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Value Decomposition (VD) aims to deduce the contributions of agents for decentralized policies in the presence of only global rewards, and has recently emerged as a powerful credit assignment paradigm for tackling cooperative Multi-Agent…

Machine Learning · Computer Science 2023-03-15 Shunyu Liu , Yihe Zhou , Jie Song , Tongya Zheng , Kaixuan Chen , Tongtian Zhu , Zunlei Feng , Mingli Song

In this paper we revisit Burnett (2021) \& Burnett and Williams (2021)'s notion of hedging valuation adjustment (HVA), originally intended to deal with dynamic hedging frictions such as transaction costs, in the direction of model risk. The…

Pricing of Securities · Quantitative Finance 2024-08-29 Cyril Bénézet , Stéphane Crépey

Competing firms that share a population of risky customers face a decentralized risk detection problem in which each firm holds fragmentary information whose aggregation would generate social value, but private incentives impede truthful…

Computer Science and Game Theory · Computer Science 2026-05-14 Jian Ni , Lecheng Zheng , John R Birge

This paper is devoted to the quantification and analysis of marginal risk contribution of a given single financial institution i to the risk of a financial system s. Our work expands on the CoVaR concept proposed by Adrian and Brunnermeier…

Risk Management · Quantitative Finance 2012-11-27 Brice Hakwa , Manfred Jäger-Ambrożewicz , Barbara Rüdiger

General wrong way risk (WWR) estimation is necessary for regulatory CVA capital and useful for pricing CVA and FVA. We introduce a model independent method for calculating WWR and update the definition of WWR to deal with the lack of…

Pricing of Securities · Quantitative Finance 2021-10-11 Chris Kenyon , Mourad Berrahoui , Benjamin Poncet

Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) are two risk measures which are widely used in the practice of risk management. This paper deals with the problem of computing both VaR and CVaR using stochastic approximation (with…

Computational Finance · Quantitative Finance 2010-12-06 Olivier Aj Bardou , Noufel Frikha , G. Pagès

We present an approach to market-consistent multi-period valuation of insurance liability cash flows based on a two-stage valuation procedure. First, a portfolio of traded financial instrument aimed at replicating the liability cash flow is…

Risk Management · Quantitative Finance 2016-07-15 Hampus Engsner , Mathias Lindholm , Filip Lindskog

Current approaches to fair valuation in insurance often follow a two-step approach, combining quadratic hedging with application of a risk measure on the residual liability, to obtain a cost-of-capital margin. In such approaches, the…

Risk Management · Quantitative Finance 2023-06-22 Karim Barigou , Valeria Bignozzi , Andreas Tsanakas

The ability to make optimal decisions under uncertainty remains important across a variety of disciplines from portfolio management to power engineering. This generally implies applying some safety margins on uncertain parameters that may…

Systems and Control · Electrical Eng. & Systems 2020-03-05 Matt Roveto , Robert Mieth , Yury Dvorkin

Tail-end risk measures such as static conditional value-at-risk (CVaR) are used in safety-critical applications to prevent rare, yet catastrophic events. Unlike risk-neutral objectives, the static CVaR of the return depends on entire…

Machine Learning · Computer Science 2026-02-04 Aneri Muni , Vincent Taboga , Esther Derman , Pierre-Luc Bacon , Erick Delage

The purpose of this paper is to design an algorithm for the computation of the counterparty risk which is competitive in regards of a brute force "Monte-Carlo of Monte-Carlo" method (with nested simulations). This is achieved using marked…

Computational Finance · Quantitative Finance 2012-03-13 Pierre Henry-Labordere

Corporate credit ratings issued by third-party rating agencies are quantified assessments of a company's creditworthiness. Credit Ratings highly correlate to the likelihood of a company defaulting on its debt obligations. These ratings play…

Machine Learning · Computer Science 2022-07-12 Han Yue , Steve Xia , Hongfu Liu

In this paper we study the pricing of exchange options under a dynamic described by stochastic correlation with random jumps. In particular, we consider a Ornstein-Uhlenbeck covariance model with Levy Background Noise Process driven by…

Computational Finance · Quantitative Finance 2017-11-29 Olivares Pablo , Villamor Enrique

We study the impact of central clearing of over-the-counter (OTC) transactions on counterparty exposures in a market with OTC transactions across several asset classes with heterogeneous characteristics. The impact of introducing a central…

Risk Management · Quantitative Finance 2014-03-13 Rama Cont , Thomas Kokholm

In this work, we address risk-averse Bayes-adaptive reinforcement learning. We pose the problem of optimising the conditional value at risk (CVaR) of the total return in Bayes-adaptive Markov decision processes (MDPs). We show that a policy…

Machine Learning · Computer Science 2021-10-27 Marc Rigter , Bruno Lacerda , Nick Hawes

In this paper, the author considers the numerical computation of CVA for large systems by Mote Carlo methods. He introduces two types of stochastic mesh methods for the computations of CVA. In the first method, stochastic mesh method is…

Probability · Mathematics 2015-10-16 Yusuke Morimoto

We study the problem of valuing and hedging a vulnerable derivative claim with bilateral cash flows between two counterparties in the presence of asymmetric funding costs, defaults and wrong way risk (WWR). We characterize the pre-default…

Pricing of Securities · Quantitative Finance 2024-03-26 Juan Jose Francisco Miguelez , Cristin Buescu

Within the context of the banking-related literature on contingent convertible bonds, we comprehensively formalise the design and features of a relatively new type of insurance-linked security, called a contingent convertible catastrophe…

Pricing of Securities · Quantitative Finance 2018-04-24 Krzysztof Burnecki , Mario Nicoló Giuricich , Zbigniew Palmowski

The practice of valuation by marking-to-market with current trading prices is seriously flawed. Under leverage the problem is particularly dramatic: due to the concave form of market impact, selling always initially causes the expected…

General Finance · Quantitative Finance 2012-08-28 Fabio Caccioli , Jean-Philippe Bouchaud , J. Doyne Farmer

In offline reinforcement learning (RL) an optimal policy is learned solely from a priori collected observational data. However, in observational data, actions are often confounded by unobserved variables. Instrumental variables (IVs), in…

Machine Learning · Statistics 2024-10-16 Luofeng Liao , Zuyue Fu , Zhuoran Yang , Yixin Wang , Mladen Kolar , Zhaoran Wang
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