This paper estimates a bivariate HEAVY system including daily and intra-daily volatility equations and its macro-augmented asymmetric power extension. It focuses on economic factors that exacerbate stock market volatility and represent major threats to financial stability. In particular, it...

We propose a novel method of Mean-Capital Requirement portfolio optimization. The optimization is performed using a parallel framework for optimization based on the Nondominated Sorting Genetic Algorithm II. Capital requirements for market risk include an additional stress component introduced...

This paper estimates a reduced-form model to assess the credit risk of General Insurance (GI) non-life firms in the UK. Compared to earlier studies, it uses a much larger sample including 30 years of data for 515 firms, and also considers a much wider set of possible determinants of credit risk....

Suppose that a group of agents having divergent expectations can share risks efficiently. We examine how this group should behave collectively to manage these risks. We show that the beliefs of the representative agent is in general a function of the group.s wealth level, or equivalently, that...

We study the interplay between tenure decisions, stock market investment and the public social security system. Housing equity not only serves a dual purpose as a consumption good and as an asset, but also provides insurance to buffer various risks in retirement. Our life cycle model captures...

We analyze the effect of the coach's gender on risk-taking in women sports teams using data taken from National Collegiate Athletic Association (NCAA) basketball games. We find that the coach's gender has a sizable and significant effect on risk-taking, a finding that is robust to several...

Tax administrations use machine learning to predict risk scores as a basis for selecting individual taxpayers for audit. Audits detect noncompliance immediately, but may also alter future filing behavior. This analysis is the first to estimate compliance effects of audits among high-risk wage...

In this study, we compare the out-of-sample forecasting performance of several modern Value-at- Risk (VaR) estimators derived from extreme value theory (EVT). Specifically, in a multi-asset study covering 30 years of stock, bond, commodity and currency market data, we analyse the accuracy of the...

We measure the economic risk of COVID-19 at a geo-spatially detailed resolution. In addition to data about the current prevalence of confirmed cases, we use data from 2014-2018 and a conceptual disaster risk model to compute measures for exposure, vulnerability, and resilience of the local...

We measure the economic risk of epidemics at a geo-spatially detailed resolution. In addition to data about the epidemic hazard prediction, we use data from 2014-2019 to compute measures for exposure, vulnerability, and resilience of the local economy to the shock of an epidemic. Using a battery...