Credit Valuation Adjustment (CVA)

What Is Credit Valuation Adjustment (CVA)?

Credit Valuation Adjustment (CVA) is the price of risk of default for a derivative or portfolio of derivatives with a specific counterparty when offsetting collateral is considered.

In other words, it is the cost of hedging the unique counterparty credit risk of a derivative instrument or a portfolio of derivative instruments. The difference between the risk-free value and the genuine risk-adjusted value is used to compute CVA.

In most circumstances, it reduces the mark-to-market value of an asset or a liability by the amount of the CVA. Around 2007/2008, it was implemented as an addition to fair value accounting, coinciding with the onset of the credit crisis.

It debuted as a new requirement to measure the price of Counterparty Credit Risk (CCR) at a time when CCR and spreads attributable to such risks had reached previously unheard-of heights.

Because most major market participants now assess CVA in their accounting statements and include it in deal pricing, CV Adjustment has piqued the interest of derivative market participants and regulators alike.

The qualitative elements listed below determine the degree of sophistication in a reporting entity's credit adjustment valuation technique.

Estimation is difficult and often requires significant judgment, which is influenced by a variety of qualitative factors, such as:

• The materiality of the entity's derivative's carrying value to its financial statements.

• The number and type of contracts for derivatives in the portfolio of the entity.

• The extent to which derivative instruments are either deeply in or out of the money.

• The existence and terms of credit mitigation arrangements (e.g., collateral arrangements in place). 

• Availability of technology and its costs to model complex credit exposures.

• Suitable input data's cost and consistent availability to calculate an accurate credit adjustment.

• The creditworthiness of the entity and its counterparties.

History of Credit Valuation Adjustment

The concept of default and its severe financial consequences have a long history and are widely understood by investors.

Many examples exist, including sovereign bodies like Russia (1998) and Argentina (2001), as well as corporations like Long-Term Capital Management (1998), WorldCom Inc. (2002), and Lehman Brothers (2008).

Credit risk management evolved and developed due to these default situations and the resulting financial consequences.

Much of the research has been focused on identifying and quantifying credit risk, particularly Counterparty Credit Risk (CCR), which is the risk of loss if a counterparty fails to meet its contractual commitments due to default.

While Counterparty Credit Risk was conceptually recognized, it was standard industry practice for years to value OTC derivative products without considering CCR, owing to the incorrect perception that counterparty default was exceedingly unlikely.

It was not until the financial crisis of 2007/2008 that market players understood that no business was immune to default risk. They began to factor CCR and price into the cost of financial derivatives, particularly at the deal level.

The Basel Committee on Banking Criteria approved Basel III, a global agreement on capital and liquidity standards for financial firms, in 2010 due to the financial crisis.

The agreement covers a wide range of topics, and there was a section on capital laws related to Credit Value Adjustment buried deep inside the hundreds of pages of regulations. Previously, the capital was held to protect against current exposure to poorly rated counterparts.

However, the regulator noted the significant volatility in bank earnings caused by CVA for those who accounted for it during the crisis. As a result, the new rules required that additional capital be held to protect against mark-to-market losses on the CVA portfolio.

Challenges to Counterparty Credit Risk

A derivative instrument is an agreement between two parties in which one or more underlying variables are used to determine the price. Depending on the nature of the instrument's payment, derivatives are classed as unilateral derivatives or bilateral derivatives.

A unilateral derivative instrument holder's exposure to any loss would occur if the Counterparty defaulted, such as an investor in a purchased option position.

The investor's loss would be calculated as the instrument's fair value (less any recoveries) at the moment of default. The investor's loss would be calculated as the fair value of the tool (less any recoveries) at the moment of default.

Whether or not the investor defaults, the Counterparty's duty and liability deriving from selling the option to the investor remains the same.

Even if the investor defaulted or filed for bankruptcy, any money payable to the investor's estate would be owed to the investor's estate.

Bilateral products, like interest rate swaps and foreign exchange forward contracts, are more complicated than unilateral instruments because both the investor and the Counterparty are exposed to each other.

For example, in a swap, one Counterparty is long the receiving leg and short the paying leg, while the other is short the receiving leg and long the paying leg.

The swap's value is the net worth of the two legs, and the recovery is based on the swap's net market value in the case of default.

