Extended Value at Risk (EVaR) Measure for Market Risk

The fluctuation of shipping freight rates (freight rate risk) is an important source of market risk for all participants in the freight markets including hedge funds, commodity and energy producers. We measure the freight rate risk by the Value-at-Risk (VaR) approach. A range of parametric and non-parametric VaR methods is applied to various popular freight markets for dry and wet cargoes. Backtesting is conducted in two stages by means of statistical tests and a subjective loss function that uses the Expected Shortfall, respectively. We find that the simplest non-parametric methods should be used to measure freight rate risk. In addition, freight rate risk is greater in the wet cargoes markets. The margins in the growing freight derivatives markets should be set accordingly.

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Market Risk Measurement

A New World Post COVID-19 ◽

10.30687/978-88-6969-442-4/007 ◽

2020 ◽

Author(s):

Emese Lazar ◽

Ning Zhang

Keyword(s):

At Risk ◽

Value At Risk ◽

Preliminary Analysis ◽

Risk Measures ◽

Market Risk ◽

Capital Requirements ◽

Risk Measurement ◽

Regulatory Framework ◽

Bank Capital ◽

Bank Capital Requirements

This chapter presents a preliminary analysis on how some market risk measures dramatically increased during the COVID-19 pandemic, with measures computed over longer horizons experiencing more pronounced effects. We provide examples when regulatory market risk measurement proved to be suboptimal, overestimating risk. A further issue was the large number of Value-at-Risk ‘exceptions’ during the first few months of the crisis, which normally leads to overinflated bank capital requirements. The current regulatory framework should address these problems by suggesting improvements to the calculation of risk measures and/or by modifying the rules which determine capital requirements to make them appropriate and realistic in crisis situations.

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Major Crops Market Risk Based on Value at Risk Model in P.R. China

Sarhad Journal of Agriculture ◽

10.17582/journal.sja/2018/34.2.435.442 ◽

2018 ◽

Vol 34 (2) ◽

Cited By ~ 1

Author(s):

Abdur Rehman ◽

Wang Jian ◽

Noor Khan ◽

Raheel Saqib

Keyword(s):

At Risk ◽

Value At Risk ◽

Risk Model ◽

Market Risk

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Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets

Journal of Economics Finance and Administrative Science ◽

10.1108/jefas-03-2021-0009 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Ramona Serrano Bautista ◽

José Antonio Nuñez Mora

Keyword(s):

At Risk ◽

Latin America ◽

Stock Markets ◽

Value At Risk ◽

Predictive Performance ◽

Market Risk ◽

Global Market ◽

Garch Models ◽

Content Type ◽

Emerging Stock Markets

PurposeThis paper tests the accuracies of the models that predict the Value-at-Risk (VaR) for the Market Integrated Latin America (MILA) and Association of Southeast Asian Nations (ASEAN) emerging stock markets during crisis periods.Design/methodology/approachMany VaR estimation models have been presented in the literature. In this paper, the VaR is estimated using the Generalized Autoregressive Conditional Heteroskedasticity, EGARCH and GJR-GARCH models under normal, skewed-normal, Student-t and skewed-Student-t distributional assumptions and compared with the predictive performance of the Conditional Autoregressive Value-at-Risk (CaViaR) considering the four alternative specifications proposed by Engle and Manganelli (2004).FindingsThe results support the robustness of the CaViaR model in out-sample VaR forecasting for the MILA and ASEAN-5 emerging stock markets in crisis periods. This evidence is based on the results of the backtesting approach that analyzed the predictive performance of the models according to their accuracy.Originality/valueAn important issue in market risk is the inaccurate estimation of risk since different VaR models lead to different risk measures, which means that there is not yet an accepted method for all situations and markets. In particular, quantifying and forecasting the risk for the MILA and ASEAN-5 stock markets is crucial for evaluating global market risk since the MILA is the biggest stock exchange in Latin America and the ASEAN region accounted for 11% of the total global foreign direct investment inflows in 2014. Furthermore, according to the Asian Development Bank, this region is projected to average 7% annual growth by 2025.

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Selection of Value-at-Risk models for MENA Islamic indices

Journal of Islamic Accounting and Business Research ◽

10.1108/jiabr-07-2019-0122 ◽

2020 ◽

Vol 11 (9) ◽

pp. 1689-1708

Author(s):

Wassim Ben Ayed ◽

Ibrahim Fatnassi ◽

Abderrazak Ben Maatoug

Keyword(s):

At Risk ◽

Risk Management ◽

Value At Risk ◽

Prediction Models ◽

Market Risk ◽

Parametric Models ◽

Arch Model ◽

Var Models ◽

Content Type ◽

Cent Level

Purpose The purpose of this study is to investigate the performance of Value-at-Risk (VaR) models for nine Middle East and North Africa Islamic indices using RiskMetrics and VaR parametric models. Design/methodology/approach The authors test the performance of several VaR models using Kupiec and Engle and Manganelli tests at 95 and 99 per cent levels for long and short trading positions, respectively, for the period from August 10, 2006 to December 14, 2014. Findings The authors’ findings show that the VaR under Student and skewed Student distribution are preferred at a 99 per cent level VaR. However, at 95 per cent level, the VaR forecasts obtained under normal distribution are more accurate than those generated using models with fat-tailed distributions. These results suggest that VaR is a good tool for measuring market risk. The authors support the use of RiskMetrics during calm periods and the asymmetric models (Generalized Autoregressive Conditional Heteroskedastic and the Asymmetric Power ARCH model) during stressed periods. Practical implications These results will be useful to investors and risk managers operating in Islamic markets, because their success depends on the ability to forecast stock price movements. Therefore, because a few Islamic financial institutions use internal models for their capital calculations, the regulatory committee should enhance market risk disclosure. Originality/value This study contributes to the knowledge in this area by improving our understanding of market risk management for Islamic assets during the stress periods. Then, it highlights important implications regarding financial risk management. Finally, this study fills a gap in the literature, as most empirical studies dealing with evaluating VaR prediction models have focused on quantifying the model risk in the conventional market.

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