Results 181 to 190 of about 111,357 (244)

Efficient parallel Monte-Carlo techniques for pricing American options including counterparty credit risk

International Journal of Computational Mathematics, 2023
In this article we mainly propose a numerical scheme, based on the novel Stochastic Grid Bundling Method (SGBM), to price American options in the presence of counterparty credit risk.
Iñigo Arregui, Á. Leitao, B. Salvador, Carlos Vázquez   +3 more
semanticscholar   +1 more source

Counterparty credit risk

Machine Learning for Risk Calculations, 2021
Book file PDF easily for everyone and every device. You can download and read online Counterparty Credit Risk file PDF Book only if you are registered here.
Joyce Damm, T. Padgett
semanticscholar   +1 more source

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

Probability in the engineering and informational sciences (Print), 2022
In this paper, we study the credit default swap (CDS) pricing with counterparty risk in a reduced form model. The default jump intensities of the reference firm and counterparty are both assumed to follow the mean-reverting CIR processes with independent
Yu Chen, Yu Xing
semanticscholar   +1 more source

Valuation of kth-to-default credit-linked notes with counterparty risk in a reduced-form model

Communications in Statistics - Theory and Methods, 2021
In this paper we analyze the kth-to-default credit-linked notes (CLN) with counterparty risk by the reduced-form model. We study the structure of the kth-to-default CLN and present a general valuation framework for CLN values and counterparty valuation ...
Kangquan Zhi, Xiao-song Qian, Ayu Xie
semanticscholar   +1 more source

Counterparty Credit Risk and AmericanOptions

The Journal of Derivatives, 2010
One of the many counterintuitive things students in a first course on options learn is that premature exercise of an American call option on a nondividend paying stock is a mistake, and that for a dividend-paying stock, early exercise is never rational except just before the stock goes ex-dividend. Efforts to incorporate counterparty credit risk in the
Peter Charles Klein, Jun Yang
openaire   +1 more source

Counterparty Credit Risk

Quantitative Finance, 2013
Counterparty Credit Risk is a must-read for anyone interested or involved in counterparty credit risk (CCR); it is one of the first comprehensive, well-written books on this topic, which has become...
openaire   +1 more source

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

Communications in Statistics - Theory and Methods
. In this article, we investigate the pricing of credit default swaps (CDS) while taking into account counterparty risk. We adopt a reduced form model with a self-exciting Hawkes process that allows for clustering in the default intensity. By solving the
Yu-hua Xing, Wei Wang, Xiaonan Su
semanticscholar   +1 more source

Wrong-way risk bounds in counterparty credit risk management

Journal of Risk Management in Financial Institutions, 2017
We study the problem of finding the worst-case joint distribution of a set of risk factors given prescribed multivariate marginals and a non-linear loss function.
Amir Memartoluie, D. Saunders, T. Wirjanto   +2 more
semanticscholar   +1 more source

Credit Contagion from Counterparty Risk

SSRN Electronic Journal, 2008
ABSTRACTStandard credit risk models cannot explain the observed clustering of default, sometimes described as “credit contagion.” This paper provides the first empirical analysis of credit contagion via direct counterparty effects. We find that bankruptcy announcements cause negative abnormal equity returns and increases in CDS spreads for creditors ...
PHILIPPE JORION, GAIYAN ZHANG
openaire   +1 more source

Artificial Neural Network Approach to Counterparty Credit Risk and XVA

Social Science Research Network, 2019
Novel approaches employing an Artificial Neural Networks to enhance the infrastructure of existing Monte Carlo Risk engines are presented. An Artificial Neural Network is utilized to retrieve trade- and market data from existing Expected Exposure ...
Sven Welack
semanticscholar   +1 more source