The problem with bilateral instruments is that they can be in either an asset or liability position at any given valuation measurement date or have no value at all. As a result, each Counterparty is at risk of being exposed to the other.

Counterparty A, which is currently in a positive asset position, is exposed to Counterparty B since, in the event of default, Counterparty B owes it the positive market value of the swap.

On the other hand, Counterparty B has prospective credit exposure to Counterparty A, even if it is in an out-of-the-money negative liability position. The identical swap could convert to an asset position over time.

Even though a swap has no net value, counterparties are exposed to one another since the derivative can switch from an asset to liability at any time.

The underlying International Swap Dealers Association (ISDA) master agreement's netting and offset provisions (typically, an entity should enter into an ISDA master agreement with a bank or dealer before making transactions with derivative instruments).

It also enables offsetting critical or liability positions against positive or asset positions with a specific counterparty in the event of default, which can help mitigate counterparty credit exposure or default risk.

An ISDA Credit Support Annex (CSA) may also exist, which allows the posting of collateral to cover all or part of the position's net market value to reduce exposure.

CVA Valuation Method

While CVA valuation procedures have progressed, they are still not standardized and may differ between market players, ranging from relatively simple to highly complicated methodologies, determined mainly by the complexity and resources available to the market participant.

The CVA can be significant depending on the market participant, especially for large financial institutions that are heavily involved in derivative markets. 

Organizations begin by quantifying and measuring net counterparty credit exposures to determine CVA (typically using specialized software).

The next stage is to price the credit risk of such exposures using the derivative instrument's or portfolio's contractual terms and conditions and the Basics of Credit Value Adjustments and Implications for Hedge Effectiveness Assessment.

Interest rates, foreign currency rates, credit default swap (CDS) spreads, and other pertinent variables are all market inputs. In addition, the company's sophistication, technical competence, and resource limits all play a role in deciding which CVA valuation approach to use.

Method 1

Steps to follow are:

• Calculate the current mark-to-market value of the derivative and repeat the calculation in a discounted cash flow framework. 

• Adjust the discount rates by the Counterparty's credit spread when the exposure is to the Counterparty (i.e., the derivative is in the money or an asset) or one's credit spread if the Counterparty is exposed to the entity is the most straightforward approach (i.e., the derivative is out-of-the-money or a liability). 

• The CVA amount is the difference between the two resulting present values.

Method 2

To estimate the contingent replacement value of the derivative using the Counterparty's respective credit spread, a more robust technique uses a swaption-type valuation approach.

This method necessitates a deeper understanding of derivative valuations and access to specialized market data, such as interest rate volatility surfaces. Steps to follow are:

• Simulation modeling of market risk factors and risk factor scenarios, followed by a revaluation of each derivative utilizing, for example, thousands of simulation scenarios in hundred-time increments, are more advanced methodologies.

• The resulting matrix of simulations is then aggregated to provide an expected exposure profile for each netting counterparty based on scenario and time steps.  

• Adjusting each Counterparty's expected exposure profile to account for the receiving and posting of collateral, when applicable, yields a collateralized expected exposure profile.

• Although some market participants solely consider CVA when it comes to their counterparty exposures (i.e., exposures that are at risk if counterparties default), a majority compute an offsetting Debt Valuation Adjustment (DVA).

• The bilateral CVA is calculated by netting the CVA and DVA.

Common challenges in determining CVA

CVA is frequently hampered by system limits that are connected to business requirements. For example, large financial institutions with significant derivative portfolios use a specialized CV Adjustment trading desk to manage them actively.

These entities usually have advanced technologies and analytics, as well as the supporting infrastructure required to run simulations, compute predicted exposure, and track and maintain net collateral by a counterparty netted against the expected exposures.

Companies with a small number of derivatives may find it difficult to justify the exact high cost of technology, infrastructure, and people and, instead, choose less expensive and resource-intensive alternatives such as spreadsheet models or third-party web-based solutions.

Spreadsheet-based solutions for computing CV Adjustment are generally the least preferred option because they are bulky and prone to human input errors. In addition, they usually still require some analytical talent to develop the solution's assumptions. 

For many organizations, though, this may be the only viable alternative.

Obtaining the requisite market data for the computation and, in particular, the predicted exposure is a common difficulty for all companies computing CVA (albeit to varying degrees). 

Discount curves, credit spread curves, and volatility surfaces are all needed to determine exposure at a high level.

