This paper outlines several approaches to benchmarking operational loss projections under stressed scenarios using both accounting metrics and historical loss experience.
This paper determines if enough data is available for forecasting or stress testing, a better measure of data length is required.
This paper examines the role of supervisory stress testing of central counterparties (CCPs). A key message is that the design of supervisory stress tests (SSTs) should be tailored to CCPs’ roles, risk profiles and financial structures.
Pascal Traccucci et al present an extended reverse stress test triptych approach with three variables
In this paper, the authors propose a new methodology for modeling credit transition probability matrixes (TPMs) using macroeconomic factors.
A generic stress testing framework with related economic shocks and possible regulatory intervention
In this paper, the authors develop and demonstrate a universal framework for supervisory stress tests of financial institutions that considers the probable dependencies among macroeconomic shocks and possible regulatory intervention.
Matthias Arnsdorf proposes a method to calculate the counterparty risk related to CCP membership
In this paper, the author's aim is to empirically analyze the numerical quantification of model risk, yielding exact buffers in currency amounts (for a given model uncertainty).
Systemic risk in the financial system: capital shortfalls under Brexit, the US elections and the Italian referendum
This paper uses SRISK to quantify the estimated capital shortfalls of financial institutions under three relevant stress events that occurred in 2016: Brexit, the Trump election and the Italian referendum.
In this paper, the author estimates a two-equation system: one for LGD that incorporates time to recovery as one of the model explanatory variables, and the other for time to recovery using survival models that address data censoring.
This paper describes the three components needed to simultaneously stress clearing members and CCPs across markets: scenario generation, evaluation of the profit and loss (P&L) of clearing member portfolios for each scenario, and default of clearing…
In this paper, the authors outline a simulation-based methodology for the generation of stressed transition probability matrixes under the structural credit risk framework.
Forward ordinal probability models for point-in-time probability of default term structure: methodologies and implementations for IFRS 9 expected credit loss estimation and CCAR stress testing
This paper proposes an ordinal model based on forward ordinal probabilities for rank outcomes.
CCP’s risk managers propose a framework for generating extreme but plausible stress scenarios
Bilgili, Ferconi and Ulitsky propose a constrained portfolio optimisation approach incorporating stress scenarios
Forecasting scenarios from the perspective of a reverse stress test using second-order cone programming
This paper proposes a model for forecasting scenarios from the perspective of a reverse stress test using interest rate, equity and foreign exchange data.
The authors put forth a realistic network model that maximizes the use of data available to a CCP in order to simulate credit default contagion.
This paper focuses on the corporate stress testing models for credit risk.
A model combination approach to developing robust models for credit risk stress testing: an application to a stressed economy
This paper uses a model combination approach to develop robust macrofinancial models for credit risk stress testing.
The author of this paper proposes a dynamic PD term structure model for multi-period stress testing and expected credit loss estimation.
The authors analyze the impact of a decline in property prices that leads to stressed recovery rates for collateral on the loss given default (LGD) parameter in portfolios of mortgage loan.
Rating-transition-probability models and Comprehensive Capital Analysis and Review stress testing: methodologies and implementation
This paper introduces a risk component called the credit index, that represents the systematic risk part of a portfolio by a list of macroeconomic variables.
The authors demonstrate how different credit risk models can be efficiently implemented for scenario analysis and stress testing execution with concrete application examples.