Search results

1 – 2 of 2
To view the access options for this content please click here
Article
Publication date: 1 March 2006

Fotios C. Harmantzis, Linyan Miao and Yifan Chien

This paper aims to test empirically the performance of different models in measuring VaR and ES in the presence of heavy tails in returns using historical data.

Abstract

Purpose

This paper aims to test empirically the performance of different models in measuring VaR and ES in the presence of heavy tails in returns using historical data.

Design/methodology/approach

Daily returns of popular indices (S&P500, DAX, CAC, Nikkei, TSE, and FTSE) and currencies (US dollar vs Euro, Yen, Pound, and Canadian dollar) for over ten years are modeled with empirical (or historical), Gaussian, Generalized Pareto (peak over threshold (POT) technique of extreme value theory (EVT)) and Stable Paretian distribution (both symmetric and non‐symmetric). Experimentation on different factors that affect modeling, e.g. rolling window size and confidence level, has been conducted.

Findings

In estimating VaR, the results show that models that capture rare events can predict risk more accurately than non‐fat‐tailed models. For ES estimation, the historical model (as expected) and POT method are proved to give more accurate estimations. Gaussian model underestimates ES, while Stable Paretian framework overestimates ES.

Practical implications

Research findings are useful to investors and the way they perceive market risk, risk managers and the way they measure risk and calibrate their models, e.g. shortcomings of VaR, and regulators in central banks.

Originality/value

A comparative, thorough empirical study on a number of financial time series (currencies, indices) that aims to reveal the pros and cons of Gaussian versus fat‐tailed models and Stable Paretian versus EVT, in estimating two popular risk measures (VaR and ES), in the presence of extreme events. The effects of model assumptions on different parameters have also been studied in the paper.

Details

The Journal of Risk Finance, vol. 7 no. 2
Type: Research Article
ISSN: 1526-5943

Keywords

To view the access options for this content please click here
Article
Publication date: 5 May 2020

Qingfeng Meng, Yifan Zhang, Zhen Li, Weixiang Shi, Jun Wang, Yanhui Sun, Li Xu and Xiangyu Wang

The purpose of this paper is to summarize the current applications of BIM, the integration of related technologies and the tendencies and challenges systematically.

Abstract

Purpose

The purpose of this paper is to summarize the current applications of BIM, the integration of related technologies and the tendencies and challenges systematically.

Design/methodology/approach

Using quantitative and qualitative bibliometric statistical methods, the current mode of interaction between BIM and other related technologies is summarized.

Findings

This paper identified 24 different BIM applications in the life cycle. From two perspectives, the implementation status of BIM applications and integrated technologies are respectively studied. The future industry development framework is drawn comprehensively. We summarized the challenges of BIM applications from the perspectives of management, technology and promotion, and confirmed that most of the challenges come from the two driving factors of promotion and management.

Research limitations/implications

The technical challenges reviewed in this paper are from the collected literature we have extracted, which is only a part of the practical challenges and not comprehensive enough.

Practical implications

We summarized the current mode of interactive use of BIM and sorted out the challenges faced by BIM applications to provide reference for the risks and challenges faced by the future industry.

Originality/value

There is little literature to integrate BIM applications and to establish BIM related challenges and risk frameworks. In this paper, we provide a review of the current implementation level of BIM and the risks and challenges of stakeholders through three aspects of management, technology and promotion.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 8
Type: Research Article
ISSN: 0969-9988

Keywords

1 – 2 of 2