Model assesses risks in CCP networks, identifying wrong-way risks.
problem Credit and liquidity risks in CCP networks.
method Developed a model to capture features of gap risk, feedback, and different participant risks.
result Identified wrong-way risks between clearing member defaults and market turbulence.
The study highlights the importance of Wrong-Way Risk in FVA calculations during financial market turmoil.
problem The relevance of Wrong-Way Risk in Funding Valuation Adjustments (FVA) during financial market uncertainty.
method The study examines the impact of various modelling choices, including default times and stochastic/deterministic funding spreads, on FVA calculations.
result WWR effects are non-negligible in FVA modelling from a risk-management perspective.
Wrong-way risk in counterparty and funding exposures is most dramatic in the situations of systemic crises and tails events. A consistent model of wrong-way risk (WWR) is developed here with the probability-weighted addition of tail events to the calculation of credit valuation and funding valuation adjustments (CVA an…
Proposes a new framework for environmental CVA with robust wrong-way risk.
problem Limited operational implementations of translating environmental scenarios into CVA.
method Three components: hazard rate mapping, tail generators, and KL divergence-based wrong-way risk bound.
result Nature CVAs can vary significantly across different ecosystem generators.
A new method uses liquid options to hedge and price wrong way risk in credit valuation adjustment.
problem Managing wrong way risk (WWR) for CVA, specifically in credit valuation adjustment (CVA).
method Model-free worst-case approach based on static hedging of counterparty exposure with liquid options.
result Option-based hedges significantly reduce practical WW-CVA, making it more realistic and practical.
Proposes a new method to assess Wrong-Way Risk in cross-currency swaps.
problem Addressing Wrong-Way Risk (WWR) in cross-currency swaps with stochastic correlation modeling.
method Proposes a stochastic correlation approach to model the dependency between exposure and counterparty credit risk, capturing tail dependence.
result The impact of stochastic correlation on calculated CVA is substantial, providing a promising method to model WWR.
Efficiently models Wrong-Way Risk in FVA without full Monte Carlo.
problem Assessing Wrong-Way Risk in Funding Valuation Adjustments (FVA) without extensive simulations.
method Splitting exposure into independent and WWR-driven parts; approximating WWR-driven part using Gaussian stochastic factor.
result An efficient and robust method to include WWR in FVA modelling.
New method to price CVA by adjusting exposure drift to eliminate Wrong-Way Risk.
problem Addressing Wrong-Way Risk (WWR) in Credit Value Adjustment (CVA) pricing.
method Stochastic intensity approach with changes of measure to embed WWR in exposure drift.
result Elimination of WWR explicitly in pricing problem, leading to tractable approximation.
Paper compares analytical and dynamic approaches for wrong-way risk modeling in finance.
problem Modeling wrong-way risk in financial contracts like CVA.
method Static and dynamic approaches, including a new dynamic approach using survival process.
result Analytical derivation of positive exposures and expected values in dynamic models.
Paper calculates robust XVA for derivatives under distributional uncertainty using Wasserstein distance.
problem Distributional uncertainty in over-the-counter derivatives pricing.
method Wasserstein distance as ambiguity measure, dual formulations derived using Lagrangian duality.
result Characterization and quantification of wrong-way counterparty credit and funding risks.
Solves worst-case joint distribution problem for financial risk factors.
problem Finding worst-case joint distribution of risk factors given marginals and loss function.
method Uses linear programming to solve the problem when CVaR is the risk measure and distributions are discretized.
result Demonstrates method's applicability to various financial contexts, including counterparty credit risk.
The dynamic Gaussian copula model shows default times are invariant, contrary to the immersion property.
problem The dynamic Gaussian copula model's default times exhibit unexpected invariance properties.
method Proof of invariance properties of default times in the dynamic Gaussian copula model.
result Default times in the dynamic Gaussian copula model are invariant, contrary to the immersion property.
Paper calculates robust FVA for OTC derivatives under distributional uncertainty.
problem Distributional uncertainty in over the counter derivatives valuation.
method Wasserstein distance as ambiguity measure, dual formulation of robust FVA optimization.
result Additional FVA charge due to distributional uncertainty measured under various configurations.
A new model reduces Wrong-Way Risk in CVA pricing.
problem Limiting Wrong-Way Risk (WWR) in CVA pricing models.
method Subordinated Cox-Ingersoll-Ross (CIR) intensity model with time-changing intensities.
result The new model introduces significant WWR compared to JCIR++.
Analyzes valuation of derivative claims with asymmetric funding costs and WWR.
problem Valuing and hedging derivative claims with bilateral cash flows in asymmetric funding and risk environments.
method Characterizes pre-default claim value as solution to a non-linear Cauchy problem, applies stochastic representation under linear funding policy.
result Derivative claim value can be represented as a portfolio of European options and admits an analytical formula involving elementary functions and Gaussian integrals.
