Yadong Li, Marco Naldi, Jeffrey Nisen and Yixi Shi propose a new capital allocation method
This paper presents a method for approximating the current loan-to-value (CLTV) and remaining principal structures of heterogeneous mortgage loan pools.
A P&L attribution framework can improve the information available to energy traders
A reduced basis method for parabolic partial differential equations with parameter functions and application to option pricing
The authors introduce an RB space–time variational approach for parametric PPDEs with coefficient parameters and a variable initial condition.
The authors propose a general framework to assess the probability of backtest overfitting (PBO).
Modeling corporate customers’ credit risk considering the ensemble approaches in multiclass classification: evidence from Iranian corporate credits
This paper introduces a model which enables lenders to develop specific policies for credit granting by predicting the solvency and insolvency rates of their corporate clients.
The author of this paper assesses operational loss data and its implications for risk capital modeling.
Comments on the Basel Committee on Banking Supervision proposal for a new standardized approach for operational risk
In this paper, the behavior of the SMA is studied under a variety of hypothetical and realistic conditions, showing that the simplicity of the new approach is very costly.
Should the advanced measurement approach be replaced with the standardized measurement approach for operational risk?
This paper discusses and studies the weaknesses and pitfalls of the SMA and the implicit relationship between the SMA capital model and systemic risk in the banking sector.
The authors of this paper give a complete algorithm and source code for constructing general multifactor risk models via any combination of style factors, principal components and/or industry factors.
This paper attempts to quantify the “effective” supply of collateral assets in Australia by applying a measure of supply that adjusts outstanding issuance for two important features of the collateral market.
This paper focuses on the use of high-quality assets for collateral purposes.
Mobilization of collateral in Germany as a reflection of monetary policy and financial market developments
This paper describes and analyzes developments in the market value of marketable assets submitted as collateral in Germany and the Eurosystem against the backdrop of the financial market crisis.
This paper looks at securities-lending, derivatives and prime-brokerage markets as suppliers of collateral.
The authors provide theoretical microfoundations to understand the impact of monetary policy on markets characterized by collateral reuse.
The authors model the asymmetry between collateral values to the parties in the collateral chain. The paper highlights that collateral reuse can be socially beneficial if the costs of misallocation are not significant.
A computationally intensive, multimethod modeling process is undertaken to address the question of whether carbon markets can offer the desired solution of balancing initiatives for technological change while maintaining a commitment to market liberalization.
The authors of this paper address some issues to do with IFRS 9 and explain how to determine if an instrument has suffered serious deterioration in credit risk.
Gordon Ritter proposes a stable mean-variance optimisation for APT models
Lingling Cao and Pierre Henry-Labordère implement Dupire's local volatility in interest rate models
This paper uses the fractional Kelly strategies framework to show that optimal portfolios with low-beta stocks generate higher median wealth and lower intra-horizon shortfall risk.
A correlated structural credit risk model with random coefficients and its Bayesian estimation using stock and credit market information
Using historical equity and credit market data, this paper illustrates the validation of a structural correlated default model applied to Black–Cox setups.
This paper presents a simple model for joint defaults and shows how it can be applied to pricing and risk-managing instruments that are sensitive to credit correlation.
The meaningful uncertainty simulation framework can enable energy firms to make better decisions