Key takeaways
- Headline below-par metrics may substantially overstate portfolio stress. Using loan-level BDC disclosures, we find that a significant share of discounted positions are associated with basis established when the investment entered the portfolio rather than subsequent valuation deterioration.
- For loans entering portfolios at a discount, approximately three quarters of the observed deviation from par is associated with entry basis rather than post-origination valuation movement. Headline below-par metrics therefore overstate the extent of credit weakening across BDC portfolios.
- Post-origination stress is concentrated in loans originated near par. Loans booked close to par exhibit the highest post-origination adjustment and migration into discount, making them the most informative segment for detecting evolving credit conditions. Early signs of stress emerge through gradual erosion of near-par assets rather than further declines in already discounted loans.
Executive summary
Investors often use the proportion of assets marked below par as a simple gauge of stress in private credit portfolios. Using loan-level disclosures from more than 6,000 investments across 34 listed BDCs, this paper finds that such an interpretation may be incomplete.
By applying an entry-adjusted valuation framework, we separate valuation effects associated with basis established at portfolio entry from those emerging after origination. The results suggest that a substantial portion of below-par marks, particularly among loans originated at a discount, reflects entry basis rather than subsequent deterioration.
Conversely, valuation movement after origination is concentrated among loans that entered portfolios near par. These exposures exhibit greater migration across valuation states and provide a clearer signal of evolving borrower conditions.
The findings suggest that investors may gain more insight from monitoring movements within the near-par segment than from focusing solely on the deepest discount bucket.
Why below-par marks can mislead investors
Fair-value marks in private credit portfolios are often treated as a direct signal of borrower stress. In practice, they can reflect two very different forces: deterioration in borrower credit quality, or pricing and structural features embedded when the investment entered the portfolio. Distinguishing between these two effects matters. If observed valuation dispersion is primarily driven by entry pricing rather than by deterioration after origination, then headline measures of portfolio stress that focus on value relative to par may overstate the degree to which credit conditions are weakening across private credit portfolios.
This distinction is particularly relevant in the context of Business Development Companies (BDCs), which have become an important source of financing for middle-market borrowers as private credit markets have expanded over the past decade. As these portfolios grow, investors and market observers increasingly look to the fair-value marks reported by BDCs as an indicator of portfolio health. Disentangling these effects is inherently difficult, particularly in markets where price discovery is limited and valuations are model-based.
This paper examines valuation outcomes across BDC portfolios using loan-level disclosures from the Schedules of Investments (SOIs) included in regulatory filings by listed BDCs. Rather than attempting to infer borrower-level credit deterioration directly, the analysis focuses on how observed fair-value marks relate to the pricing basis recorded at entry. By decomposing each investment’s distance from par into an entry basis component (recorded cost relative to face value) and a post-origination component (subsequent fair-value movement relative to that recorded basis), the paper provides a simple cross-sectional view of how valuation marks are distributed across the BDC universe. This approach allows us to assess whether observed valuation dispersion is primarily associated with entry pricing decisions or with subsequent changes in asset quality.
Building an entry-adjusted view of portfolio stress
The analysis uses loan-level disclosures from the SOIs included in periodic filings by listed BDCs with the U.S. Securities and Exchange Commission. The sample comprises 6,387 individual positions across 34 BDCs as per February 2026 and includes a broad cross-section of direct corporate credit exposures.
Instrument types were classified using a rules-based taxonomy designed to isolate funded debt claims on operating companies. Inclusion was based on descriptors such as term loan, revolver, credit facility, bond, lien, secured, unsecured, subordinated, unitranche. Both fixed and floating rate instruments were retained. No distinction was made between loan and bond formats where the underlying exposure represented direct corporate credit risk. Instruments associated with equity ownership, fund structures, securitized products, or embedded equity optionality (e.g. convertible or hybrid securities) were excluded.
Exposures are measured on a funded basis, using reported fair values as a proxy for economic exposure. Undrawn commitments and availability-based facilities were excluded where identifiable, while drawn revolving exposures were retained. Revolving credit facilities represent less than 1% of total principal and do not materially affect the results. This approach aligns the dataset with realized balance sheet risk rather than contingent liquidity exposure, which is not consistently disclosed across BDC filings. The resulting dataset provides an economically consistent representation of private credit exposures, subject to minor classification noise inherent in issuer-reported taxonomies.
