Describing financial crisis propagation through epidemic modelling on multiplex networks

This paper proposes a novel framework for modelling the spread of financial crises in complex networks, combining financial data, Extreme Value Theory and an epidemiological transmission model. We accommodate two key aspects of contagion modelling: fundamentals-based contagion, where the transmission is due to direct financial linkages, and...

Investigating the dependencies of individual overtopping volumes on vertical wall breakwaters under non-breaking waves

Wave overtopping of coastal structures is generally expressed in terms of average discharge and maximum overtopping volume. While substantial research can be found on the relationship of such variables with incident spectral characteristics and other geometrical dimensions, limited research has been done to identify the conditions for which...

Quantile co-movement and dependence between energy-focused sectors and artificial intelligence

This paper examines the dependence between Artificial Intelligence (AI) and eight energy-focused sectors (including renewable energy and coal) across different market conditions and investment horizons. This paper adopts both linear and non-linear models such as quantile regressions and quantile cross-spectral coherency models. Evidence from the...

A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar

In recent decades, substantial efforts have been devoted in flood monitoring, prediction, and risk analysis for aiding flood event preparedness plans and mitigation measures. Introducing an initial framework of spatially probabilistic analysis of flood research, this study highlights an integrated statistical copula and satellite data-based...

Lorenz-generated bivariate archimedean copulas

A novel generating mechanism for non-strict bivariate Archimedean copulas via the Lorenz curve of a non-negative random variable is proposed. Lorenz curves have been extensively studied in economics and statistics to characterize wealth inequality and tail risk. In this paper, these curves are seen as integral transforms generating increasing...

Estimation of the marginal expected shortfall under asymptotic independence

We study the asymptotic behavior of the marginal expected shortfall when the two random variables are asymptotic independent but positively associated, which is modeled by the so-called tail dependent coefficient. We construct an estimator of the marginal expected shortfall, which is shown to be asymptotically normal. The finite sample...

Characterizations of Multivariate Tail Dependence: On theory and inference to assess extremal dependence structures

This thesis gathers, develops and evaluates several characterizations of multivariate tail dependence. It is established that the stable tail dependence function (STDF) is a suitable copula-based dependence function that fully captures the multivariate extremal dependence structure in all dimensions d≥2 and can be used to visualize the tail...

Tail dependence in financial data: Modelling dependence in dynamic factor models with copulas and extreme value theory

In this thesis we model extreme log-returns on economic variables and apply this to Ortec Finance's model. These extreme log-returns are relevant for risk management applications such as Value-at-Risk and other measures of tail risk. We use extreme value theory to simulate economic variables with the desired tail behaviour. We pay special...