This paper provides a strategy for portfolio risk management by inferring extreme movements in financial markets. The core of the provided strategy is a statistical model for the joint tail distribution that attempts to capture accurately the data generating process through an extremal modelling...

We introduce a multivariate Hawkes process with constraints on its conditional density. It is a multivariate point process with conditional intensity similar to that of a multivariate Hawkes process but certain events are forbidden with respect to boundary conditions on a multidimensional...

This paper compares multivariate and univariate GARCH models to forecast portfolio value-at-risk (VaR). We provide a comprehensive look at the problem by considering realistic models and diversified portfolios containing a large number of assets, using both simulated and real data. Moreover, we...

Systematic improvements in mortality dependence in the survival distributions of insured lives, which is not accounted for in standard life tables and actuarial models used for annuity pricing and reserving. Systematic longevity risk also undermines the law of large numbers; a law that is relied...

This paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to fit them using a BEKK-type parameterization of the...

This paper proposes methods for testing the multivariate mixture of normals hypothesis. It uses multivariate measures of integrated variance to standardize (in a matrix sense) daily returns. Because replacing the unobserved integrated covariance by its estimator introduces a finite-sample...

This study investigates how top Finance & Accounting managers perceive the performance implications of adopting technologies to improve Purchasing processes. Based on a large-sample (454) survey, we employ multivariate data analysis techniques to specifically provide insights into how...

Data revisions in macroeconomic time series are typically studied in isolation ignoring the joint behaviour of revisions across different series. This ignores (i) the possibility that early releases of some series may help forecast revisions in other series and (ii) the problems statistical...

Forecasting aggregate demand is a crucial matter in all industrial sectors. In this paper, we provide the analytical prediction properties of top-down (TD) and bottom-up (BU) approaches when forecasting aggregate demand, using multivariate exponential smoothing as demand planning framework. We...

The last two decades have seen a growing concern about rising inequality. In a recent book (2012), Economics Nobel laureate Joseph Stiglitz argues that rising income inequality is one of the main factors underlying the economic and financial crisis in the United States. Wilkinson and Pickett...