Approximates CVA of European options with WWR using correlation expansions.
problem Computing CVA of European options with Wrong Way Risk in a default intensity setting.
method Exploits a correlation expansion approach to approximate option pricing.
result Numerical evaluations show the method's performance compared to existing methods.
Maps obstructing positive scalar curvature and inessentialness.
problem Obstructing metrics with positive scalar curvature and inessential submanifolds.
method Construction of wrong way maps in uniformly finite homology and homology of groups.
result Obstructions to positive scalar curvature metrics and inessential submanifolds.
The introduction of CCPs in most derivative transactions will dramatically change the landscape of derivatives pricing, hedging and risk management, and, according to the TABB group, will lead to an overall liquidity impact about 2 USD trillions. In this article we develop for the first time a comprehensive approach fo…
Study shows how to better estimate credit provisions and economic capital.
problem Estimating credit provisions and economic capital accurately.
method Using supermodularity ordering properties and elliptically distributed latent factors.
result Convex risk measures of credit losses are nondecreasing w.r.t. various covariances.
Counterparty Risk FAQ: Credit VaR, PFE, CVA, DVA, Closeout, Netting, Collateral, Re-hypothecation, WWR, Basel, Funding, CCDS and Margin Lendingq-fin.PR We present a dialogue on Counterparty Credit Risk touching on Credit Value at Risk (Credit VaR), Potential Future Exposure (PFE), Expected Exposure (EE), Expected Positive Exposure (EPE), Credit Valuation Adjustment (CVA), Debit Valuation Adjustment (DVA), DVA Hedging, Closeout conventions, Netting clauses, Collateral …
The paper analyzes credit valuation adjustments under collateralized interest rate derivatives, introducing a new dynamics for multiple interest rate curves.
problem The impact of multiple interest rate curves on credit valuation adjustments under collateralized models.
method Formulated a consistent dynamics for multiple interest rate curves, including the margin period of risk and stochastic basis for wrong-way risk analysis.
result Numerical results confirm the importance of stochastic basis for proper wrong-way risk analysis of sensitive products like basis swaps.
Everyone misunderstands the Sharpe ratio, which measures risk in finance.
problem Misunderstanding of the Sharpe ratio as a risk metric.
method A critical analysis and rectification of the Sharpe ratio concept.
result Clarification of the Sharpe ratio's role in risk assessment.
This paper addresses recalibration issues in hedging callable assets, proposing a new risk-adjusted approach.
problem The mismatch between dynamic hedging theory and practice due to daily recalibration.
method Extends HVA model risk approach to callable assets, focusing on recalibration and model risks.
result Model risk reserves adjusted for exercise decisions may significantly exceed basic valuation differences.
The market practice of extrapolating different term structures from different instruments lacks a rigorous justification in terms of cash flows structure and market observables. In this paper, we integrate our previous consistent theory for pricing under credit, collateral and funding risks into term structure modellin…
Study normal bundle and deformation to get new pushforward maps.
problem Construct pushforward maps in various homology theories.
method Use deformation Lie groupoids to construct pushforward maps.
result Functoriality of pushforward maps recovers and generalizes previous cases.
We depart from the usual methods for pricing contracts with the counterparty credit risk found in most of the existing literature. In effect, typically, these models do not account for either systemic effects or at-first-default contagion and postulate that the contract value at default equals either the risk-free valu…
In this note we sketch an initial tentative approach to funding costs analysis and management for contracts with bilateral counterparty risk in a simplified setting. We depart from the existing literature by analyzing the issue of funding costs and benefits under the assumption that the associated risks cannot be hedge…
CCPs, Central Clearing, CSA, Credit Collateral and Funding Costs Valuation FAQ: Re-hypothecation, CVA, Closeout, Netting, WWR, Gap-Risk, Initial and Variation Margins, Multiple Discount Curves, FVA?q-fin.PR We present a dialogue on Funding Costs and Counterparty Credit Risk modeling, inclusive of collateral, wrong way risk, gap risk and possible Central Clearing implementation through CCPs. This framework is important following the fact that derivatives valuation and risk analysis has moved from exotic derivatives managed…
For a Lie groupoid G with a twisting (a PU(H)-principal bundle over G), we use the (geometric) deformation quantization techniques supplied by Connes tangent groupoids to define an analytic index morphism in twisted K-theory. In the case the twisting is trivial we recover the analytic index morphism of the groupoid. Fo…
This paper introduces an arbitrage-free conic martingale model for credit risk.
problem The lack of an arbitrage-free conic martingale model for credit risk.
method Developed an arbitrage-free conic martingale called Φ-martingale.
result The Φ-martingale model satisfies the immersion property and is suitable for practical applications in credit risk.
Derives a new formula for measuring risk aversion in markets.
problem Measuring the degree of risk aversion in markets accurately.
method Closed-form expression based on three variables: Treasury yields, returns, and market capitalization.
result Investors exhibit Decreasing Absolute Risk Aversion (DARA) but the degree of Relative Risk Aversion (RRA) varies.
