In this paper we analyse the properties of hierarchical Archimedean copulas. This class is a generalisation of the Archimedean copulas and allows for general non-exchangeable dependency structures. We show that the structure of the copula can be uniquely recovered from all bivariate margins. We...

Zero expenditure poses several challenges when estimating demand systems. Zero expenditure on energy goods occur due to limited opportunity to consume the good or because the household chooses not to use all available equipment (corner solution). In this paper we develop a method to estimate an...

While the Generalized Error Distribution (GED) has been used quite extensively in time series applications and has demonstrated a sound flexibility in the estimation process, there is so far no attempt to use this function in the construction of Copulas. Copulas are probability functions that...

Copulas are a general tool to construct multivariate distributions and to investigate dependence structure between random variables. However, the concept of copula is not popular in Finance. In this paper, we show that copulas can be extensively used to solve many financial problems.

This paper surveys several applications of parametric copulas to market portfolios, credit portfolios, and enterprise risk management in the banking industry, focusing on how to capture stressed conditions. First, we show two simple applications for market portfolios: correlation structures for...

We apply Bayesian updating theory to model how decision-makers may gradually learn about climate change and make use of this information in making adaptive forest management decisions. We develop modelling steps to i) simulate observation of a multi-dimensional climate system, ii) apply updating...

In this paper we study the existence of arbitrage opportunities in a multi-asset market when risk-neutral marginal distributions of asset prices are known. We first propose an intuitive characterization of the absence of arbitrage opportunities in terms of copula functions. We then address the...

In this paper, we introduce a new class of multivariate distributions as an extension of the normal variance–mean mixture distributions class. The new class results from a variance-mean mixture of the skew normal and the generalized inverse Gaussian distributions. The new class is very...

We propose a new sequential procedure for estimating multivariate distributions in cases when conventional maximum likelihood has too many parameters and is therefore inaccurate or non-operational. The procedure constructs a multivariate distribution and its pseudo-likelihood sequentially, in...

This paper examines the marginal distributions of stocks and bonds, and a copula between the movement of stock prices and interest rates. Because some widely used aggregation methods such as variance-covariance tend to underestimate the risk of an aggregated portfolio, a copula is utilized for...