scholarly journals Calculation of Credit Valuation Adjustment Based on Least Square Monte Carlo Methods

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Qian Liu
Keyword(s):  
Monte Carlo ◽  
Credit Risk ◽  
Financial Markets ◽  
Financial Institutions ◽  
Least Square ◽  
Copula Functions ◽  
Default Intensity ◽  
Interest Rate Swaps ◽  
Counterparty Credit Risk ◽  
Credit Valuation Adjustment

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced mathematically. We examine this issue using interest rate swaps. This largely traded financial product allows us to well identify the risk profiles of both institutions and their counterparties. Concretely, Hull-White model for rate and mean-reverting model for default intensity have proven to be in correspondence with the reality and to be well suited for financial institutions. Besides, we find that least square Monte Carlo method is quite efficient in the calculation of credit valuation adjustment (CVA, for short) as it avoids the redundant step to generate inner scenarios. As a result, it accelerates the convergence speed of the CVA estimators. In the second part, we propose a new method to calculate bilateral CVA to avoid double counting in the existing bibliographies, where several copula functions are adopted to describe the dependence of two first to default times.

Die Stabilität von Finanzmärkten:Wie kann die Wirtschaftspolitik Vertrauen schaffen?

2006 ◽  
Vol 55 (1) ◽  
Author(s):  
Theresia Theurl ◽  
Jan Pieter Krahnen ◽  
Thomas P. Gehrig
Keyword(s):  
Credit Risk ◽  
Financial Markets ◽  
Financial Market ◽  
Financial Institutions ◽  
Banking Sector ◽  
Public Awareness ◽  
Credit Derivatives ◽  
Point Of View ◽  
Regulatory Oversight ◽  
The Creation

AbstractFrom Theresia Theurl’s point of view financial markets exhibit certain features that turn them inherently unstable. Therefore, economic policy measures were necessary and advisable, but they should not take the shape of isolated and selected interventions. Rather, these measures of financial market supervision and regulation had to be integrated into a comprehensive concept of micro- and macroeconomic policy in order to allow the creation of stabilizing trust.In his contribution, Jan Pieter Krahnen maintains, that the systemic risk of banks and financial institutions has changed and risen in recent years. According to his view, this is due to a more widespread use of credit derivatives. Although they may cause a more efficient distribution of credit risk in the banking sector, at the same time they could mean a higher vulnerability of the banking sector to system-wide contagion effects of credit risk. As such, financial market supervision as well as the Basel II rules on Capital Standards should take into account not only the credit risk exposure of individual financial institutions, but also correlation measures of their share prices.For Thomas Gehrig, empirical anomalies demonstrate the relevance of awareness and trust in financial markets. This note would argue in favor of social policies that enhance public awareness in financial markets as a basis for trust. And so naturally, these policies need to be complemented by a strong financial order that aims at minimizing behavioral risks. He says, trust requires a regulatory framework that reduces manipulation by private as well as public interests. A competitive order complemented by strong regulatory oversight may go a long way towards generating liquid financial markets and the creation of trust. Trust by individuals, however, would be most strongly encouraged when individuals are entrusted in managing their own financial market activities including their own pension arrangements.

scholarly journals The Impact of Default Dependency and Collateralization on Asset Pricing and Credit Risk Modeling

2019 ◽  
Author(s):  
Tim Xiao
Keyword(s):  
Asset Pricing ◽  
Credit Risk ◽  
Financial Markets ◽  
Default Risk ◽  
Risk Modeling ◽  
Financial Instruments ◽  
Otc Derivatives ◽  
Counterparty Credit Risk ◽  
Comprehensive Framework ◽  
The Impact

This article presents a comprehensive framework for valuing financial instruments subject to credit risk. In particular, we focus on the impact of default dependence on asset pricing, as correlated default risk is one of the most pervasive threats in financial markets. We analyze how swap rates are affected by bilateral counterparty credit risk, and how CDS spreads depend on the trilateral credit risk of the buyer, seller, and reference entity in a contract. Moreover, we study the effect of collateralization on valuation, since the majority of OTC derivatives are collateralized. The model shows that a fully collateralized swap is risk-free, whereas a fully collateralized CDS is not equivalent to a risk-free one.

scholarly journals An Accurate Solution for Credit Valuation Adjustment (CVA) and Wrong Way Risk

2019 ◽  
Author(s):  
Tim Xiao
Keyword(s):  
Monte Carlo ◽  
Probability Distribution ◽  
Accurate Solution ◽  
Least Square ◽  
Backward Induction ◽  
Order Of Accuracy ◽  
Monte Carlo Approach ◽  
Default Time ◽  
Credit Valuation Adjustment ◽  
High Order Of Accuracy

