Counterparty Risk Research Articles

Commercial real estate exposure and bank counterparty risk

Detailed analysis of December 2023 bank regulatory data suggests that unrealised interest rate losses in the banking system amplify banks' true commercial real estate (CRE) loan concentrations making CRE exposures much more consequential than traditional supervisory CRE loan concentration measures suggest. Taken together, weak demand for several types of commercial properties, sustained unexpectedly high interest rates and the concentration of CRE loans in many bank portfolios may magnify the risk of many financial institution's uncollateralised exposures to bank counterparties.

Pricing options on the maximum or the minimum of several assets with default risk

This paper presents analytical solutions for options on the maximum or the minimum of several assets with counterparty default risk before maturity, including derivations of several specific Greeks. To derive the solutions, we provide the joint distribution of the minimum value of one Brownian motion and the terminal values of all Brownian motions for correlated multidimensional Brownian motion. We then conduct a numerical analysis to examine the effects of counterparty risk on option prices.

The dynamic effects of debtor bankruptcy on unsecured creditors' stock liquidity

This paper explores the dynamic effects of counterparty risk on stock liquidity using data on unsecured creditors after a debtor has declared bankruptcy. Through matched pair fixed effect panel regressions, we find that liquidity for unsecured creditors reduces after such declarations but only in the short term. This is evidenced by increases in various spread measures and Kyle's (1985) lambda and decreases in the bid depth differentials between the stocks of the unsecured creditors and the matched firms. Additionally, we find the greater the credit exposure, the greater the decline in liquidity. In the long term, debtor bankruptcies appear to have no effect on spread measures. Rather, the market depth for unsecured creditor stocks improves.

Evaluation of counterparty credit risk under netting agreements

We investigate counterparty credit risk and credit valuation adjustments in portfolios including derivatives with early-exercise opportunities, under a netting agreement. We show that credit risk and netting agreements have a significant impact on the way portfolios are managed (that is, on options’ exercise strategies) and, therefore, on the value of the portfolio and on the price of counterparty risk. We derive the value of a netted portfolio as the solution of a zero-sum, finite horizon, discrete-time stochastic game. We show that this dynamic-game interpretation can be used to determine the value of the reglementary capital charges required of financial institutions to cover for counterparty credit risk and we propose a numerical valuation method. Numerical investigations show that currently used numerical approaches can grossly misestimate the value of credit valuation adjustments.

Dynamic margin optimization

In response to the Global Financial Crisis of 2007–2009, by now, most of the financial transactions must be cleared through central counterparties operating a dynamic margin setting mechanism. High margin calls can reduce counterparty risk in a turbulent market, but at the same time, increase liquidity risk and escalate systemic risk. In this paper, we construct a theoretical model to address this challenge, deriving an optimal margin setting policy framed as a stochastic control problem. Our analysis reveals that an adaptive, countercyclical approach is superior to a purely risk-sensitive strategy, primarily by minimizing the expected loss for the clearing institution.

On the pricing of vulnerable Parisian options

Parisian options, serving as substitutes for barrier options, are frequently embedded in complex financial derivatives. Despite the considerable mathematical challenges in pricing, their significant applications in finance and insurance have generated extensive studies in the literature. However, the impact of counterparty risk has not been taken into account so far. To address this gap, we develop a closed-form pricing framework for vulnerable Parisian options. Utilizing the Laplace transform and measure-change technique, we derive closed-form pricing formulas of Parisian options incorporating counterparty credit risk. Finally, we conduct numerical analyses to verify our pricing formulas’ accuracy and efficiency.

Discrepancy between regulations and practice in initial margin calculation

Counterparty risk remains an issue in over-the-counter derivative transactions following the 2008 financial crisis. While the margin for a derivative transaction can only be transferred until just before the counterparty’s default, the exposure of the derivative transaction can vary stochastically during the margin period of risk, that is, the period from the counterparty’s default to the actual closing-out of the transaction. Thus, the anticipated positive exposure may not be recognized, resulting in counterparty risk. Considering it is difficult to calculate the initial margin (IM) according to the regulations, IM has been calculated in practice using a simplified method proposed by the International Swaps and Derivatives Association (ISDA), which is called the ISDA Standard Initial Margin Model (“ISDA SIMM”). In this study, we derive an approximate formula for some counterparty risk indicators for a stochastic volatility model and illustrate numerical analyses for a call option in the SABR model as an example to examine the effect of the discrepancy between regulations and practices in margin calculation. Our results imply that the IM calculated in practice may be insufficient for counterparty risk management, particularly when the market is volatile.

