In the present paper, a decomposition formula for the call price due to Alòs is transformed into a Taylor-type formula containing an infinite series with stochastic terms. The new decomposition may be considered as an alternative to the decomposition of…
Integrating macroeconomic variables into behavioral models for interest rate risk measurement in the banking book
This paper proposed a nonparametric approach to decompose a macroeconomic variable into an interest-rate-correlated component and a macro-specific component.
This work looks at a wide range of models to test the degree to which CECL is procyclical for different types of model.
Application scoring plays a critical role in determining the future quality of a lender’s book. It is therefore important to monitor the performance of an application scorecard to ensure it performs as expected.
This paper expands on the foundation of model risk analytics to address the governance, organizational and human behavior challenges associated with enterprise MRM.
Lorenzo Bergomi exposes a condition important to the use of LSV models in trading
A gradient-boosting decision-tree approach for firm failure prediction: an empirical model evaluation of Chinese listed companies
In this paper, the authors employ a gradient-boosting decision-tree method to improve firm failure prediction and explain how to better analyze the relative importance of each financial variable.
Modeling impacts of stock jumps on real estate investment trust returns with application to value-at-risk
This paper aims to model the impact of extreme stock jumps on REIT returns.
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.
In this paper, a structural model is presented for estimating losses associated with the mis-selling of retail banking products. It is the first paper to consider factor-based modeling for this operational/conduct risk scenario.
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 addresses the issue of model selection risk by examining whether a model’s past performance in forecasting expected returns provides an indication of its future forecasting performance.
In this paper, the authors show how one can use a certain class of models for modeling portfolios such as large corporates, banks and insurance companies.
Realistic models not necessarily a prerequisite for successful risk management
Portfolio diversification often breaks down in stressed market environments, but the co-movement of asset prices in a tail risk regime may be modelled using a coefficient of tail dependence. Here, Yannick Malevergne and Didier Sornette show how such…