The difficulty arises because market data is frequently unavailable, even for large financial institutions, necessitating some judgment in determining proxy data for CV Adjustment computation.

If name-specific or proxy CDS spreads are available, they are often employed for credit spreads. However, when CDS spreads are not readily available, credit spread proxy measures such as new debt issuance spreads are routinely utilized.

When deciding which proxy measures to use, a lot of judgment is required, especially if there are no recent acceptable name-specific debt issuances to reference and/or one has to look at debt issuance spreads for peers.

Traditional data sources such as newspapers and the internet are insufficient. In addition, they do not provide adequate historical data, so third-party market data service providers are generally required to supply both current and past market data needed for the assessment study.

Credit Valuation Adjustment Vs. Hedge Accounting

The hedge accounting model, according to IFRS 9, is a valuation model that requires the value of the hedged item and hedging instrument to be quantified independently for both fair value and cash flow hedges.

The (in)effectiveness of a hedge is then determined by comparing the changes in the value of the hedging instrument and the hedged item, which must take credit risk into account.

Even when a hypothetical derivative is utilized, the model does not allow for complete hedge effectiveness to be assumed because this could hide variations in the credit risk or liquidity of the hedging instrument and the hedged item.

Therefore, when examining the effectiveness of hedge relationships and quantifying ineffectiveness, this credit risk and CV Adjustment principles also apply to the valuation of OTC derivatives.

In a Fair Value hedge, the valuation of the derivative hedging instrument should incorporate the applicable CV Adjustment when comparing the change in the fair value of the hedged item (such as a fixed rate bond) to the difference in the fair value of the hedged item (such as a fixed rate bond).

Similarly, the impact of CV Adjustment should be included in the data points that reflect the derivative hedging instrument when employing a statistical technique such as Regression Analysis to assess effectiveness.

Although there are changes in applicability between International and US standards, this theory applies to all forms of hedge relationships, including Fair Value hedges, Cash Flow hedges, and Net Investment hedges.

Credit risk may be omitted from the valuation of derivatives for measuring effectiveness only under US standards where conditions relating to the chance of default of either the company or the Counterparty are met.

It also follows that the method or approach chosen by an entity to incorporate CV adjustment in the valuation of OTC derivatives should serve as the foundation for the form or approach used to value hedging derivatives to assess and measure hedge accounting effectiveness.

As a result, when the tools for analyzing efficacy are more sophisticated, such as regression-based procedures, the issues connected with CV Adjustment tend to multiply.

For firms with a sizeable derivative portfolio and heavy use of hedge accounting, the necessity for sufficient and appropriate skills and resources becomes even more crucial.

Conclusion

Existing trading systems will likely prove to be a poor starting point for providing credible CVA measurement, as they process only a subset of all trades with a counterparty and cannot model netting and collateral agreements.

They can also not generate risk-neutral scenarios at the required performance levels across all risk factors.

Furthermore, most present systems lack the performance and analytical capabilities needed to determine sensitivities (Greeks) necessary for CVA management.

Finding the correct mix between risk-taking and active hedging is crucial to running a successful CV Adjustment desk.

Even though it is a requirement under international and US accounting standards, capturing the dollar worth of credit in the fair value of a derivative instrument or portfolio makes sense. However, it is both an art and a science to accomplish this.

To ensure that CVA has been assessed and applied effectively, regardless of the methodology used to compute it, a certain amount of expertise and management judgment is essential.

This is true not only for general derivative valuation but also for evaluating and measuring the efficacy of hedge relationships subject to hedge accounting.

When deciding on a methodology, an institution must thoroughly evaluate the availability of expertise and resources and the potential financial implications of such a change.

And while CV Adjustment must be somewhat hedged to avoid significant profit and loss (P&L) swings, this hedging is far from ideal, and the remaining risks must be fully recognized.

Also, given the complexities and amount of judgment required, it is essential to discuss CV Adjustment with financial advisors, accountants, systems providers, auditors, and experts in the industry who are familiar with market practices to identify the best route to take.

The most successful teams in the future will be those that can balance this into a successful relationship that supports a firm's clients and helps lead resource allocation, whether capital, balance sheet or liquidity, to the bank's most important clients.

Researched and Authored by Sara Malwiya  | LinkedIn

Reviewed and Edited by Aditya Salunke | LinkedIn

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