Search results

1 – 10 of over 7000

Abstract

Details

Tools and Techniques for Financial Stability Analysis
Type: Book
ISBN: 978-1-78756-846-4

Article
Publication date: 1 March 2000

KEVIN DOWD

This article outlines a subjective approach to estimating value at risk (VaR) and its related confidence intervals based on priors of the profit/loss distribution and its…

Abstract

This article outlines a subjective approach to estimating value at risk (VaR) and its related confidence intervals based on priors of the profit/loss distribution and its parameters. In the tradition of Bayesian statistics, this pro‐duces probability density functions for VaR that allow for subjective uncertainty. The author shows that imple‐menting this approach can be intuitive, straightforward, and applicable to any parametric VaR. One of the more difficult issues in this area is how to assess the precision of estimates: VaR estimation is usually straightforward, but estimating a confidence interval for a VaR estimate is not. This article suggests that, by inferring VaR from prior beliefs, rather than thinking of VaR as dependent on an “objective” P/L distribution, interpreting estimated confidence intervals is less problematic

Details

The Journal of Risk Finance, vol. 1 no. 4
Type: Research Article
ISSN: 1526-5943

Article
Publication date: 1 May 2006

Chu‐Hsiung Lin and Shan‐Shan Shen

This paper aims to investigate how effectively the value at risk (VaR) estimated using the student‐t distribution captures the market risk.

2424

Abstract

Purpose

This paper aims to investigate how effectively the value at risk (VaR) estimated using the student‐t distribution captures the market risk.

Design/methodology/approach

Two alternative VaR models, VaR‐t and VaR‐x models, are presented and compared with the benchmark model (VaR‐n model). In this study, we consider the Student‐t distribution as a fit to the empirical distribution for estimating the VaR measure, namely, VaR‐t method. Since the Student‐t distribution is criticized for its inability to capture the asymmetry of distribution of asset returns, we use the extreme value theory (EVT)‐based model, VaR‐x model, to take into account the asymmetry of distribution of asset returns. In addition, two different approaches, excess‐kurtosis and tail‐index techniques, for determining the degrees of freedom of the Student‐t distribution in VaR estimation are introduced.

Findings

The main finding of the study is that using the student‐t distribution for estimating VaR can improve the VaR estimation and offer accurate VaR estimates, particularly when tail index technique is used to determine the degrees of freedom and the confidence level exceeds 98.5 percent.

Originality/value

The main value is to demonstrate in detail how well the student‐t distribution behaves in estimating VaR measure for stock market index. Moreover, this study illustrates the easy process for determining the degrees of freedom of the student‐t, which is required in VaR estimation.

Details

The Journal of Risk Finance, vol. 7 no. 3
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 9 January 2007

Andrey Rogachev

The purpose of this paper is to consider the problem of using the Value‐at‐Risk (VaR) technique and examine its practical implementation by Swiss Private Banks.

2607

Abstract

Purpose

The purpose of this paper is to consider the problem of using the Value‐at‐Risk (VaR) technique and examine its practical implementation by Swiss Private Banks.

Design/methodology/approach

The paper is based on a survey originally undertaken in 2003 and updated in 2005. The research results provide details on how asset and portfolio managers understand and apply VaR methodology in their daily business.

Findings

From the banks' perspectives, VaR has both positive and negative points. It is like a common denominator for various risks. The reason is that VaR is used by portfolio managers as comparable risk measurement across different asset classes and business lines.

Originality/value

This analysis shows how banks can implement VaR concept more effectively through its practical implementation areas in: portfolio management decisions and asset allocation; the “what‐if” modeling of candidate traders; and measuring and monitoring market risk.

Details

The Journal of Risk Finance, vol. 8 no. 1
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 1 February 2004

KEVIN DOWD, DAVID BLAKE and ANDREW CAIRNS

One of the most significant recent developments in the risk measurement and management area has been the emergence of value at risk (VaR). The VaR of a portfolio is the…

Abstract

One of the most significant recent developments in the risk measurement and management area has been the emergence of value at risk (VaR). The VaR of a portfolio is the maximum loss that the portfolio will suffer over a defined time horizon, at a specified level of probability known as the VaR confidence level. The VaR has proven to be a very useful measure of market risk, and is widely used in the securities and derivatives sectors: a good example is the RiskMetrics system developed by J.P. Morgan. VaR measures based on systems such as RiskMetrics' sister, CreditMetrics, have also shown their worth as measures of credit risk, and for dealing with credit‐related derivatives. In addition, VaR can be used to measure cashflow risks and even operational risks. However, these areas are mainly concerned with risks over a relatively short time horizon, and VaR has had a more limited impact so far on the insurance and pensions literatures that are mainly concerned with longer‐term risks.