Pricing vulnerable lookback options using Laplace transforms

This study develops a closed-form solution for pricing vulnerable lookback options, which combines the Black–Scholes model for the underlying asset and a correlated jump–diffusion model for the issuer’s asset to account for default risks. Our approach relies on applying Laplace transforms to establish a closed-form solution and compute them numerically using Laplace inversion algorithms. To determine the price, we derive the joint distribution of the first passage time of a drifted Brownian motion and the value of the correlated jump–diffusion. Through numerical examples, we demonstrate the accuracy of the numerical solutions obtained through our method and the stability of the algorithm. Subsequently, we conduct a numerical analysis to understand how counterparty risk influences option prices based on our formula.

Assessing the impact of renewable energy policies on decarbonization in developing countries

This study offers the first consistent attempt to identify how energy sector decarbonization policies have affected the energy mix over the last four decades across more than 100 developing countries. It applies systematic regression analysis to five energy sector decarbonization outcomes and 75+ policy instruments aggregated into seven policy packages. Combining instrumental variables with country interactions and country and time-fixed effects in regional panels helps address potential endogeneity issues. Only a handful of energy policy packages significantly affect decarbonizing developing countries' energy mix, and they more often achieve a negligible or opposite result than intended three years after implementation. Policies that address counterparty risk have the highest immediate effect. Effects of renewable policies on different decarbonization outcomes improve slightly five and seven years after their implementation.

Credit default swap pricing with counterparty risk in a reduced form model with Hawkes process

Credit default swap pricing with counterparty risk in a reduced form model with Hawkes process

Cross-exchange crypto risk: A high-frequency dynamic network perspective

Cross-exchange crypto trading presents inherent risks, particularly for centralized exchanges. Investors observe exacerbating crypto volatility and counterparty risk and would like to quantify these elements of crypto trades. The multiple exchanges require a multivariate view on the structures of risk spillover across exchanges. Here, a Multivariate Heterogeneous AutoRegression (MHAR) model is designed and analyzed, accommodating the stylized facts of crypto markets, including 24/7 trading and the long-memory effect on return variations. The proposed MHAR approach clearly reveals the intensity of interconnectedness among exchanges during extreme events, e.g., the Bitcoin market. Additionally, one observes extremely volatile eigenvector centralities of Futures Exchange Ltd (FTX), suggesting potential implications for its bankruptcy. Furthermore, portfolios that account for the dynamics of partial correlations or eigenvector centralities offer promising results in terms of risk measures.

Blockchain Enabled Smart Contracts for Digital Assets

The diverse applications and benefits of blockchain technology and smart contracts across various sectors are explored in this overview. Decentralized Finance (DeFi) projects, supply chain management, tokenization of assets, NFT platforms, and identity verification stand out as prominent examples. Smart contracts are lauded for their cost efficiency and security, underpinned by blockchain's cryptographic features that fortify system integrity. Blockchain's global accessibility facilitates cross-border transactions, while decentralized exchanges (DEX) mitigate censorship and counterparty risks, empowering users with asset control. Moreover, blockchain expands investment opportunities through asset tokenization, encompassing diverse classes such as real estate and intellectual property, bolstering security and transparency through immutable ownership records. Oracles play a vital role in integrating real-time data into DeFi ecosystems, informing decision-making by linking off-chain data with blockchain networks.Diverse token standards like ERC-20 and ERC-721 are pivotal, catering to fungible and non-fungible token ecosystems respectively. Lastly, the advantages of proof of stake (PoS) over proof of work (PoW) are highlighted, emphasizing PoS's energy efficiency, transaction throughput, and scalability

Counterparty risk and contagion in financial networks

ABSTRACT Based on the concept of multi-orbit contagion, we develop a network-based probabilistic model to illustrate the risk contagion among institutions and the stability of financial networks. Our examination focuses on two key aspects: the size of component, which the network divided into different components, and the number of institutional partners. Our study finds a non-monotonic relationship between the systemic risk and the connection density, and there needs a trade-off between the number of partners and the risk contagion to reduce systemic risk. Furthermore, our analysis of core-periphery structures provides an understanding of why the”too big to fail” phenomenon occurs. Our research contributes to systemic risk analysis and has significant theoretical implications for regulators.

Corporate Social Responsibility and Risk: Evidence from various countries

This study investigates the relationship between corporate social responsibility and default risk. The usage of a significant sample size of companies from 42 nations between 2006 and 2020, this investigation examines the connection between corporate social responsibility (CSR) and counterparty risk, concentrating on the discrepancy impact conditional on the intervals of time limits. We discover that corporate social responsibility is negatively related to the default probability, and the impact is more potent in the long run than in the short term. In addition, the effect of corporate social responsibility on company nonpayment probability seems to be more significant in international locations with weaker securities markets and legal institutions. This study is unique in the field of CSR and Default risk. Our results generally assist corporate social responsibility's position in filling institutional voids.

