Debt Valuation Adjustment Research Articles

Banks’ Discretion Over the Debt Valuation Adjustment for Own Credit Risk

During our 2007 to 2015 sample period, firms recorded unrealized gains and losses on fair-valued liabilities attributable to changes in the firms’ own credit risk, referred to as the debt valuation adjustment (DVA), in earnings. Various parties criticized the inclusion of DVA in earnings as counterintuitive and manipulable. Using a small but comprehensive sample of European banks reporting nonzero DVA during this period, we decompose banks’ DVA into a normal portion explained by economic factors (e.g., changes in bond yield spreads) and an abnormal portion (the residual). Controlling for abnormal loan loss provisions (LLP) and realized securities gains and losses (RGL), we find that banks’ abnormal DVA is negatively associated with their premanaged earnings, consistent with banks exercising discretion over DVA to smooth earnings. We further find that banks that record larger LLP or RGL or that have histories of using LLP or RGL to smooth earnings are less likely to exercise discretion over DVA. These findings obtain in the financial crisis but not afterward. Collectively, our findings suggest that banks exercised discretion over DVA substitutably with discretion over LLP and RGL during the crisis. With the caveat that our analysis is limited by a small sample and the inherent difficulties of DVA decomposition, our findings have implications for how bank regulators and investors should interpret banks’ reported DVA, particularly in stress periods such as the crisis, and they provide support for the International Accounting Standards Board and Financial Accounting Standards Board’s (FASB) decisions to require firms to record DVA in other comprehensive income starting in 2018.

Binary funding impacts in derivative valuation

AbstractWe discuss the binary nature of funding impact in derivative valuation. Under some conditions, funding is either a cost or a benefit, that is, one of the lending/borrowing rates does not play a role in pricing derivatives. When derivatives are priced, considering different lending/borrowing rates leads to semilinear backward stochastic differential equations (BSDEs) and partial differential equation (PDEs), and thus it is necessary to solve the equations numerically. However, once it can be guaranteed that only one of the rates affects pricing, linear equations can be recovered, and analytical formulae can be derived. Moreover, as a by‐product, our results explain how debt value adjustment (DVA) and funding benefits are dissimilar. It is often believed that considering both DVA and funding benefits results in a double‐counting issue but it will be shown that the two components are affected by different mathematical structures of derivative transactions. We find that funding benefit is related to the decreasing property of the payoff function, but this relationship decreases as the funding choices of underlying assets are transferred to repo markets.

Failing Faithful Representations of Financial Statements: Issues in Reporting Financial Instruments

Both the International Financial Reporting Standards (IFRS) and the codified accounting standards (ASC) for the US GAAP categorize hedging relationships as falling into several buckets. The two buckets of relevance in this paper are (i) hedging the volatility of fair values, and (ii) hedging the volatility of future cash flow. In this paper, I argue that at least three accounting treatments of derivatives and hedging lead to creating serious distortion of reporting actual transactions, to combining hard and plastic valuations, and to violating adherence to the principle of ‘faithful representation’. The three accounting treatments are as follows: (1) creating the fictional Hypothetical Derivatives Method; (2) allowing for the establishment of purely discretionary valuation adjustments for all over‐the‐counter derivative assets (Credit Valuation Adjustment) and liabilities (Debt Valuation Adjustment) without any guides or constraints; (3) requiring subjective metaphysical separation of embedded derivatives with the main guide being the management's own perception of the instrument's embodiment of unrelated value and risk generators. To remedy the resulting distortion in financial reporting, significant revisions of certain accounting standards are sorely needed.

The FASB and IASB Achilles Heel: Unfaithful Representations of Financial Instruments

Available at SSRN: https://ssrn.com/abstract=3357733 Both the International Financial Reporting Standards (IFRSs) and the codified accounting standards (ASC) for the US GAAP categorize hedging relationships as falling into several buckets. The two buckets of relevance in this paper are (a) hedging the volatility of fair values, and (b) hedging the volatility of future cash flow. In this paper, I argue that at least three accounting treatments of derivatives and hedging lead to creating serious distortion of reporting actual transactions, to combining hard and plastic valuations, and to violating adherence to the principle of “faithful representation.” The three accounting treatments are as follows: (1) Creating the fictional Hypothetical Derivatives Method. (2) Allowing for the establishment of purely discretionary valuation adjustments for all of OTC derivative assets (Credit Valuation Adjustment) and liabilities (Debt Valuation Adjustment) without any guides or constraints. (3) Requiring subjective metaphysical separation of embedded derivatives with the main guide being the management’s own perception of the instrument’s embodiment of unrelated value and risk generators. To remedy the resulting distortion in financial reporting, significant revisions of certain accounting standards are sorely needed.