Seniority bucket was assigned using a rules-based text classification applied to the reported investment type descriptors. Classifications were made only where the contractual position in the capital structure was explicitly identifiable from standard market terminology, with instruments containing terms such as “first lien”, “second lien”, “unitranche”, “subordinated”, or “unsecured” mapped to corresponding seniority buckets. Where descriptors were ambiguous or insufficient to determine priority of claim, exposures were conservatively left unclassified rather than inferred. This approach prioritizes classification precision over coverage, avoiding model-driven assumptions that could introduce structural bias into the analysis, particularly given the heterogeneity and issuer-specific nature of BDC disclosure conventions.
The analysis relies on three variables that are consistently reported across BDC disclosures:
- Principal (or par)
- Amortized cost
- Fair Value
These values allow the current valuation of each investment to be expressed relative to its recorded accounting basis.
For each investment, the current distance from par is decomposed into two additive components: an entry basis component and a post-origination component. Both components are measured relative to stated principal amount, such that together they equal the total deviation of fair value from par. Conceptually, the entry-adjusted valuation framework separates valuation effects embedded at entry from valuation changes that emerged after origination. Because the relationship between cost and principal is largely established at acquisition and tends to remain comparatively stable over time, subsequent changes in fair value are captured primarily through the post-origination component.
This decomposition follows directly from the accounting relationship between the three reported variables: (FV − Par)/Par ≡ (AC − Par)/Par + (FV − AC)/Par, such that the two components sum exactly to total distance from par by construction.
This is not a valuation model; it is a mechanical decomposition of reported figures. It makes no claim about why fair value deviates from par, only about when, relative to origination, the deviation arose.
How entry basis can distort the stress picture
The Entry component captures the difference between recorded amortized cost and face value and is used as a proxy for basis established when the investment entered the portfolio. This captures in aggregate what might be described as structural discounts – original issue discounts, upfront fee structures, illiquidity or complexity premia embedded at market-clearing spread – that represent compensation for risk at origination rather than evidence of subsequent credit weakening.
The Post-Origination component captures the difference between current fair value and amortized cost, measured relative to principal amount. This represents the portion of valuation movement that emerges after the investment has entered the portfolio.
To facilitate interpretation, investments are grouped into entry pricing buckets based on their cost-to-par ratio.
Loans are classified as:
- Discount: cost-to-par below 0.98
- Near par: cost-to-par between 0.98 and 1.02
- Premium: cost-to-par above 1.02
These thresholds create narrow, symmetric bands around par that distinguish between loans recorded meaningfully below face value, those recorded close to par, and those recorded at a premium. This classification allows valuation outcomes to be interpreted in the context of the pricing conditions under which the loan originally entered the portfolio. Portfolio-level results are calculated using principal weights so that aggregate measures reflect economic exposure rather than the number of reported positions.
Given that a substantial portion of BDC assets is classified as Level 3 under ASC 820, reported fair values may reflect model-based estimates rather than observable transaction prices. This is particularly relevant when interpreting gradual valuation adjustments over time.
The entry-adjusted valuation framework described above provides a simple way to separate entry pricing effects from subsequent valuation movements. Applying this framework to the BDC universe allows us to examine how current valuation marks are distributed across loans that entered portfolios at a discount, near par, or at a premium.
Most below-par marks reflect entry basis, not deterioration
The starting point for the analysis is a critical distinction: not all loans trading below par today arrived there for the same reason. Some were recorded below par at entry and have remained there with limited subsequent movement, while others entered portfolios close to par and only later moved lower as fair values adjusted. Looking only at current, aggregated marks obscures this distinction. Decomposing valuation outcomes by entry bucket makes it possible to separate loans whose discount largely reflects entry basis from those whose discount appears to have emerged after origination.
Across the sample, three broad groups can be identified based on cost relative to face value at entry: loans booked at a discount, loans booked near par, and loans booked at a premium. As shown in Figure 1, the distribution of fair value relative to par is concentrated around 100% when weighted by principal amount, indicating that most economic exposure remains close to par. Only a relatively small share of principal resides in deeply discounted positions. The resulting pattern is asymmetric. Loans entered at a discount account for the majority of negative deviation from par. However, this deviation is overwhelmingly explained by the entry component rather than by subsequent valuation movement. By contrast, loans entered near par show only a modest overall deviation from par, yet a larger share of that deviation is attributable to post-origination effects. Premium-originated exposures are comparatively small in aggregate and do not materially alter the portfolio-level picture.