This paper presents a Least Square Monte Carlo approach for accurately calculating credit value adjustment (CVA). In contrast to previous studies, the model relies on the probability distribution of a default time/jump rather than the default time itself, as the default time is usually inaccessible. As such, the model can achieve a high order of accuracy with a relatively easy implementation. We find that the valuation of a defaultable derivative is normally determined via backward induction when their payoffs could be positive or negative. Moreover, the model can naturally capture wrong or right way risk.

scholarly journals An Accurate Solution for Credit Valuation Adjustment (CVA) and Wrong Way Risk

2019 ◽  
Author(s):  
Tim Xiao
Keyword(s):  
Monte Carlo ◽  
Probability Distribution ◽  
Accurate Solution ◽  
Least Square ◽  
Backward Induction ◽  
Order Of Accuracy ◽  
Monte Carlo Approach ◽  
Default Time ◽  
Credit Valuation Adjustment ◽  
High Order Of Accuracy

This paper presents a Least Square Monte Carlo approach for accurately calculating credit value adjustment (CVA). In contrast to previous studies, the model relies on the probability distribution of a default time/jump rather than the default time itself, as the default time is usually inaccessible. As such, the model can achieve a high order of accuracy with a relatively easy implementation. We find that the valuation of a defaultable derivative is normally determined via backward induction when their payoffs could be positive or negative. Moreover, the model can naturally capture wrong or right way risk. https://frenxiv.org/2rtya/download

scholarly journals An Accurate Solution for Credit Valuation Adjustment (CVA) and Wrong Way Risk

2019 ◽  
Author(s):  
Tim Xiao
Keyword(s):  
Monte Carlo ◽  
Probability Distribution ◽  
Accurate Solution ◽  
Least Square ◽  
Backward Induction ◽  
Order Of Accuracy ◽  
Monte Carlo Approach ◽  
Default Time ◽  
Credit Valuation Adjustment ◽  
High Order Of Accuracy

This paper presents a Least Square Monte Carlo approach for accurately calculating credit value adjustment (CVA). In contrast to previous studies, the model relies on the probability distribution of a default time/jump rather than the default time itself, as the default time is usually inaccessible. As such, the model can achieve a high order of accuracy with a relatively easy implementation. We find that the valuation of a defaultable derivative is normally determined via backward induction when their payoffs could be positive or negative. Moreover, the model can naturally capture wrong or right way risk. https://osf.io/preprints/socarxiv/3yjk2/download

scholarly journals The Impact of Default Dependency and Collateralization on Asset Pricing and Credit Risk Modeling

2019 ◽  
Author(s):  
Tim Xiao
Keyword(s):  
Asset Pricing ◽  
Credit Risk ◽  
Financial Markets ◽  
Default Risk ◽  
Risk Modeling ◽  
Financial Instruments ◽  
Otc Derivatives ◽  
Counterparty Credit Risk ◽  
Comprehensive Framework ◽  
The Impact

This article presents a comprehensive framework for valuing financial instruments subject to credit risk. In particular, we focus on the impact of default dependence on asset pricing, as correlated default risk is one of the most pervasive threats in financial markets. We analyze how swap rates are affected by bilateral counterparty credit risk, and how CDS spreads depend on the trilateral credit risk of the buyer, seller, and reference entity in a contract. Moreover, we study the effect of collateralization on valuation, since the majority of OTC derivatives are collateralized. The model shows that a fully collateralized swap is risk-free, whereas a fully collateralized CDS is not equivalent to a risk-free one.

scholarly journals An Accurate Solution for Credit Valuation Adjustment (CVA) and Wrong Way Risk

2019 ◽  
Author(s):  
Tim Xiao
Keyword(s):  
Monte Carlo ◽  
Probability Distribution ◽  
Accurate Solution ◽  
Least Square ◽  
Backward Induction ◽  
Order Of Accuracy ◽  
Monte Carlo Approach ◽  
Default Time ◽  
Credit Valuation Adjustment ◽  
High Order Of Accuracy

This paper presents a Least Square Monte Carlo approach for accurately calculating credit value adjustment (CVA). In contrast to previous studies, the model relies on the probability distribution of a default time/jump rather than the default time itself, as the default time is usually inaccessible. As such, the model can achieve a high order of accuracy with a relatively easy implementation. We find that the valuation of a defaultable derivative is normally determined via backward induction when their payoffs could be positive or negative. Moreover, the model can naturally capture wrong or right way risk. https://arabixiv.org/2cqbg/download

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