmark rate used to discount the cash flows back to a price. For loan valuation, spread is determined by multiple factors by the valuation agent.
- Benchmark rate is typically SOFR or LIBOR and is computed in our models as a forward rate derived from the active swap curve. For our decomposition analysis, we use the swap rate best related to the weighted average life of the valued instruments—typically four years.
- Price is the instrument price after all factors have been incorporated. Typically expressed as a percentage of par, price is also shown as the amount of discount to par to facilitate display. The change in the component metrics is what drives changes in price. We show price as a change in percentage of par.
- Composition is the measurement of the change in PPCI relative to the change in the portfolio of valued instruments.
In the chart above, we illustrate the relationships between these metrics in three highlighted periods. Spread and price have an inverse relationship; when the spread increases, the price decreases, all else equal. During the valuation process, we take into consideration changes in market spreads and yields. We evaluate portfolio company performance, including relevant credit metrics, to determine an appropriate spread to apply to the cash flows. Despite the relationships, the calculation methodologies prevent a conclusive summation of the components to exactly explain the results of any period. The first bullet highlights this:
- Q4 ’18: This period saw a large decrease in the coupon rate (-0.43%), which could have been the result of refinancings or resets as well as new issues. However, the spread decreased by less (-0.35%), which is consistent with a reduction in price (-0.83%). This reduction was obscured by the change in portfolio composition, which contributed to a decrease in yield of -0.20%.
- Q1 ’20: This period marked the beginning of COVID-19 and saw a huge decrease in benchmark rate (-1.22%), but it was almost fully offset by an increase in spread (1.31%). However, spread determines discount rate, so the price fell approximately 3.16%.
- Q1 ’22: This period saw a large increase in the benchmark rate, but since there were only slight changes in spread and coupon, there was almost no change in price.
In the chart above, the price is expressed as a positive amount (the discount from par) and clearly shows that the strongest relationship is between spread and price. The increase in benchmark rate largely does not affect the price of these instruments. Coupon has remained remarkably stable despite economic volatility. The entire range of coupon variability has been 100 bps, where spread has ranged by 150 bps in the same period, and the price is now appropriately moderately lower (discount is a half point larger).
We note that the pricing of a loan embeds many components. There are duration and volatility effects associated with any benchmark rate floors, the prepayment option (which is subject to market and credit conditions), and the concept of duration related to fixed spread (particularly when spread is a multiple of benchmark rate). The variance in prices can reflect these duration and volatility issues in a way that prevents the components above from explaining 100% of the aggregated yield changes. Please contact us for a broader discussion of these valuation elements.
The answer then to the question about explaining changes in PPCI is, yes, the best explanation is to consider these metrics in light of the market conditions and the difference between outstanding and new issue instruments. The components viewed in relationship substantially explain changes but do not explain 100% due to secondary and related factors not included in these primary components.
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