International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12
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 Volume 12, Issue 1 (January 2025), Pages: 184-193

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 Original Research Paper

Impact of oil price and market volatility on the relationship between Saudi stock prices and illiquidity

 Author(s): 

 Hela Ben Soltane 1, 2, *

 Affiliation(s):

 1Department of Economics and Finance, College of Business Administration, University of Ha’il, Ha’il, Saudi Arabia
 2ESCT, LARIMRAF LR21ES29, University of Manouba, Manouba, 2010, Tunisia

 Full text

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-0615-4807

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2025.01.018

 Abstract

This study examines whether stock price sensitivity to illiquidity shocks changes over time in the Saudi stock market. Using structural break analysis, the research identifies shifts in the sensitivity of stock prices to illiquidity. A Markov switching model is then applied to understand these changes. The results indicate that small firms experience two distinct regimes, with illiquidity shocks reducing stock prices in the first regime ten times more than in the second. For large firms, stock price responses to illiquidity shocks vary across three regimes: in the first, prices decrease; in the second, prices remain stable; and in the third, prices drop sharply. Further analysis shows that higher market volatility significantly increases the impact of illiquidity shocks on small firms, while large firms are more sensitive to illiquidity shocks following periods of negative market performance. The study finds no evidence that changes in oil prices influence the relationship between illiquidity shocks and stock prices. These findings provide valuable insights for investors to predict periods of high illiquidity risk and implement effective investment strategies.

 © 2025 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Stock price sensitivity, Illiquidity shocks, Saudi stock market, Markov switching model, Oil price

 Article history

 Received 10 September 2024, Received in revised form 25 December 2024, Accepted 9 January 2025

 Acknowledgment

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Ben Soltane H (2025). Impact of oil price and market volatility on the relationship between Saudi stock prices and illiquidity. International Journal of Advanced and Applied Sciences, 12(1): 184-193

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 

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 References (21)

  1. Acharya VV and Pedersen LH (2005). Asset pricing with liquidity risk. Journal of Financial Economics, 77(2): 375-410. https://doi.org/10.1016/j.jfineco.2004.06.007   [Google Scholar]
  2. Acharya VV, Amihud Y, and Bharath ST (2013). Liquidity risk of corporate bond returns: Conditional approach. Journal of Financial Economics, 110(2): 358-386. https://doi.org/10.1016/j.jfineco.2013.08.002   [Google Scholar]
  3. Acharya VV, Schaefer S, and Zhang Y (2015). Liquidity risk and correlation risk: A clinical study of the General Motors and Ford downgrade of May 2005. The Quarterly Journal of Finance, 5(2): 1550006. https://doi.org/10.1142/S2010139215500068   [Google Scholar]
  4. Al-Najjar D (2022). Impact of the twin pandemics: COVID-19 and oil crash on Saudi exchange index. PLOS ONE, 17(5): e0268733. https://doi.org/10.1371/journal.pone.0268733   [Google Scholar] PMid:35594304 PMCid:PMC9122232
  5. Alshammari TS, Ismail MT, Al-wadi S, Saleh MH, and Jaber JJ (2020). Modeling and forecasting Saudi stock market volatility using wavelet methods. The Journal of Asian Finance, Economics and Business, 7(11): 83-93. https://doi.org/10.13106/jafeb.2020.vol7.no11.083   [Google Scholar]
  6. Alturki FA and Aldughaiyem AM (2020). Trading Saudi stock market shares using multivariate recurrent neural network with a long short-term memory layer. International Journal of Advanced Computer Science and Applications, 11(9): 522-528. https://doi.org/10.14569/IJACSA.2020.0110963   [Google Scholar]
  7. Amihud Y (2002). Illiquidity and stock returns: Cross-section and time-series effects. Journal of Financial Markets, 5(1): 31-56. https://doi.org/10.1016/S1386-4181(01)00024-6   [Google Scholar]
  8. Amihud Y and Noh J (2021). The pricing of the illiquidity factor's conditional risk with time-varying premium. Journal of Financial Markets, 56: 100605. https://doi.org/10.1016/j.finmar.2020.100605   [Google Scholar]
  9. Azar SA and Basmajian L (2013). Oil prices and the Kuwaiti and the Saudi stock markets: The contrast. International Journal of Economics and Financial Issues, 3(2): 294-304.   [Google Scholar]
  10. Bai J and Perron P (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1): 1-22. https://doi.org/10.1002/jae.659   [Google Scholar]
  11. Ben Soltane H and Naoui K (2021). Time‐varying responses of stock returns to market illiquidity: Stress scenario with regime‐switching framework. International Journal of Finance and Economics, 26: 1611-1622. https://doi.org/10.1002/ijfe.1866   [Google Scholar]
  12. Bensoltane H (2023). Price behavior of small and medium enterprises on the Saudi stock exchange in the face of market illiquidity. International Journal of Advanced and Applied Sciences, 10(6): 113-118. https://doi.org/10.21833/ijaas.2023.06.014   [Google Scholar]
  13. Brunnermeier MK and Pedersen LH (2009). Market liquidity and funding liquidity. The Review of Financial Studies, 22(6): 2201-2238. https://doi.org/10.1093/rfs/hhn098   [Google Scholar]
  14. Hamilton JD (2010). Regime switching models. In: Durlauf SN and Blume LE (Eds.), Macroeconometrics and time series analysis: The new Palgrave economics collection: 202–209. Palgrave Macmillan, London, UK. https://doi.org/10.1057/9780230280830_23   [Google Scholar] PMid:20479438
  15. Jensen GR and Moorman T (2010). Inter-temporal variation in the illiquidity premium. Journal of Financial Economics, 98(2): 338-358. https://doi.org/10.1016/j.jfineco.2010.05.008   [Google Scholar]
  16. Khamis R, Anasweh M, and Hamdan AMM (2018). Oil prices and stock market returns in oil exporting countries: Evidence from Saudi Arabia. International Journal of Energy Economics and Policy, 8(3): 301-306.   [Google Scholar]
  17. Lou X and Shu T (2017). Price impact or trading volume: Why is the Amihud (2002) measure priced? The Review of Financial Studies, 30(12): 4481-4520. https://doi.org/10.1093/rfs/hhx072   [Google Scholar]
  18. Pástor Ľ and Stambaugh RF (2003). Liquidity risk and expected stock returns. Journal of Political Economy, 111(3): 642-685. https://doi.org/10.1086/374184   [Google Scholar]
  19. Samontaray DP, Nugali S, and Sasidhar B (2014). A study of the effect of macroeconomic variables on stock market: Saudi perspective. International Journal of Financial Research, 5(4): 120-127. https://doi.org/10.5430/ijfr.v5n4p120   [Google Scholar]
  20. Tissaoui K, Kouki M, and Jouadi M (2018). Liquidity commonality under normal and a boom/bust conditions: Evidence from the Saudi stock exchange. International Journal of Advanced and Applied Sciences, 5(1): 37-48. https://doi.org/10.21833/ijaas.2018.01.006   [Google Scholar]
  21. Watanabe A and Watanabe M (2008). Time-varying liquidity risk and the cross section of stock returns. The Review of Financial Studies, 21(6): 2449-2486. https://doi.org/10.1093/rfs/hhm054   [Google Scholar]