Corporate defaults may be triggered by some major market news or events such as financial crises or collapses of major banks or financial institutions. With a view to develop a more realistic model for credit risk analysis, we introduce a new type of reduced-form intensity-based model that can incorporate the impacts o…
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48 results for “default event”
We propose two structural models for stochastic losses given default which allow to model the credit losses of a portfolio of defaultable financial instruments. The credit losses are integrated into a structural model of default events accounting for correlations between the default events and the associated losses. We…
The study examines Cox models for lifetime loan default risk, addressing biased estimates by incorporating recurrent events.
problem Ignoring recurrent default events in Cox models leads to biased and inaccurate PD estimates.
method Investigates and compares different Cox models (Andersen-Gill and Prentice-Williams-Peterson) for lifetime loan default risk.
result The Andersen-Gill model underperforms compared to the Prentice-Williams-Person model and the time to first default model.
We study large deviations and rare default clustering events in a dynamic large heterogeneous portfolio of interconnected components. Defaults come as Poisson events and the default intensities of the different components in the system interact through the empirical default rate and via systematic effects that are comm…
The impact of a stress scenario of default events on the loss distribution of a credit portfolio can be assessed by determining the loss distribution conditional on these events. While it is conceptually easy to estimate loss distributions conditional on default events by means of Monte Carlo simulation, it becomes imp…
A new method estimates corporate bond defaults in financial networks efficiently.
problem Challenges in valuing corporate bonds in interconnected financial systems.
method Bi-Level Importance Sampling with Splitting
result The method efficiently estimates rare default events in financial networks.
Hedging of defaultable claims in a structural model using a locally risk-minimizing approachq-fin.MF
A method for hedging defaultable claims using locally risk-minimizing in a structural model.
problem Hedging defaultable claims in a structural model with jumps and non-risk-neutral probabilities.
method Locally risk-minimizing approach in a structural model with finite variation Levy process.
result Derivation of Follmer-Schweizer decompositions for hedging.
New model estimates corporate defaults using pure jump processes, capturing extreme events.
problem Estimating corporate defaults using standard diffusion models that underestimate short-term probabilities.
method Introduced pure jump processes with negative jumps only, derived formulas, calibrated parameters, and implemented practical tools.
result Models redistribute credit risk towards shorter maturities, improving short-term default probability estimates.
The paper models default probabilities and total defaults in credit portfolios using a contagion process with self-exciting jumps.
problem Modeling default probabilities and total defaults in credit portfolios to mitigate credit risk.
method Developed a contagion process with self-exciting jumps to model credit events and derive closed-form expressions for default probabilities and total defaults.
result The proposed framework captures the feedback effect and can be used to price synthetic CDOs.
We develop a dynamic point process model of correlated default timing in a portfolio of firms, and analyze typical default profiles in the limit as the size of the pool grows. In our model, a firm defaults at a stochastic intensity that is influenced by an idiosyncratic risk process, a systematic risk process common to…
Study on price formation in financial markets with a single default event.
problem Equilibrium price formation in financial markets with a single default risk.
method Characterized optimal strategies using quadratic-growth BSDEs, derived market-clearing condition, and established mean-field BSDE solvability.
result Characterized equilibrium risk premium and its dependence on default risk factors.
Develops RES metrics for stable rare-event forecasting evaluation.
problem Challenges in evaluating forecasts of rare events.
method Rare-event-stable (RES) metrics designed to maintain stable thresholds under extreme rarity.
result RES metrics maintain stable thresholds, consistent model rankings, and near-complete prevalence invariance.
Collateral-Enhanced Default Riskq-fin.RM
Changes in collateralization have been implicated in significant default (or near-default) events during the financial crisis, most notably with AIG. We have developed a framework for quantifying this effect based on moving between Merton-type and Black-Cox-type structural default models. Our framework leads to a singl…
The single risk factor approach to capital charges in case of correlated loss given default ratescond-mat.other
A new methodology for incorporating LGD correlation effects into the Basel II risk weight functions is introduced. This methodology is based on modelling of LGD and default event with a single loss variable. The resulting formulas for capital charges are numerically compared to the current proposals by the Basel Commit…
The mixed-fractional CEV model improves CDS pricing by accounting for default risk.
problem Improving the pricing of Credit Default Swaps (CDS) by accounting for default risk.
method Using a mixed-fractional Brownian motion to model the Constant Elasticity of Variance (CEV) model.
result The mixed-fractional CEV model yields more realistic CDS spreads and default probabilities.