Details

The Journal of Risk Finance, vol. 5 no. 2
Type: Research Article
ISSN: 1526-5943

Open Access
Article
Publication date: 21 September 2022

Manuel Alonso Dos Santos, Manuel J. Sánchez-Franco, Eduardo Torres-Moraga and Ferran Calabuig Moreno

This study explores the effect of video assistant referee (VAR) sponsorship on spectator response and compares it with advertising and conventional sponsorship.

Abstract

Purpose

This study explores the effect of video assistant referee (VAR) sponsorship on spectator response and compares it with advertising and conventional sponsorship.

Design/methodology/approach

An experiment with 809 subjects is conducted by analyzing 20 one-minute video clip stimuli from a Premier League soccer game divided into four formats: two formats of VAR sponsorship, advertising, and conventional sponsorship.

Findings

The results show that the indicators of recall, credibility, and perceived congruence improve when the VAR sponsorship format is used.

Originality/value

This is the first manuscript to examine the effectiveness of a new type of sponsorship: VAR sponsorship. This manuscript provides metrics that will guide practitioners on whether to use this type of sponsorship.

Details

International Journal of Sports Marketing and Sponsorship, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1464-6668

Keywords

Abstract

Details

Understanding Financial Risk Management, Second Edition
Type: Book
ISBN: 978-1-78973-794-3

Book part
Publication date: 13 December 2013

Refet S. Gürkaynak, Burçin Kısacıkoğlu and Barbara Rossi

Recently, it has been suggested that macroeconomic forecasts from estimated dynamic stochastic general equilibrium (DSGE) models tend to be more accurate out-of-sample…

Abstract

Recently, it has been suggested that macroeconomic forecasts from estimated dynamic stochastic general equilibrium (DSGE) models tend to be more accurate out-of-sample than random walk forecasts or Bayesian vector autoregression (VAR) forecasts. Del Negro and Schorfheide (2013) in particular suggest that the DSGE model forecast should become the benchmark for forecasting horse-races. We compare the real-time forecasting accuracy of the Smets and Wouters (2007) DSGE model with that of several reduced-form time series models. We first demonstrate that none of the forecasting models is efficient. Our second finding is that there is no single best forecasting method. For example, typically simple AR models are most accurate at short horizons and DSGE models are most accurate at long horizons when forecasting output growth, while for inflation forecasts the results are reversed. Moreover, the relative accuracy of all models tends to evolve over time. Third, we show that there is no support to the common practice of using large-scale Bayesian VAR models as the forecast benchmark when evaluating DSGE models. Indeed, low-dimensional unrestricted AR and VAR forecasts may forecast more accurately.

Details

VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims
Type: Book
ISBN: 978-1-78190-752-8

Keywords

Book part
Publication date: 15 April 2020

Cindy S. H. Wang and Shui Ki Wan

This chapter extends the univariate forecasting method proposed by Wang, Luc, and Hsiao (2013) to forecast the multivariate long memory model subject to structural breaks…

Abstract

This chapter extends the univariate forecasting method proposed by Wang, Luc, and Hsiao (2013) to forecast the multivariate long memory model subject to structural breaks. The approach does not need to estimate the parameters of this multivariate system nor need to detect the structural breaks. The only procedure is to employ a VAR(k) model to approximate the multivariate long memory model subject to structural breaks. Therefore, this approach reduces the computational burden substantially and also avoids estimation of the parameters of the multivariate long memory model, which can lead to poor forecasting performance. Moreover, when there are multiple breaks, when the breaks occur close to the end of the sample or when the breaks occur at different locations for the time series in the system, our VAR approximation approach solves the issue of spurious breaks in finite samples, even though the exact orders of the multivariate long memory process are unknown. Insights from our theoretical analysis are confirmed by a set of Monte Carlo experiments, through which we demonstrate that our approach provides a substantial improvement over existing multivariate prediction methods. Finally, an empirical application to the multivariate realized volatility illustrates the usefulness of our forecasting procedure.

Book part
Publication date: 29 February 2008

Todd E. Clark and Michael W. McCracken

Small-scale VARs are widely used in macroeconomics for forecasting US output, prices, and interest rates. However, recent work suggests these models may exhibit…

Abstract

Small-scale VARs are widely used in macroeconomics for forecasting US output, prices, and interest rates. However, recent work suggests these models may exhibit instabilities. As such, a variety of estimation or forecasting methods might be used to improve their forecast accuracy. These include using different observation windows for estimation, intercept correction, time-varying parameters, break dating, Bayesian shrinkage, model averaging, etc. This paper compares the effectiveness of such methods in real-time forecasting. We use forecasts from univariate time series models, the Survey of Professional Forecasters, and the Federal Reserve Board's Greenbook as benchmarks.

Details

Forecasting in the Presence of Structural Breaks and Model Uncertainty
Type: Book
ISBN: 978-1-84950-540-6

1 – 10 of over 7000