LETTER FROM THE EDITOR-IN-CHIEF
Warrington College of Business, University of Florida
This issue of the Journal of Risk concerns credit risk, particularly the modeling of loss given default; regulatory capital for banks in view of cyclical macroeconomic factors; the impact of monetary uncertainty on equity return volatility; and optimal reinsurance policies from a risk management perspective.
In our first paper, “Modeling loss given default regressions”, Phillip Li, Xiaofei Zhang, and Xinlei Zhao conduct a simulation exercise to control the various aspects affecting the accuracy of current loss given default (LGD) regression models. Their study addresses the lack of discrimination between simple and more sophisticated models despite the fact that LGD distributions tend to be multi modal. Through their approach, the authors find that, if the focus is on expected values, then all the regression models perform similarly. However, if the entire LGD distribution is the object of the analysis, then the more sophisticated models are to be preferred. Most importantly, though, all models are affected significantly when critical variables are omitted or if samples are small, thus cautioning against incomplete models for stress testing.
The second paper, “Bank leverage and core capital adjustment through the macroeconomic cycle,” by Andy Jia-Yuh Yeh, addresses the still evolving discussion regarding the appropriate level of regulatory equity capital for banks. The author’s analysis, consisting of a theoretical model supported by empirical results, shows that current recommendations, which rely on certain macroeconomic risk variates without considering their variance and skewness, lead to a downward capitalization bias. As a consequence, banks, which are typically highly leveraged, should increase their equity capital in a countercyclical fashion to better weather unpredictable downturns.
In “Monetary policy uncertainty and volatility jumps in advanced equity markets”, the third paper in this issue, Elie Bouri, Konstantinos Gkillas, Rangan Gupta, and Clement Kyei propose the use of a nonparametric causality-in-quantile test to explore the link between monetary policy uncertainty and equity return volatility. This study thus offers a stronger evidence of the effect of the former on the latter than that provided by the standard linear Granger causality test.
In our fourth and final paper, “Optimal reinsurance with expectile under Vajda condition”, Yanhong Chen considers the minimization of an insurer’s adjusted liability. The author adopts the combined use of expectiles for risk margin determination, to address coherence and elicitability, and of the so-called Vajda condition, which captures increased retained risk in reinsurance contracts. This approach results, in particular, in optimal loss functions that account for quota share reinsurance and stop-loss reinsurance.
The authors investigate the puzzle in the literature that various parametric loss given default (LGD) statistical models perform similarly, by comparing their performance in a simulation framework.
The author assesses the quantitative effects of the recent proposal for more robust bank capital adequacy.
The authors analyze the role of monetary policy uncertainty in predicting jumps in nine advanced equity markets.
In this paper, the author revisits optimal reinsurance problems by minimizing the adjusted value of the liability of an insurer, which encompasses a risk margin. The risk margin is determined by expectile.