Extends contagion models to include direct and indirect impacts of defaults on the environment.
problem Capturing the impact of defaults on a broader economy.
method Introduces a new model allowing direct and indirect contagion within and from a default system.
result Shows how defaults within a system can affect the environment and vice versa.
Paper studies estimating asset correlations across sectors.
problem Estimating correlations between different asset sectors.
method Separates cross-sectional and time dimensions for estimation.
result Developed method for better asset correlation estimation.
Investment strategy optimized for agents with varying information about default events.
problem Optimal investment strategy under default risk with varying information.
method Using enlargement of filtrations theory to model insider information and solving utility maximization problems.
result Explicit logarithmic utility maximization results for optimal wealth of insiders and ordinary agents.
The paper analyzes Lending Club's loan applicants to predict default risk.
problem Predicting default risk in loan applicants of Lending Club.
method Exploratory data analysis and machine learning (Logistic Regression, Random Forest) were used.
result A credit derivative based on Credit Default Swap was designed to hedge default risk.
Paper analyzes CoCos with short-term uncertainty and noisy firm reports.
problem Modeling conversion and default in CoCos under short-term uncertainty.
method Combines Duffie and Lando (2001) and Jeanblanc and Valchev (2005) models.
result Describes CoCo bond conversion and default using a short-term uncertainty model.
While defaults are rare events, losses can be substantial even for credit portfolios with a large number of contracts. Therefore, not only a good evaluation of the probability of default is crucial, but also the severity of losses needs to be estimated. The recovery rate is often modeled independently with regard to th…
The study examines how class imbalance impacts logistic regression models in low-default credit portfolios.
problem The impact of class imbalance on logistic regression models in low-default credit portfolios.
method Simulation study with controlled data-generating mechanisms to vary class imbalance and predictor-response association strength.
result Classification accuracy decreases significantly as event rate decreases, and optimal cut-off shifts with imbalance.
We develop a finite horizon continuous time market model, where risk averse investors maximize utility from terminal wealth by dynamically investing in a risk-free money market account, a stock written on a default-free dividend process, and a defaultable bond, whose prices are determined via equilibrium. We analyze fi…
Model shows how firms manage risk and capital in default-prone markets.
problem Managing risk and capital in firms facing default risk.
method Developed a model to characterize optimal dividend and capital structure policies.
result Optimal policy involves paying dividends to keep equity value below a critical threshold.
Paper uses interbank contagion to predict U.S. bank defaults, finding it highly explanatory.
problem Predicting U.S. bank defaults using interbank contagion.
method Regression and neural network models were used to analyze U.S. commercial bank data.
result Interbank contagion is highly explanatory in default prediction, often outperforming established metrics.
Pricing formulae for defaultable corporate bonds with discrete coupons under consideration of the government taxes in the united model of structural and reduced form models are provided. The aim of this paper is to generalize the comprehensive structural model for defaultable fixed income bonds (considered in [1]) into…
Diffusion in a linear potential in the presence of position-dependent killing is used to mimic a default process. Different assumptions regarding transport coefficients, initial conditions, and elasticity of the killing measure lead to diverse models of bankruptcy. One "stylized fact" is fundamental for our considerati…
For credit risk management purposes in general, and for allocation of regulatory capital by banks in particular (Basel II), numerical assessments of the credit-worthiness of borrowers are indispensable. These assessments are expressed in terms of probabilities of default (PD) that should incorporate a certain degree of…
A new model calculates LGD distribution based on firm value and credit market conditions.
problem Estimating LGD distribution in credit markets.
method Uses last passage time of a linear diffusion process to model LGD distribution.
result Explicit distributions of default time and LGD are obtained under minimal assumptions.
In this article, we consider a 2 factors-model for pricing defaultable bond with discrete default intensity and barrier where the 2 factors are stochastic risk free short rate process and firm value process. We assume that the default event occurs in an expected manner when the firm value reaches a given default barrie…
Deep learning detects sleep events like arousals and leg movements.
problem Detecting arousals and leg movements in polysomnogram for sleep disorders.
method Deep learning model trained on 1,485 subjects, tested on 1,000 recordings.
result Optimal detection achieved with dynamic event window for arousals and static window for leg movements.
Optimal dividend strategy for insurance group with contagious default risk.
problem Optimal dividend strategy for a multi-line insurance group with default contagion.
method Analysis of recursive system of Hamilton-Jacobi-Bellman variational inequalities (HJBVIs).
result Optimal dividend strategy is still of the barrier type, and optimal barrier is modulated by default state.