FIGURE 1 Distribution of Fair Value to Par (Principal-Weighted)
Note: Distribution of fair value relative to par across 6,387 investments from 34 listed BDCs as of February 2026. Values are weighted by principal amount. Fair value represents the manager-reported valuation disclosed in regulatory filings.
This distinction matters because the market often treats all below-par marks as evidence of borrower stress. The results suggest a more nuanced interpretation of BDC marks. For a meaningful portion of the discounted universe, the discount appears associated with basis established at portfolio entry rather than newly emergent valuation deterioration.
Figure 2 summarizes the average principal-weighted contribution of the entry basis and post-origination components across each entry bucket. There, the weighted deviation from par is explained almost entirely by the entry component, while the post-origination component is only marginally negative. For loans originated at a discount, the entry component accounts for approximately 130 basis points of the 172 basis point deviation from par, while the post-origination component accounts for only 42 basis points. This is consistent with a portion of BDC portfolios being originated or acquired on terms that already imply a discount to face value, whether through original issue discount, fee structures, tighter economics embedded in cost, or positions that had already undergone some valuation adjustment by the time they appeared in the reported portfolio. The practical implication is that the headline discount levels may overstate the degree of deterioration occurring after origination. From a private credit perspective, this is important because investors often use the share of assets marked below par as a shorthand for portfolio stress. The evidence here suggests that such a shorthand can be misleading unless entry pricing is taken into account.
FIGURE 2 Drivers of Distance from Par by Entry Pricing Bucket
Note: Values represent principal-weighted average percentage point contributions to current distance from par. The Entry Component reflects basis established at acquisition, while the Post-Origination Component reflects subsequent fair-value movement relative to that basis. Components sum to Total Deviation from Par.
The near-par bucket behaves differently. Although the overall weighted deviation from par is modest, the post-origination component is larger than the entry component in absolute terms. That makes the near-par segment the part of the portfolio where valuation behavior appears most informative about subsequent credit quality developments. These are not deeply distressed assets, but neither are they static carry positions. Rather, they are the segment where fair-value marks carry the highest incremental information content. In other words, the near-par segment functions as the most informative transmission channel through which changes in credit conditions are reflected in reported marks. In a practical sense, this is likely the part of the BDC book where investors should focus if the goal is to identify emerging pressure rather than inherited pricing structure. From a private credit perspective, this is intuitive. Direct lending portfolios are typically originated close to par, with limited secondary price discovery. As a result, meaningful valuation movement tends to occur only when underlying risk assumptions change, rather than through continuous market repricing.
The premium bucket is small and should be treated with caution. In aggregate, premium-originated exposures show little net deviation from par, with positive entry effects broadly offset by negative post-origination movement. That pattern is directionally intuitive. Premiums embedded at entry can compress over time even in the absence of acute borrower stress, particularly as underwriting richness normalizes or as spread assumptions are revisited. But given the small size of this bucket in the sample, it is better viewed as supplementary context than as a conclusive result.
The migration analysis in Figure 3 reinforces these results. Loans originated at a discount exhibit limited movement across valuation states, with the majority remaining in the discount bucket and only limited reversion towards par. This persistence suggests that these positions are not simply fluctuating around par with each reporting cycle. Instead, they behave as a persistently discounted cohort. That in turn supports the interpretation from the decomposition analysis: the discount bucket is dominated by exposures whose valuation profile was largely established at entry, rather than by loans steadily repricing lower after origination. This persistence suggests that discounted positions contain limited incremental information about current credit conditions, reinforcing the distinction between structural pricing and active re-pricing.
FIGURE 3 Distribution of Principal Across Entry and Current Valuation Buckets from Origination to February 2026
Note: Figure 3 does not represent a traditional migration matrix. Rather, it shows the percentage of total portfolio principal associated with each combination of entry bucket and current valuation bucket. The table therefore illustrates where economic exposure is currently concentrated rather than transition probabilities.
Near-par loans show materially higher migration intensity. A meaningful proportion move into the discount bucket over time, while a smaller share migrate upwards into premium. This provides the clearest cross-sectional indication in the dataset of live valuation movement after origination. In other words, the loans that start near par are the ones most likely to reveal genuine changes in the portfolio’s credit temperature. From a private credit lens, that is exactly where one would expect re-pricing to occur. Most performing direct lending assets are underwritten close to par and remain there unless either fundamentals weaken, refinancing assumptions change, or required returns rise. The fact that migration is concentrated in this bucket suggests that fair-value marks around par contain more incremental information than deep original issue discounts do.