Loss Sharing in Central Clearinghouses: Winners and Losers

Abstract Central clearing counterparties (CCPs) were established to mitigate default losses resulting from counterparty risk in derivatives markets. In a parsimonious model, we show that clearing benefits are unevenly distributed across market participants. Loss sharing rules determine who wins or loses from clearing. Current rules disproportionately benefit market participants with flat portfolios. Instead, those with directional portfolios are relatively worse off, consistent with their reluctance to voluntarily use central clearing. Alternative loss sharing rules can address cross-sectional disparities in clearing benefits. However, we show that CCPs may favor current rules to maximize fee income, with externalities on clearing participation. (JEL G18, G23, G28, G12)

Blockchain technology and international countertrade

We illustrate the concept of using a Turing complete consortium blockchain (TCCB) to facilitate international countertrade. Physical goods and services would be linked to the blockchain by associating them with corresponding non-fungible tokens (NFTs). TCCBs could help small or new companies, particularly those in less developed countries, reduce the counterparty risk and transaction costs related to logistic chain management and contract arbitration. They could also supplement trade financing that often requires a mature banking system and developed financial market. We analyze the concept using a hypothetical example to illustrate the potential efficiencies over traditional countertrade transactions.

Analytical valuation of vulnerable chained options

In this paper, we present analytical pricing formulae for vulnerable chained options. To derive the price, we provide the joint probability that one of the two-dimensional Brownian motions hits multiple barriers sequentially before a fixed time and the positions of both Brownian motions. Using the derived formulae, we perform numerical analysis to investigate the impacts of counterparty risk on option prices.

Changes in repo markets and the necessity for CCPs in Korea

In 2022, US financial regulators proposed to mandate a single central clearing mechanism for treasury bonds and repo transactions to stabilize financial markets. The systemic risks inherent in repo markets were first highlighted by the global financial crisis and, as a response, global financial authorities such as the Financial Stability Board (FSB) and Bank for International Settlements (BIS) have advocated for the introduction of a central counterparty (CCP). This study examines the structural characteristics of Korean repo markets and proposes the introduction of CCPs as a way to mitigate systemic risk. To this end, the author analyzes the structural differences between US and European repo markets and estimates the potential consequences of introducing CCP clearing in local repo markets. In general, CCPs offer two benefits: they can reduce required capital through netting in multilateral transactions, and they can mitigate the effects of risk transfer by isolating counterparty risk during periods of turbulence. In Korea, the latter effect is expected to play a pivotal role in mitigating potential risks.

Effectiveness of Green Bonds in Selected CEE Countries: Analysis of Similarities

Green bonds are an increasingly important area not only in the financing of investments important to the environment, but recently also as an object of investment. From the investors point of view, the key aspect still remains the efficiency of the investment and its profitability. The subject of this research is to evaluate changes in the efficiency of green bonds issued in the selected CEE countries (Poland, Slovakia, Czech Republic, and Hungary), in the short and long term. Poland is the largest issuer of green bonds in this group, followed by the Czech Republic, Hungary, and Slovakia. Individual green bonds in these group of countries are characterized by varying levels of green bond yields, duration of the investment, issue size and counterparty risk. These factors greatly hinder their comparability, especially in terms of investment efficiency. This manuscript fits into this area, as the main purpose of the manuscript is to show similarities in the yields of green bonds issued in Poland and green bonds issued in CEE countries. The hypothesis that will be tested is that changes in the effectiveness of green bonds issued in Poland are strongly correlated with changes in the effectiveness of green bonds issued in CEE countries. The results of the research positively verified the hypothesis, and the objectives of the research were achieved. It was shown that green bonds issued in the Czech Republic and Slovakia demonstrate a high similarity in terms of effectiveness to green bonds issued in Poland. At the same time, the results confirmed that of all the bonds analysed, the one bond issued by the Hungarian government is the least related to green bonds issued in Poland in terms of effectiveness for investors. The study used multiresolution analysis and Dynamic Time Warping. The Dynamic Time Warping algorithm measures the similarity between two sequences that can change over time. The analysis was carried out over a wide temporal cross-section, analysing the similarity between the effectiveness in both the short and long term.

Intermediation and Voluntary Exposure to Counterparty Risk

Intermediation and Voluntary Exposure to Counterparty Risk