Modelling Value at Risk: Evidence from the Saudi Stock Market

  • Khalafalla Ahmed Mohamed Arabi King Khalid University
  • Hemeda Mohamed Abdelmageed King Khalid University
Keywords: Backtest, Normal distribution, TASI, Value at Risk, worst loss



This paper aims to estimate Value at Risk (VaR) of Tadawul All Shares Index of Saudi Stock Market (TASI) over the period January 2004 – December 2017. It applies the following methods, empirical quartile, historical simulation (HS), and percentile, parametric via delta normal, GARCH, IGARCH, Monte Carlo simulation and bootstrapping simulation. It uses 5% and 1% critical value under Normal distribution.  Back- testing based on likelihood ratio LR accepted empirical quartile at both five and one percent, while accepting delta normal, historical simulation, percentile, IGARCH, and Monte Carlo at one percent. The worst loss obtained is approximately 4%.

Author Biographies

Khalafalla Ahmed Mohamed Arabi, King Khalid University

College of Administrative and Financial Studies, Department of Business Administration


Hemeda Mohamed Abdelmageed, King Khalid University

College of Admistrative and Financial Studies, Department of Accounting

Assistant Professor


Adabi1, Mehrara, Mohsen and Mohammadi, Shapour (2015) Evaluation Approaches of Value at Risk for Tehran Stock Exchange Iran. Econ. Rev. Vol.19, No.1, 2015. P.41-62

Alfi, Ayman F. and Mishra, Tapas K. (2014) Dynamics of Investor Risk Behavior in Emerging Stock Markets: Evidence from Saudi Arabia

Aloui, Chaker and Ben Hemida, Hala (2015) Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models Czech Journal of Economics and Finance, 65, no. 1-

Bogdan, Sinisa, Suzana Baresa, and Zoran Ivanovic. (2015) Estimating Risk on the Capital Market with VaR Method. UTMS Journal of Economics 6 (1): 165–175. 165 Estimating Risk on the Capital Market with the Value at Risk Method

Bucevska, Vesna (2013) an Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange Business Systems Research Vol. 4 No. 1

Chang Hae-Ching, Chen, Cheng-TE, Hsieh, and Chin-Shan (2017) Forecasting of the Value at Risk by using Percentile of Cluster Method論文成果彙編/206.pdf

Chena, Qi and Chen Rongda (2013) Method of Value-at-Risk and empirical research for Shanghai stock market

Cheung, Yun Hsing and Powell Robert J. (2012) anybody can do Value at Risk: A Teaching Study using Parametric Computation and Monte Carlo Simulation Volume 6 | Issue 5 Article 7

Chen, Xibei () Empirical Research on Value-at-Risk Methods of Chinese Stock Indexes

Čorkalo, Šime (2011) Comparison of Value at Risk Approached on Stock Portfolio Croatian Operational Research Review (CRORR), Vol. 2

Diedwardo, Mike, Mad Quant ttps://

DuttaA, Debashis and Basabi Bhattacharya (2006) Bootstrapped Historical Simulation Value at Risk Approach to S & P CNX Nifty

Fernandez Viviana (2003) "Extreme Value Theory and Value at Risk" Revista de Analisis Economico Vol. 18 No. 1 pp 57-85

Goorbergh, Rob van den and Vlaar, Peter (1999) Value-at-Risk Analysis of Stock Returns Historical Simulation, Variance Techniques or Tail Index Estimation

HHarper, David Calculation of Conditional Value at Risk:;

Harper, David: Bootstrapping

Hurlin, Christophe and Tokpavi, Sessi (2014) Backtesting Value-at-Risk Accuracy: A New Simple Test. International Journal of Forecasting.

Fabio Lamantia, Sergio Ortobelli, Svetlozar Rachev () An Empirical Comparison among VaR Models and Time Rules with Elliptical and Stable Distributed Returns

sieha, Chin-Shan and Choub, Jian-Hsin, () Forecasting Value at Risk (VAR) in the Shanghai Stock Market Using the Hybrid Method

Holton, Glyon (2017) How to Calculate Value-at-Risk – Step by Step

Linsmeier Thomas J. and Pearson Neil D. (1996) “Risk Management: an Introduction to Value at Risk”

ChampaignManfredo, Mark R. and Leuthold Raymond M (2016) Analysis: A Review and the Potential for Agricultural Applications Review of Agricultural Economics--Volume 21, Number 1--Pages 99-111 Value-at-Risk

Monteiro, Paulo (2004) Forecasting Hedge Funds Volatility: Value at Risk Approach

Norling, Nicklas and Selling, Daniel (2012) Empirical Evaluation of Value-at-Risk during the Financial Crisis.

Provizionatou, Vikentia, Markose, Sheri and Menkens, Olaf (2005) Empirical Scaling Rules for Value-at-Risk (VaR)

Rob van den Goorbergh and Peter Vlaar (1999) Value-at-Risk Analysis of Stock Returns Historical Simulation, Variance Techniques or Tail Index Estimation

Rogachev, Andrey (2002) Dynamic Value-at-Risk

Samanta, G. P (2015) How Good is the Transformation-Based Approach to Estimate Value at Risk Simulation and Empirical Results. National Stock Exchange India WP/16/2015

Smolović, Cerović Julija, Milena Lipovina-Božović & Vujošević, Saša (2017) GARCH models in value at risk estimation: empirical evidence from the Montenegrin stock


Tsay, Ruey S. (2002) Analysis of Financial Time Series John Wiley & Sons, INC

Uryasev, Stan (2011) VaR vs CVaR in Risk Management and Optimization

Yoon, Seong-Min,, Woo Hyojin and Kang Sang Hoon (2011) VaR Analysis for the Shanghai Stock Market International Conference on Advancements in Information Technology With workshop of ICBMG

Zhang, Bingqiu (2016) Stock Market Risk Measurement Method Based on Improved Genetic Algorithm Chemical Engineering Transactions Vol. 51

How to Cite
Arabi, K. A. M., & Abdelmageed, H. M. (2018). Modelling Value at Risk: Evidence from the Saudi Stock Market. Archives of Business Research, 6(6), 339-352.