An insurer optimizes investment and risk control with default contagion and regime-switching.
problem Maximizing expected utility of terminal wealth in a risky market with default events.
method Develops a truncation technique to analyze the recursive HJB system and proves the existence and uniqueness of solutions.
result Characterizes optimal trading strategy and risk control for the insurer.
Model financial default cascades on sparse graphs via hitting times.
problem Capturing systemic risk in large, sparsely-connected financial networks.
method Dynamic particle systems with hitting times and convergence theory.
result Characterization of default time distribution in tree-like networks.
We build a general model for pricing defaultable claims. In addition to the usual absence of arbitrage assumption, we assume that one defaultable asset (at least) looses value when the default occurs. We prove that under this assumption, in some standard market filtrations, default times are totally inaccessible stoppi…
The estimation of probabilities of default (PDs) for low default portfolios by means of upper confidence bounds is a well established procedure in many financial institutions. However, there are often discussions within the institutions or between institutions and supervisors about which confidence level to use for the…
Study estimates default probabilities without liquid CDS, using real-world probabilities.
problem Estimating default probabilities in markets with no liquid CDS.
method Use minimum variance hedge, estimate real-world probabilities.
result Validates use of real-world probabilities for CVA calculations.
As it is known in the finance risk and macroeconomics literature, risk-sharing in large portfolios may increase the probability of creation of default clusters and of systemic risk. We review recent developments on mathematical and computational tools for the quantification of such phenomena. Limiting analysis such as …
This paper studies the valuation of a class of default swaps with the embedded option to switch to a different premium and notional principal anytime prior to a credit event. These are early exercisable contracts that give the protection buyer or seller the right to step-up, step-down, or cancel the swap position. The …
French bank uses corporate transaction data to predict credit default risk better than traditional methods.
problem Predicting credit default risk of enterprises using financial ratios and transaction data.
method Advanced machine learning methods applied to transaction data.
result Transaction data outperforms traditional financial ratios in predicting credit default risk.
In this article, we study the problem of pricing defaultable bond with discrete default intensity and barrier under constant risk free short rate using higher order binary options and their integrals. In our credit risk model, the risk free short rate is a constant and the default event occurs in an expected manner whe…
Study dynamic hedging of credit risk using a new model.
problem Dynamic hedging of counterparty risk for credit derivatives.
method Empirically driven credit model with interacting default intensities; Galtchouk-Kunita-Watanabe decomposition; closed-form risk minimizing strategy.
result Closed-form representation for risk minimizing strategy in nonlinear recursive systems.
Model explains asset price dynamics, defaults, and market crashes via non-linear dynamics.
problem Understanding asset price dynamics, defaults, and market crashes in financial markets.
method Proposes a non-equilibrium model incorporating market frictions and feedback mechanisms.
result The QED model produces non-linear dynamics, broken scale invariance, and corporate defaults.
Paper compares different models for time-to-event analysis.
problem Comparing models for time-to-event analysis.
method Experimental comparison of semi-parametric, parametric, and machine learning models.
result Models' performance evaluated using concordance index.
Modeling bank defaults through hitting thresholds to study systemic risk.
problem Understanding systemic risk in a network of interconnected banks.
method An interacting particle system to model bank defaults and analyze the resulting losses.
result Characterization of discontinuities in the cumulative loss process as systemic events.
Valuation of Credit Valuation Adjustment (CVA) has become an important field as its calculation is required in Basel III, issued in 2010, in the wake of the credit crisis. Exposure, which is defined as the potential future loss of a default event without any recovery, is one of the key elementsfor pricing CVA. This pap…
New mortgage contracts reduce underwater default by adjusting loan balances, but must balance prepayment incentives.
problem Underwater default incentives in mortgages.
method Analyzes automatic balance adjustment and prepayment penalties in mortgage contracts.
result Automatic balance adjustments are preferable to traditional contracts at certain spreads, reducing underwater default.
Credit Calibration with Structural Models: The Lehman case and Equity Swaps under Counterparty Riskq-fin.PR
In this paper we develop structural first passage models (AT1P and SBTV) with time-varying volatility and characterized by high tractability, moving from the original work of Brigo and Tarenghi (2004, 2005) [19] [20] and Brigo and Morini (2006)[15]. The models can be calibrated exactly to credit spreads using efficient…