The data points to a bifurcated valuation structure within BDC portfolios. One part of the book consists of structurally discounted exposures whose current marks are largely explained by where they entered. Another consists of loans booked near par, where subsequent movement in fair value appears to do more of the explanatory work. This is a more useful framework than a simple distressed-versus-performing split because it distinguishes static discount from active re-pricing.
That distinction has direct relevance for how BDC marks are interpreted. If deeply discounted loans are primarily entry-driven and relatively stable, then their presence tells investors something important about underwriting mix and portfolio construction, but less about incremental credit deterioration in subsequent periods. By contrast, deterioration emerging from the near-par bucket is more likely to reflect developments after origination and therefore to carry more timely information about borrower credit conditions and portfolio health.
There are, however, two important cautions. First, cost is used here as a proxy for entry pricing, but it is not a perfect measure of original underwriting economics. In BDC reporting, cost can incorporate accounting adjustments, fee treatment, and in some cases valuation changes that occur relatively early in the life of the position. The entry component should therefore be interpreted as a reported acquisition-basis effect rather than a pure measure of original underwriting economics. Secondly, the analysis is cross-sectional. The migration exercise is informative about valuation state changes across the sample, but it does not by itself establish causality or precisely date when deterioration occurred.
Even with those caveats, the message from the empirical analysis is clear. The distribution of fair-value marks across BDC portfolios is not driven by a single, primarily credit risk-driven process. Deep discounts appear predominantly associated with basis established at entry, while valuation movement after origination is more visible in the near-par portion of the book. For investors, that means the deepest discount bucket may be less informative about emerging credit stress than movements occurring within the near-par segment.
Where post-origination deterioration actually emerges
Post-origination deterioration is evident in the data, but unevenly distributed and concentrated in segments where entry pricing provides little structural buffer. Figure 4 shows the distribution of the post-origination component across principal-weighted exposures in the discount and near-par entry buckets.
FIGURE 4 Distribution of Post-Origination Repricing by Entry Bucket from origination to February 2026
Note: The chart shows the distribution of principal across ranges of post-origination valuation movement. Values are weighted by principal amount and shown separately for loans entering the portfolio at a discount and near par.
The near-par cohort exhibits the largest contribution from the post-origination component and the highest degree of migration across valuation states. Approximately 15% of principal associated with near-par originated loans are currently classified within the discount bucket, with comparatively limited upward movement into premium. This asymmetry is consistent with incremental credit weakening rather than static pricing effects. In practice, loans originated near par have limited embedded cushion, so changes in borrower fundamentals, refinancing assumptions, or required returns are more readily reflected in fair-value marks. In effect, near-par exposures act as the primary conduit through which changing credit conditions are transmitted into reported valuations.
Importantly, the magnitude of post-origination adjustment remains modest relative to the entry-driven component observed in the discount bucket. This suggests that valuation changes are, at this stage, gradual rather than abrupt. Fair-value marks adjust incrementally over successive reporting periods, reflecting reassessments of expected performance and discount rates rather than discrete credit events.
Taken together, the evidence indicates that post-origination stress is most visible not in the entry discount cohort, but in the migration and dispersion of loans that entered near par. For investors, this implies that the most informative signals of changing credit conditions are likely to emerge from movements within this segment, rather than from the level of already discounted exposures.
What this means for investors
- Headline below-par metrics may overstate portfolio stress when entry basis is not considered.
- Approximately 75% of the average below-par mark on discount-originated loans is associated with basis established at portfolio entry rather than post-origination valuation deterioration.
- Near-par assets exhibit the greatest post-origination valuation movement and the highest migration into discount territory.
- Monitoring valuation migration around par may provide earlier signals of emerging stress than focusing solely on deeply discounted exposures.
Why investors may be looking at the wrong segment
The results point to a structural feature of private credit valuation: fair-value marks embed both initial pricing and subsequent reassessment of risk. Interpreting these marks therefore requires distinguishing between inherited pricing effects and post-origination re-pricing of risk.
Recorded entry basis plays a central role in shaping observed valuation outcomes. Loans may be recorded away from par due to OID, fees, or secondary execution, creating a persistent gap between cost and face value. These features create a divergence between accounting cost and contractual face value that persists over time. As a result, the level at which a loan is marked relative to par is not, in isolation, a reliable indicator of credit deterioration.
