Search results

1 – 3 of 3
To view the access options for this content please click here
Article
Publication date: 1 July 2005

Sergio M. Focardi and Frank J. Fabozzi

This paper seeks to discuss a modeling tool for explaining credit‐risk contagion in credit portfolios.

Downloads
2801

Abstract

Purpose

This paper seeks to discuss a modeling tool for explaining credit‐risk contagion in credit portfolios.

Design/methodology/approach

Presents a “collective risk” model that models the credit risk of a portfolio, an approach typical of insurance mathematics.

Findings

ACD models are self‐exciting point processes that offer a good representation of cascading phenomena due to bankruptcies. In other words, they model how a credit event might trigger other credit events. The model herein discussed is proposed as a robust global model of the aggregate loss of a credit portfolio; only a small number of parameters are required to estimate aggregate loss.

Originality/value

Discusses a modeling tool for explaining credit‐risk contagion in credit portfolios.

Details

The Journal of Risk Finance, vol. 6 no. 3
Type: Research Article
ISSN: 1526-5943

Keywords

To view the access options for this content please click here
Article
Publication date: 1 April 2003

SERGIO M. FOCARDI and FRANK J. FABOZZI

Fat‐tailed distributions have been found in many financial and economic variables ranging from forecasting returns on financial assets to modeling recovery distributions…

Abstract

Fat‐tailed distributions have been found in many financial and economic variables ranging from forecasting returns on financial assets to modeling recovery distributions in bankruptcies. They have also been found in numerous insurance applications such as catastrophic insurance claims and in value‐at‐risk measures employed by risk managers. Financial applications include:

Details

The Journal of Risk Finance, vol. 5 no. 1
Type: Research Article
ISSN: 1526-5943

To view the access options for this content please click here
Article
Publication date: 10 May 2019

Peterson Owusu Junior, George Tweneboah, Kola Ijasan and Nagaratnam Jeyasreedharan

This paper aims to contribute to knowledge by investigating the return behaviour of seven global real estate investment trusts (REITs) with respect to the appropriate…

Abstract

Purpose

This paper aims to contribute to knowledge by investigating the return behaviour of seven global real estate investment trusts (REITs) with respect to the appropriate distributional fit that captures tail and shape characteristics. The study adds to the knowledge of distributional properties of seven global REITs by using the generalised lambda distribution (GLD), which captures fairly well the higher moments of the returns.

Design/methodology/approach

This is an empirical study with GLD through three rival methods of fitting tail and shape properties of seven REIT return data from January 2008 to November 2017. A post-Global Financial Crisis (GFC) (from July 2009) period fits from the same methods are juxtaposed for comparison.

Findings

The maximum likelihood estimates outperform the methods of moment matching and quantile matching in terms of goodness-of-fit in line with extant literature; for the post-GFC period as against the full-sample period. All three methods fit better in full-sample period than post-GFC period for all seven countries for the Region 4 support dynamics. Further, USA and Singapore possess the strongest and stronger infinite supports for both time regimes.

Research limitations/implications

The REITs markets, however, developed, are of wide varied sizes. This makes comparison less than ideal. This is mitigated by a univariate analysis rather than multivariate one.

Practical implications

This paper is a reminder of the inadequacy of the normal distribution, as well as the mean, variance, skewness and kurtosis measures, in describing distributions of asset returns. Investors and policymakers may look at the location and scale of GLD for decision-making about REITs.

Originality/value

The novelty of this work lies with the data used and the detailed analysis and for the post-GFC sample.

Details

Journal of European Real Estate Research , vol. 12 no. 3
Type: Research Article
ISSN: 1753-9269

Keywords

1 – 3 of 3