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Decisions under uncertainty or with multiple objectives usually require the decision maker to formulate a preference regarding risks or trade-offs. If this preference is known, the ordered weighted averaging (OWA) criterion can be applied…

Optimization and Control · Mathematics 2023-08-02 Werner Baak , Marc Goerigk , Michael Hartisch

We introduce an innovative theoretical framework to model derivative transactions between defaultable entities based on the principle of arbitrage freedom. Our framework extends the traditional formulations based on Credit and Debit…

Risk Management · Quantitative Finance 2012-05-08 Claudio Albanese , Damiano Brigo , Frank Oertel

We consider economic obstacles that limit the reliability and accuracy of value-at-risk (VaR). Investors who manage large market transactions should take into account the impact of the randomness of large trade volumes on predictions of…

General Economics · Economics 2024-04-30 Victor Olkhov

We consider the framework proposed by Burgard and Kjaer (2011) that derives the PDE which governs the price of an option including bilateral counterparty risk and funding. We extend this work by relaxing the assumption of absence of…

Mathematical Finance · Quantitative Finance 2018-02-15 P. Amster , A. P. Mogni

This paper considers the problem of measuring the credit risk in portfolios of loans, bonds, and other instruments subject to possible default under multi-factor models. Due to the amount of the portfolio, the heterogeneous effect of…

Computational Finance · Quantitative Finance 2019-04-10 Cheng-Der Fuh , Chuan-Ju Wang

In mathematical finance, a process of calibrating stochastic volatility (SV) option pricing models to real market data involves a numerical calculation of integrals that depend on several model parameters. This optimization task consists of…

Numerical Analysis · Mathematics 2020-06-24 Josef Daněk , J. Pospíšil

We study a first-order primal-dual subgradient method to optimize risk-constrained risk-penalized optimization problems, where risk is modeled via the popular conditional value at risk (CVaR) measure. The algorithm processes independent and…

Optimization and Control · Mathematics 2021-09-03 Avinash N. Madavan , Subhonmesh Bose

Bank behaviour is important for pricing XVA because it links different counterparties and thus breaks the usual XVA pricing assumption of counterparty independence. Consider a typical case of a bank hedging a client trade via a CCP. On…

Pricing of Securities · Quantitative Finance 2018-03-12 Chris Kenyon , Hayato Iida

Daily Value-at-Risk (VaR) for option books requires more than an accurate quantile forecast. It first requires a precise definition of the loss target. Before any model is evaluated, the protocol must fix the book construction rule, the…

Risk Management · Quantitative Finance 2026-05-19 Tenghan Zhong , Keyuan Wu

We show how the cost of funding the collateral in a particular set up can be equal to the Bilateral Valuation Adjustment with the "funded" probability of default, leading to the definition of a Funded Bilateral Valuation Adjustment (FBVA).…

Pricing of Securities · Quantitative Finance 2012-11-08 Lorenzo Giada , Claudio Nordio

In this paper we modify the model of Itkin, Shcherbakov and Veygman, (2019) (ISV2019), proposed for pricing Quanto Credit Default Swaps (CDS) and risky bonds, in several ways. First, it is known since the Lehman Brothers bankruptcy that the…

Computational Finance · Quantitative Finance 2019-12-19 Andrey Itkin , Fazlollah Soleymani

This work studies the valuation of currency options in markets suffering from a financial crisis. We consider a European option where the underlying asset is a foreign currency. We assume that the value of the underlying asset is a…

Pricing of Securities · Quantitative Finance 2018-01-26 Abdulnasser Hatemi-J , Youssef El-Khatib

Optimizing risk measures such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) of a general loss distribution is usually difficult, because 1) the loss function might lack structural properties such as convexity or…

Optimization and Control · Mathematics 2016-08-03 Helin Zhu , Joshua Hale , Enlu Zhou

Estimating customer lifetime value (CLV or LTV) is extremely important for making better business decisions. The proposed flexible proportional hazards model allows an estimation of lifetime value in contractual settings. This approach…

Applications · Statistics 2022-08-04 Vadim Pliner

We present a path integral method to derive closed-form solutions for option prices in a stochastic volatility model. The method is explained in detail for the pricing of a plain vanilla option. The flexibility of our approach is…

Pricing of Securities · Quantitative Finance 2008-12-02 D. Lemmens , M. Wouters , J. Tempere , S. Foulon

This paper introduces the Inverse Gamma (IGa) stochastic volatility model with time-dependent parameters, defined by the volatility dynamics $dV_{t}=\kappa_{t}\left(\theta_{t}-V_{t}\right)dt+\lambda_{t}V_{t}dB_{t}$. This non-affine model is…

Computational Finance · Quantitative Finance 2019-06-28 Nicolas Langrené , Geoffrey Lee , Zili Zhu

In this paper, we analyze the robustness and sensitivity of various continuous-time rough Volterra stochastic volatility models in relation to the process of market calibration. Model robustness is examined from two perspectives: the…

Pricing of Securities · Quantitative Finance 2023-06-05 Jan Matas , Jan Pospíšil

In this work we develop a tractable structural model with analytical default probabilities depending on a random default barrier and possibly random volatility ideally associated with a scenario based underlying firm debt. We show how to…

Pricing of Securities · Quantitative Finance 2009-12-17 Damiano Brigo , Marco Tarenghi

We present a methodology for model evaluation and selection where the sampling mechanism violates the i.i.d. assumption. Our methodology involves a formulation of the bias between the standard Cross-Validation (CV) estimator and the mean…

Methodology · Statistics 2025-03-14 Oren Yuval , Saharon Rosset

This paper analyses the implementation and calibration of the Heston Stochastic Volatility Model. We first explain how characteristic functions can be used to estimate option prices. Then we consider the implementation of the Heston model,…

Pricing of Securities · Quantitative Finance 2015-03-18 Ricardo Crisostomo