This is particularly relevant in private credit markets, where continuous price discovery is limited. Unlike broadly syndicated loans, where secondary trading provides frequent valuation signals, private credit assets are typically revalued periodically using model-based approaches. Changes in fair value therefore tend to occur through incremental adjustments to assumptions around discount rates, recovery expectations, or borrower performance, rather than through immediate market clearing prices.
The role of entry pricing also interacts with the credit cycle. In periods of strong capital inflows and competitive lending conditions, loans are more likely to be originated close to par or even at a premium. These vintages have less embedded cushion and are therefore more sensitive to subsequent changes in required returns or credit conditions. Conversely, assets originated with discounts or more conservative economics may exhibit greater stability in reported marks, not necessarily because underlying credit risk is lower, but because part of that risk is already reflected in the entry basis.
The near-par segment provides a useful reference point in this context. Because these exposures are less influenced by structural pricing effects, movements in their fair-value marks offer a clearer signal of changes in credit conditions. Stability within this cohort suggests that valuation dispersion elsewhere in the portfolio is more likely to reflect entry effects, while deterioration within it is more indicative of evolving borrower risk or shifts in market assumptions.
Taken together, these dynamics suggest that valuation behavior in private credit is best understood as a combination of static and dynamic components. Static effects arise from the pricing and structuring of loans at origination, while dynamic effects reflect the ongoing reassessment of credit risk. Separating these components avoids conflating underwriting structure with credit deterioration and provides a more accurate basis for interpreting portfolio risk.
Implications for private credit investors
The empirical results have direct implications for how investors interpret valuation signals, assess portfolio risk, and evaluate manager underwriting in private credit. The central insight is that fair-value marks are not a homogeneous indicator of credit conditions. Without adjusting for entry pricing, they risk conflating structural basis effects with genuine deterioration. For investors, this distinction is not merely analytical; it shapes how portfolios are monitored, compared, and ultimately allocated.
The primary implication is that headline below-par metrics may be an incomplete proxy for credit deterioration when viewed without reference to entry basis. This has direct consequences for allocator behavior. Strategies that originate at a discount may appear structurally weaker on a mark-to-market basis despite exhibiting stable credit performance, while near-par portfolios may understate latent risk. In practice, investors often view the proportion of assets marked below par as a shorthand for portfolio stress. The evidence here suggests that such a metric is, at best, incomplete. A meaningful share of discounted positions reflects entry economics rather than subsequent credit weakening. Interpreted naively, this can lead to an overstatement of deterioration and, by extension, a mischaracterization of portfolio resilience. A more informative approach is to distinguish between inherited discount and emergent discount, focusing on the post-origination component as the relevant signal of changing borrower conditions.
This reframing has consequences for fund relative manager assessment. Managers that originate or acquire loans at a discount may, all else equal, report a higher share of below-par assets without necessarily exhibiting weaker credit performance. Conversely, portfolios concentrated in near-par assets may appear healthier on a static basis, while in reality embedding greater sensitivity to future re-pricing. Comparing managers on the basis of current valuation levels alone therefore risks rewarding entry pricing discipline or penalizing it, depending on the lens applied, rather than capturing true differences in credit outcomes. Incorporating entry-adjusted measures allows for a cleaner comparison of underwriting quality and subsequent asset performance.
A second implication relates to where investors should focus their monitoring efforts. The results indicate that the most informative part of the portfolio is not the deeply OID tail, but the near-par at entry segment where post-origination movement is most active. These exposures are more likely to reflect incremental changes in credit quality, refinancing risk, or required returns. From a surveillance perspective, this suggests a shift away from static measures of distress towards tracking migration dynamics and valuation drift around par. Early signs of portfolio pressure are more likely to emerge through the gradual erosion of near-par positions than through further declines in already discounted assets.
This perspective also interacts with vintage risk and underwriting conditions. Loans originated in periods of tighter spreads or more aggressive structures are more likely to enter portfolios near par, leaving less embedded cushion against adverse developments. As a result, these vintages may exhibit greater post-origination sensitivity even if initial valuation levels appear benign (in public debt markets, these vintage effects are well documented). Conversely, assets originated with more conservative economics or acquired at a discount may display greater stability in reported marks, not necessarily because underlying credit risk is lower, but because part of that risk is already reflected in the entry basis. Investors evaluating vintage performance should therefore consider not only realized marks, but also the pricing context at origination.
