A simple and commonly used method to approximate the total claim distribution of a (possible weakly dependent) insurance collective is the normal approximation. In this article, we investigate the error made when the normal approximation is plugged in a fairly general distribution-invariant risk...

A risk management strategy that is designed to be robust to the Global Financial Crisis (GFC), in the sense of selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models, was proposed in McAleer et al. (2010c). The robust forecast is based on the median of the...

This paper develops a robust portfolio optimization model based on regime switching R-Vine copulas, where regime switching R-Vine copulas capture asymmetric dependence and regime switching in financial markets. We consider the uncertainty in hidden economic states and define WSCVaR as CVaR in...

Distributionally robust optimization (DRO) has arose as an important paradigm to address the issue of distributional ambiguity in decision optimization. In its standard form, DRO seeks an optimal solution against the worst-possible expected value evaluated based on a set of candidate...

Robustness of risk measures to changes in underlying loss distributions (distributional uncertainty) is of crucial importance when making well-informed risk management decisions. In this paper, we quantify for any given distortion risk measure its robustness to distributional uncertainty by...

Event studies have become pivotal in securities fraud litigation. The typical use-cases are single firm / single event (SFSE) applications. These differ from the standard event study methodology in that inference on abnormal returns can only be based on the time-series variance of abnormal...

We consider the optimal contract between an entrepreneur and investors in a moral hazard model when both parties have limited liability, are risk-neutral toward cash flow risk, and are ambiguity-averse. In the static setting, the first-best security is either convertible debt or levered equity....

US firm cash holdings have become increasingly concentrated over time withering shareholder returns and heightening agency problems associated with free cash flows. Our use of a robust regression technique (LAD) and a state-of-the-art variable selection procedure (LASSO) to identify the...

Every model presents an approximation of reality and thus modeling inevitably implies model risk. We quantify model risk in a non-parametric way, i.e., in terms of the divergence from a so-called nominal model. Worst-case risk is defined as the maximal risk among all models within a given...

Backtesting methods are statistical tests designed to uncover excessive risk-taking from financial institutions. We show in this paper that these methods are subject to the presence of model risk produced by a wrong specification of the conditional VaR model, and derive its effect on the...