The implication of unrecognized asset value on the relation between market valuation and debt valuation adjustment

Under SFAS No. 159, U.S. firms can measure debt liabilities at fair value, which results in recognition of unrealized gains and losses from debt valuation adjustments (DVA) when a firm’s own credit risk changes. Critics have raised concerns about the counterintuitive income consequences of DVA; that is, when a firm’s credit risk increases (i.e., bad news), debt values decrease, and resulting DVA gains increase the firm’s income (i.e., good news), and vice versa. In this paper, we examine the relation between market valuation and DVA gains and losses, conditioning on the level of unrecognized asset value (UAV). We develop a model to demonstrate the mitigating effect of UAV on the relation between equity returns and DVA. We show that, while the association between equity returns and DVA is positive when the level of UAV is low, the association decreases and eventually turns negative with increasing levels of UAV.

Internal Valuation of Assets with Liquidity Risk

FVA, funding valuation adjustment, is a new and controversial adjustment to the value of a firm’s derivatives position, joining CVA (credit valuation adjustment) and DVA (debt valuation adjustment), both of which attempt to account for the effects of counterparty credit risk on the value of a contract on a firm’s books. FVA adjusts for the fact that an investor who holds a security but finances it in the money market will have to pay a premium over the riskless rate in order to do so. This premium reduces the investment value of the position by an amount that is supposed to be captured by the FVA. The problem that Nauta raises is that this treatment does not distinguish between a security that is traded in a liquid market and can be sold for its fair value at any time, meaning overnight funding is OK, versus an illiquid security that must be financed through maturity. The article shows how this key difference translates into a liquidity-based FVA and an optimal funding horizon for less than perfectly liquid assets. <b>TOPICS:</b>Counterparty risk, quantitative methods, credit risk management

Bankss Discretion Over the Debt Valuation Adjustment for Own Credit Risk

Prior to 2018, accounting rules required banks that recognize financial liabilities at fair value to record unrealized gains and losses on the liabilities attributable to changes in the banks’ own credit risk, referred to as the debt valuation adjustment (DVA), in earnings each period. Using a comprehensive sample of publicly traded European banks during 2007–2015, we investigate the economic determinants of DVA and banks’ exercise of discretion over DVA. We find that DVA exhibits the expected associations with economic factors, e.g., is positively associated with the change in banks’ bond yield spread. We decompose DVA into normal and abnormal components and find that abnormal DVA is negatively associated with pre-managed earnings, controlling for banks’ abnormal loan loss provisions and realized securities gains and losses, consistent with banks exercising discretion over DVA to smooth earnings. We further find that banks that record larger loan loss provisions or realized gains and losses and banks that have histories of using provisions or realized gains and losses to smooth earnings are less likely to exercise discretion over DVA to smooth earnings. These findings generally are consistent with banks using loan loss provisions, realized gains and losses, and DVA substitutably to smooth earnings. Lastly, we provide evidence that banks exercised discretion over DVA to smooth earnings during the recent financial crisis but not afterward. These findings have implications for how bank regulators and investors should interpret banks’ reported DVA, and they support the decisions by the IASB and FASB to require firms to record DVA in other comprehensive income starting in 2018.

A Gentle Introduction to Default Risk and Counterparty Credit Modelling

In this paper we introduce the reader to the basic tools for the computation of Counterparty Credit Risk such as Credit Value Adjustment and Debt Value Adjustment. We also present the effect of mitigating clauses, like netting and collateral, in reducing the credit exposure. Detailed numerical examples are presented with reference to commodity derivatives.