The study corrects misconceptions in GBDT speed benchmarks.
problem Misleading speed benchmarks of GBDT algorithms.
method Explained and criticized several straightforward benchmarking methods, outlined fair benchmark requirements.
result A fair GBDT speed benchmark requires specific conditions.
Causal Set Theory's Hauptvermutung is resolved in two ways, one of which is true.
problem Formulating and resolving the Hauptvermutung in Causal Set Theory.
method Two mathematically well-defined formulations of the Hauptvermutung, one of which is true.
result The Hauptvermutung is true when finite sets are replaced by countable sets.
This paper examines limitations of machine learning models in social systems.
problem Understanding and addressing the shortcomings of machine learning models in social applications.
method Structured overview of conceptual, procedural, and statistical limitations.
result Identification of failure points and ways to address them.
A new update rule for deep reinforcement learning reduces learning variance and variance in reference signals.
problem Learning variance and incorrect reference signals in deep reinforcement learning.
method t-soft update method inspired by student-t distribution, which reduces extreme updates and accelerates similar updates.
result The t-soft update method outperforms conventional methods in terms of return and variance in PyBullet robotics simulations.
New model fits term structures with positivity constraints.
problem Calibrating term structure models to market curves with positivity constraints.
method Time-changed approach to fit term structures.
result Model generates larger volatility and covariance effects under positivity constraints.
This work examines fundamental limits in model falsification without assuming specific distributions.
problem Establishing lower bounds on model class risk in distribution-free settings.
method Model-agnostic fundamental hardness result for constructing lower bounds on test error.
result No positive lower bound on model class risk is possible in certain settings.
A clearing member of a Central Counterparty (CCP) is exposed to losses on their default fund and initial margin contributions. Such losses can be incurred whenever the CCP has insufficient funds to unwind the portfolio of a defaulting clearing member. This does not necessarily require the default of the CCP itself. In …
Unsupervised learning models can produce accurate but misleading predictions.
problem Widespread misleading predictions in unsupervised learning models.
method Developed Explainable AI techniques to detect misleading predictions.
result Widespread Clever Hans effects in unsupervised learning models.
The paper reduces xVA calculations by approximating sensitivities.
problem Nested expectation problem and computational expense in xVA calculations.
method Polynomial approximations of shocked and unshocked valuation functions, and their difference.
result High accuracy and remarkable computational cost reduction demonstrated.
Study examines hedging options on asset portfolios against one underlying asset with transaction costs.
problem Hedging options on asset portfolios when one underlying asset is expensive to trade.
method Simulated data analysis with varying trading intervals, correlation coefficients, and transaction costs.
result Trading the wrong asset can be beneficial when correlation is high and transaction costs are low.
Unified deep learning from noisy crowds using BP and MF.
problem Inference and learning from noisy crowdsourced data.
method Neural-powered Bayesian framework with deepMF and deepBP.
result deepBP is more robust against wrong priors and feature overfitting.
Combining interpretability and stability methods improves DNN robustness.
problem Improving interpretability and robustness of deep neural networks.
method Combining interpretability (conductance) and stability (binary classifier) methods to detect and discard wrong predictions.
result Combining interpretability and stability methods increases model robustness.
The paper provides a method to calculate CVA for vulnerable options in stochastic volatility models.
problem Evaluating Credit Value Adjustment (CVA) for options subject to default events in stochastic volatility models.
method Using Ito's calculus, the paper provides a general representation formula for CVA correction in SABR, Hull & White, and Heston models.
result The formula explicitly shows the correction in CVA due to the correlation between the underlying's price process and the default event.
Simple method calculates WWR for regulatory and accounting purposes.
problem Estimating WWR for regulatory and accounting capital requirements.
method Model-independent approach using integral expressions and component calibration.
result WWR effects for FVA are significantly more material than for CVA.
Study on information cascade fragility under mismatched revealing probabilities.
problem Analyzing the fragility of information cascades in decision-making processes with imperfect knowledge of revealing probabilities.
method Examined sequential decision-making models with players having private information and imitating previous decisions. Studied the effect of a mismatch between players' beliefs and actual revealing probabilities.
result Derived closed-form expressions for optimal learning rates and identified phase transitions in the behavior of asymptotic learning rates.
Paper proposes a method to detect adversarial examples using saliency.
problem Detecting adversarial perturbations in machine learning models.
method Trains a binary classifier with origin data and saliency data.
result Shows good performance in detecting adversarial perturbations.
ToolChain-CRC addresses the risk-control problem for retrieval-augmented and tool-using agents under drift.
problem Risk-control problem for retrieval-augmented and tool-using agents under drift.
method ToolChain-CRC uses conformal risk-control under exchangeable calibration runs.
result Trajectory-level risk control keeps accepted-trajectory risk below the target.