IDEAS home Printed from https://ideas.repec.org/a/ris/statec/0093.html
   My bibliography  Save this article

Modeling and assessing systematic risk in stock markets in major oil exporting countries

Author

Listed:
  • Onour , Ibrahim A.

    (University of Khartoum)

Abstract

Introduction. This paper aims to assess time variability of beta coefficients (systematic risk) of Capital Asset Pricing Model (CAPM) using data from five key sectors in Saudi Arabia and Kuwait stock markets. Material and methods. To assess time – varying systematic risk we employed symmetric as well as asymmetric conditional volatility specifications to account for skewness and leptkurtosis of high frequency financial time series to better specify conditional higher moments. Results & discussions. The results of the paper support significant evidence of time-varying beta coefficients for all sectors included in the study, in particular the banking sector, and relatively with a lesser degree ,the food, and the service sectors in both countries. For the banking sector in Saudi Arabia, the beta coefficients variability during the sample period estimated between (0.18 to 22.1), and also for Kuwait stock market the beta coefficient of the banking sector variability estimated between (0.16 to 22.1). This result invalidates, at least in the context of the sample country’s banking sectors, the standard application of (CAPM) that assumes constant beta coefficients. Also indicated in the paper, time-varying beta estimates are consistent with a modified version of CAPM prediction that is portfolios with wider range of beta variations expected to yield higher return values and those with lower range of beta variations yield lower returns. Conclusion. In this new context, risk is no longer is a point estimate as implied by the standard CAPM model, but it is a range of values. Our findings also show the size and the range of beta variations are sensitive to skewness and fat tailedness that characterize asset returns distribution.

Suggested Citation

  • Onour , Ibrahim A., 2021. "Modeling and assessing systematic risk in stock markets in major oil exporting countries," Economic Consultant, Roman I. Ostapenko, vol. 35(3), pages 18-29.
  • Handle: RePEc:ris:statec:0093
    as

    Download full text from publisher

    File URL: https://statecounsellor.files.wordpress.com/2021/08/210303.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Victor S.H. Wong & Suzanna El Massah, 2018. "Recent Evidence on the Oil Price Shocks on Gulf Cooperation Council Stock Markets," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 25(2), pages 297-312, May.
    2. Antonio Pacifico, 2019. "Structural Panel Bayesian VAR Model to Deal with Model Misspecification and Unobserved Heterogeneity Problems," Econometrics, MDPI, vol. 7(1), pages 1-24, March.
    3. Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(4), pages 465-487, December.
    4. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.
    5. Adrian, Tobias & Franzoni, Francesco, 2009. "Learning about beta: Time-varying factor loadings, expected returns, and the conditional CAPM," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 537-556, September.
    6. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    7. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    8. Rabemananjara, R & Zakoian, J M, 1993. "Threshold Arch Models and Asymmetries in Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 31-49, Jan.-Marc.
    9. Roberto Casarin & German Molina & Enrique ter Horst, 2019. "A Bayesian time varying approach to risk neutral density estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(1), pages 165-195, January.
    10. Berna Aydoğan & Gökçe Tunç & Tezer Yelkenci, 2017. "The impact of oil price volatility on net-oil exporter and importer countries’ stock markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 7(2), pages 231-253, August.
    11. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    12. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5‐6), pages 523-554, June.
    13. McKenzie, Michael D. & Brooks, Robert D. & Faff, Robert W. & Ho, Yew Kee, 2000. "Exploring the economic rationale of extremes in GARCH generated betas The case of U.S. banks," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(1), pages 85-106.
    14. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    15. Yudong Wang & Li Liu, 2016. "Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging," Empirical Economics, Springer, vol. 50(4), pages 1481-1509, June.
    16. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
    17. Murad A. Bein, 2019. "Interrelationship between crude oil and the stock markets of major demanders and suppliers in emerging and developed markets," Applied Economics Letters, Taylor & Francis Journals, vol. 26(15), pages 1247-1252, September.
    18. Brooks, Robert D. & Faff, Robert W. & Ariff, Mohamed, 1998. "An investigation into the extent of beta instability in the Singapore stock market," Pacific-Basin Finance Journal, Elsevier, vol. 6(1-2), pages 87-101, May.
    19. Jun Yu, 2002. "Forecasting volatility in the New Zealand stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 12(3), pages 193-202.
    20. Chinazaekpere Nwani & Jacob Bassey Orie, 2016. "Economic growth in oil-exporting countries: Do stock market and banking sector development matter? Evidence from Nigeria," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1153872-115, December.
    21. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    22. Salah A. Nusair & Jamal A. Al-Khasawneh, 2018. "Oil price shocks and stock market returns of the GCC countries: empirical evidence from quantile regression analysis," Economic Change and Restructuring, Springer, vol. 51(4), pages 339-372, November.
    23. Syed Abuzar Moonis & Ajay Shah, 2003. "Testing for Time-variation in Beta in India," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 2(2), pages 163-180, May.
    24. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    25. Haroon Mumtaz & Konstantinos Theodoridis, 2018. "The Changing Transmission of Uncertainty Shocks in the U.S," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(2), pages 239-252, April.
    26. Onour, Ibrahim, 2008. "Forward-Looking Beta Estimates:Evidence from an Emerging Market," MPRA Paper 14992, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ibrahim Onour, "undated". "Exploring Stability of Systematic Risk: Sectoral Portfolio Analysis," API-Working Paper Series 1002, Arab Planning Institute - Kuwait, Information Center.
    2. Onour, Ibrahim, 2008. "Forward-Looking Beta Estimates:Evidence from an Emerging Market," MPRA Paper 14992, University Library of Munich, Germany.
    3. Dr. Ibrahim Onour, "undated". "The Global Financial Crisis and Equity Markets in Middle East Oil Exporting Countries," API-Working Paper Series 1009, Arab Planning Institute - Kuwait, Information Center.
    4. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    5. Abounoori, Esmaiel & Elmi, Zahra (Mila) & Nademi, Younes, 2016. "Forecasting Tehran stock exchange volatility; Markov switching GARCH approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 264-282.
    6. Emanuela Ciapanna & Marco Taboga, 2019. "Bayesian Analysis of Coefficient Instability in Dynamic Regressions," Econometrics, MDPI, vol. 7(3), pages 1-32, June.
    7. Taufiq Choudhry & Hao Wu, 2008. "Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time-varying beta," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 670-689.
    8. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
    9. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    10. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    11. Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Parameterizing Unconditional Skewness in Models for Financial Time Series," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 208-230, Spring.
    12. Onour, Ibrahim, 2009. "Natural Gas markets:How Sensitive to Crude Oil Price Changes?," MPRA Paper 14937, University Library of Munich, Germany.
    13. Zhao, Yixiu & Upreti, Vineet & Cai, Yuzhi, 2021. "Stock returns, quantile autocorrelation, and volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 73(C).
    14. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    15. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
    16. Malay Bhattacharyya & Dileep Kumar M & Ramesh Kumar, 2009. "Optimal sampling frequency for volatility forecast models for the Indian stock markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 38-54.
    17. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    18. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    19. Benjamin Beckers & Helmut Herwartz & Moritz Seidel, 2017. "Risk forecasting in (T)GARCH models with uncorrelated dependent innovations," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 121-137, January.
    20. Francesco Audrino & Fabio Trojani, 2006. "Estimating and predicting multivariate volatility thresholds in global stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 345-369, April.

    More about this item

    Keywords

    beta; CAPM; GARCH; volatility; asymmetry;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:statec:0093. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Roman I. Ostapenko (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.