Closing Out the DVA Debate

When considering counterparty credit risk, it has become increasingly common in recent years for institutions to consider bilateral CVA which includes debt value adjustment (DVA) linked to their own default probability. However, the use of DVA is contentious as it is not obvious that an institution can monetise this “profit” prior to actually defaulting. Furthermore, the use of DVA also seems to require an understanding of the dependence between the default probability of the institution and their counterparty and introduces ambiguity over the correct choice of “closeout” assumptions. In this article, we analyse the complex interaction between CVA, DVA and closeout assumptions and consider if the relatively simple formulas used for bilateral CVA in the industry are reasonable.

Conic CVA and DVA

Conic pricing (or bid and ask pricing) of credit risk shows how counterparty credit risk when conservatively valued at the bid price results in larger CVA than would occur under risk neutral pricing. On the other hand when it comes to the debt valuation adjustment, since it is a liability, it must be priced at the ask. This mitigates and can even eliminate the DVA.

LIQUIDITY RISK, INSTEAD OF FUNDING COSTS, LEADS TO A VALUATION ADJUSTMENT FOR DERIVATIVES AND OTHER ASSETS

Traditionally derivatives have been valued in isolation. The balance sheet of which a derivative position is part, was not included in the valuation. Recently however, aspects of the valuation have been revised to incorporate certain elements of the balance sheet. Examples are the debt valuation adjustment which incorporates default risk of the bank holding the derivative, and the funding valuation adjustment that some authors have proposed to include the cost of funding into the valuation. This paper investigates the valuation of derivatives as part of a balance sheet. In particular, the paper considers funding costs, default risk and liquidity risk. A valuation framework is developed under the elastic funding assumption. This assumption states that funding costs reflect the quality of the assets, and any change in asset composition is immediately reflected in the funding costs. The result is that funding costs should not affect the value of derivatives. Furthermore, a new model for pricing liquidity risk is described. The paper highlights that the liquidity spread, used for discounting cashflows of illiquid assets, should be expressed in terms of the liquidation value (LV) of the asset, and the probability that the institution holding the asset needs to liquidate its assets.

Bilateral counterparty risk valuation adjustment with wrong way risk on collateralized commodity counterparty

Basel III requires banks to include a credit value adjustment (CVA) into capital charges. Both CVA and debt value adjustment (DVA) must be included for derivatives using mark-to-market accounting. An effective method to calculate bilateral-CVA (BR-CVA) by incorporating wrong-way risk (WWR) for a collateralized counterparty is proposed which handles WWR — defined as when counterparty credit exposure increases as default probability increases — by building a trivariate Gaussian copula between the aggregate market risk exposure factor and default quality of the financial institution and counterparty. This paper extends the ordered-scenario copula model proposed in the literature. It links BR-CVA pricing and WWR, which is close to the current regulatory requirement and useful for managing a financial institution's risk. A practical example is provided. Numerical results suggest that the proposed method is efficient and robust and can easily stress test the impact of WWR in BR-CVA pricing.

Counterparty Risk: A Review

This review provides formal definitions of the terms credit value adjustment (CVA) and debt value adjustment (DVA). Estimating these quantities requires modeling the probabilities of default and the loss given default, recognizing the dependence structure among all these inputs. In practice, marginal distributions are used and a copula function assumed. Although it has long been known that different copula functions can produce very different price estimates, keeping marginal distributions constant, there is little empirical evidence about the appropriate form of function to use for modeling default dependence. This review discusses the use of collateral for risk mitigation and its effects on CVA. Regulators have argued that standardized contracts should be cleared through central counterparties (CCPs). However, there are arguments against CCPs.

Understanding CVA, DVA, and FVA: Examples of Interest Rate Swap Valuation

Financial statements of major money-center commercial banks increasingly include reference to a credit valuation adjustment (CVA), debit (or debt) valuation adjustment (DVA), and funding valuation adjustment (FVA). This article explains the concepts behind CVA, DVA, and FVA using examples of interest rate swap valuation. A binomial forward rate tree model is used to get the value of the swap assuming no default. The CVA (the credit risk of the counterparty) and the DVA (the credit risk of the entity itself) depend on assumptions about the probability of default, the recovery rate and the expected exposure, which depends of projected values and settlement payments for the swap. The FVA arises when an uncollateralized swap is hedged with a collateralized or centrally cleared contract. In this version of the paper, two methods to calculate FVA are shown, both using the same assumptions about the credit risk parameters for the bank.