A third implication concerns portfolio construction and diversification. The bifurcation observed in the data suggests that portfolios can contain a mix of structurally discounted exposures and near-par assets with higher re-pricing potential. These segments behave differently under changing credit conditions. Structurally discounted assets may provide a form of valuation stability, albeit with limited upside, while near-par exposures carry greater optionality but also greater sensitivity to deterioration. Understanding this composition is important for assessing how portfolios may evolve through the credit cycle, particularly in environments where refinancing risk and funding costs are shifting.
Finally, the findings have implications for how investors engage with valuation itself. BDC fair-value marks are often treated as point-in-time estimates of asset quality, yet the analysis highlights that they embed both historical and forward-looking information. The entry component reflects underwriting and acquisition conditions, while the post-origination component captures subsequent reassessment of risk. Interpreting these marks requires separating these layers. Investors who fail to do so risk drawing conclusions about credit conditions that are driven as much by past pricing decisions as by current borrower performance.
Taken together, the results argue for a more nuanced framework for analyzing private credit portfolios. Rather than relying on headline valuation metrics, investors should focus on the drivers of those valuations: how assets entered the portfolio, how they have moved since, and where within the distribution that movement is concentrated. In a market where transparency is limited and secondary pricing is sparse, such analysis provides a more robust basis for assessing portfolio health, underwriting discipline, and the evolution of credit risk over time.
Limitations of the approach
The approach adopted in this paper focuses on valuation behavior rather than borrower-level credit performance. As a result, several limitations should be acknowledged when interpreting the results.
First, the analysis relies on fair values reported by BDCs in regulatory filings. While these valuations are subject to internal governance processes and board oversight, they remain manager estimates rather than observable market prices1. As a result, reported fair values incorporate managerial judgment and may adjust gradually rather than reflecting immediate market repricing.
Second, the analysis is cross-sectional in nature and is based on the most recent available disclosures for each BDC. The entry-adjusted valuation framework therefore does not capture the full dynamics of valuation changes through time, nor does it directly measure the speed at which portfolio marks adjust in response to changing credit conditions.
Third, the dataset is intentionally restricted to a limited set of variables that are consistently available across BDC filings. While this constraint allows for transparent and replicable analysis, it also means that borrower-level fundamentals, capital structure details, and contractual features of individual loans are not incorporated into the analysis.
Finally, the decomposition used in this paper is not intended to infer realized losses or predict default outcomes. Principal-weighted aggregation may overweight larger, more stable exposures, potentially understating volatility in smaller or more opportunistic positions. Instead, it provides a descriptive framework for understanding how current valuation marks relate to entry pricing across BDC portfolios. As such, valuation movements should be interpreted as indicative signals of changing portfolio conditions rather than definitive measures of borrower-level credit performance.
Conclusion
This paper addresses a fundamental but often overlooked question: what do below-par marks in private credit portfolios actually represent? Using loan-level disclosures from BDCs, the analysis shows that valuation outcomes are not driven by a single, credit-sensitive process. A significant portion of discounted positions appears associated with basis established at portfolio entry rather than deterioration emerging after origination, while observable re-pricing is more concentrated among loans that entered portfolios close to par.
This distinction matters for how portfolio health is assessed. Headline measures of assets marked below par risk overstating the extent of credit weakening if they do not account for the basis at which investments were originated or acquired. Conversely, the near-par segment, often perceived as benign, appears to contain more of the incremental information about changing borrower conditions and emerging stress.
The evidence points to a more nuanced interpretation of fair-value marks. Rather than treating them as a uniform signal, they should be understood as a combination of inherited pricing structure and subsequent credit evolution. For investors, this implies a shift in focus: away from static valuation levels and towards the dynamics of how and where valuations are moving.
More broadly, the findings highlight the importance of context in private credit analysis. In a market where transparency is limited and pricing is not continuously discovered, decomposing valuation outcomes provides a clearer and more decision-relevant lens on underwriting discipline, portfolio construction, and the evolution of credit risk.
1Financial Accounting Standards Board (FASB) ASC 820 defines fair value as an estimate based on market participant assumptions, often requiring judgement where observable prices are unavailable.
Contacts
Hanna Sundqvist
Head of Private Credit, Europe
Asset Management
+44 203 314 2217
Hanna.Sundqvist@moodys.com
David Hamilton
Head of Asset Management Research
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David.Hamilton@moodys.com
About
This article is a product of Moody’s Asset Management Research team, part of Moody’s Analytics (“Moody’s”), a division of Moody’s Corp. separate from Moody’s Ratings. The analysis and viewpoints expressed herein are solely those of Moody’s Asset Management Research team.
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