The Implication of Unrecognized Intangible Assets on the Relation between Market Valuation and Debt Valuation Adjustment

U.S. firms have the option to measure debt liabilities at fair value, which results in unrealized gains and losses from debt valuation adjustments (DVA) when a firm’s own credit risk changes. Critics raise concern on the counterintuitive net income consequence of DVA, namely, when a firm’s credit risk increases (i.e., bad news), debt values decrease and resulting DVA gains increase the firm’s net income (i.e., good news). Prior research posits that the perplexing net income effect of DVA is attributable to incomplete fair value accounting for contemporaneous assets such as unrecognized intangible assets (UIA). Specifically, DVA gains or losses are not properly offset by opposite fair value adjustments of UIA in net income. In this paper, we examine market valuation reactions to DVA gains and losses, conditioning on the level of UIA. We first develop a model to demonstrate the mitigating effect of UIA on the relation between equity returns and DVA. Using a sample of U.S. bank holding companies during 2007–2013, we show that while the association between equity returns and DVA is positive when the level of UIA is low, the association decreases and turns from positive to negative with increased levels of UIA. Our findings suggest that the market appears to understand the offsetting relation between DVA and changes in UIA fair values resulting from a firm’s own credit risk change.

COUNTERPARTY RISK AND FUNDING: THE FOUR WINGS OF THE TVA

The credit crisis and the ongoing European sovereign debt crisis have highlighted the native form of credit risk, namely the counterparty risk. The related credit valuation adjustment (CVA), debt valuation adjustment (DVA), liquidity valuation adjustment (LVA) and replacement cost (RC) issues, jointly referred to in this paper as total valuation adjustment (TVA), have been thoroughly investigated in the theoretical papers [8, 9]. The present work provides an executive summary and numerical companion to these papers, through which the TVA pricing problem can be reduced to Markovian pre-default TVA BSDEs. The first step consists in the counterparty clean valuation of a portfolio of contracts, which is the valuation in a hypothetical situation where the two parties would be risk-free and funded at a risk-free rate. In the second step, the TVA is obtained as the value of an option on the counterparty clean value process called contingent credit default swap (CCDS). Numerical results are presented for interest rate swaps in the Vasicek, as well as in the inverse Gaussian Hull-White short rate model, which allows also to assess the related model risk issue.

Counterparty Credit Risk in a Multivariate Structural Model with Jumps

We present a multivariate version of a structural default model with jumps and use it in order to quantify the bilateral credit value adjustment and the bilateral debt value adjustment for equity contracts, such as forwards, in a Merton-type default setting. In particular, we explore the impact of changing correlation between names on these adjustments and study the effect of wrong-way and right-way risk.

The Impact of Funding Costs and Liquidity Risk on the Valuation of Derivatives and Banking Book Products

Traditionally derivatives and other assets have been valued in isolation. The balance sheet of which a derivative position is part, was not included in the valuation. Recently, aspects of the valuation have been revised to incorporate certain elements of the balance sheet in the valuation. Examples are the debt valuation adjustment which incorporates default risk of the bank holding the derivative, and the funding valuation adjustment that some authors have proposed to include the cost of funding into the valuation. This paper investigates the valuation of derivatives and other assets as part of a balance sheet. In particular, funding costs, default risk and liquidity risk are considered. A valuation framework is developed under the elastic funding assumption. This assumption states that funding costs reflect the quality of the assets, and any change in asset composition is immediately reflected in the funding costs. The paper generalizes the result of Nauta 2012 that funding costs do not have an impact on the value of derivatives to cases including default risk. Furthermore a new model for the valuation of liquidity risk is developed. The result is that the liquidity spread, that is used for discounting cashflows of illiquid assets, can be expressed in terms of liquidation value of the asset, and the probability that the institution holding the asset needs to liquidate (part of its) assets. The resulting model is similar to existing models that include fixed funding costs, such as Burgard Kjaer 2011, with the difference that the funding spread is replaced by the liquidity spread. This has some important consequences, since the liquidity spread depends on the product and e.g. the size of the position, whereas the funding spread does not. Examples for banking book products and OTC call options are included to illustrate the framework.