IDEAS home Printed from https://ideas.repec.org/a/brc/brccej/v7y2022i3p171-193.html
   My bibliography  Save this article

Is Monetary Policy - Stock Price Behaviour Effect Sector-Sensitive? Evidence From Nigeria

Author

Listed:
  • Anthony Olugbenga ADARAMOLA

    (Department of Finance, Ekiti State University, Ado-Ekiti, Nigeria)

  • Peter Akinyemi KAYODE

    (Department of Banking & Finance, Adekunle Ajasin University, Akungba-Akoko, Nigeria)

Abstract

Monetary policy variables are theoretically expected to exert significant positive or negative effect on performance of the capital market. Most empirical studies on the relationship between monetary policy and stock prices in Nigeria have not taken cognizance of the fact that the relationship can be sector-sensitive. This study was conducted to examine effect of monetary policy on stock prices of listed firms in Nigeria from a two-sector comparative perspective: banks and manufacturing. Specifically, the study examined effects of seven selected monetary variables on stock prices of 15 banks and 15 manufacturing firms listed on the Nigerian Stock Exchange between Q1 of 2006 and Q4 of 2019. We employed panel dynamic ordinary least squares and panel causality models to analyze average quarterly stock price (STP) and monetary policy variables. We found that for banks, broad money supply (M2), monetary policy rate (MPR), exchange rate (EXCH) and interest on savings (SDR) significantly affect stock price negatively (p =0.0147; p =0.0000; p = 0.0110 and p = 0.0003 for the variables respectively). We also found that Treasury bill rate (TBR) significantly affects stock price positively (p = 0.0000) while cash reserve ratio (CRR) and lending rate (LDR) have insignificant effect on stock prices of banks. For manufacturing firms, MPR negatively and significantly affected stock prices (p=0.0110) but M2, Treasury bill rate, EXCH, LDR, CRR and SDR have insignificant effect on stock prices. All monetary policy variables except broad money supply have causal relationship with stock prices of banks but only exchange rate has causal relationship with with STP for manufacturing firms. We concluded that monetary policy significantly affects stock prices of Nigerian banks and manufacturing firms.. However, the effect is more pronounced in the banking industry than in manufacturing firms. It was also concluded that the effect of monetary policy on stock prices of banks is markedly different from that of manufacturing firms. The study recommended a disaggregated, sector sensitive monetary policy, a monetary policy re-appraisal and a reduction in monetary policy lags.

Suggested Citation

  • Anthony Olugbenga ADARAMOLA & Peter Akinyemi KAYODE, 2022. "Is Monetary Policy - Stock Price Behaviour Effect Sector-Sensitive? Evidence From Nigeria," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 7(3), pages 171-193.
  • Handle: RePEc:brc:brccej:v:7:y:2022:i:3:p:171-193
    as

    Download full text from publisher

    File URL: http://www.revec.ro/papers/220321.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. Lucia Alessi & Mark Kerssenfischer, 2019. "The response of asset prices to monetary policy shocks: Stronger than thought," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 661-672, August.
    3. William F. Sharpe, 1963. "A Simplified Model for Portfolio Analysis," Management Science, INFORMS, vol. 9(2), pages 277-293, January.
    4. Narayan, Seema & Narayan, Paresh Kumar, 2012. "Do US macroeconomic conditions affect Asian stock markets?," Journal of Asian Economics, Elsevier, vol. 23(6), pages 669-679.
    5. John Lintner, 1965. "Security Prices, Risk, And Maximal Gains From Diversification," Journal of Finance, American Finance Association, vol. 20(4), pages 587-615, December.
    6. S. Burcu Avci & Eray Yucel, 2017. "Effectiveness of monetary policy: evidence from Turkey," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 7(2), pages 179-213, August.
    7. Bekhet, Hussain Ali & Matar, Ali, 2013. "Co-integration and causality analysis between stock market prices and their determinates in Jordan," Economic Modelling, Elsevier, vol. 35(C), pages 508-514.
    8. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    9. Jaffe, Jeffrey F, 1974. "Special Information and Insider Trading," The Journal of Business, University of Chicago Press, vol. 47(3), pages 410-428, July.
    10. John Y. Campbell & Albert S. Kyle, 1993. "Smart Money, Noise Trading and Stock Price Behaviour," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(1), pages 1-34.
    11. J. Tobin, 1958. "Liquidity Preference as Behavior Towards Risk," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 25(2), pages 65-86.
    12. Patrick Olufemi Adeyeye & Olufemi Adewale Aluko & Stephen Oseko Migiro, 2017. "The nexus between stock price and foreign exchange rate: validating the portfolio-balance model in Nigeria," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 7(4), pages 363-377.
    13. Raed Walid Al-Smadi & Muthana Mohammad Omoush, 2019. "The long-Run and Short-Run Analysis between Stock Market Index and Macroeconomic Variables in Jordan: Bounds Tests Approach," International Business Research, Canadian Center of Science and Education, vol. 12(4), pages 50-60, April.
    14. Mike Dempsey, 2013. "The Capital Asset Pricing Model ( CAPM ): The History of a Failed Revolutionary Idea in Finance?," Abacus, Accounting Foundation, University of Sydney, vol. 49, pages 7-23, January.
    15. Rozeff, Michael S & Zaman, Mir A, 1988. "Market Efficiency and Insider Trading: New Evidence," The Journal of Business, University of Chicago Press, vol. 61(1), pages 25-44, January.
    16. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    17. Stephen Grenville, 1996. "Recent Developments in Monetary Policy: Australia and Abroad," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 29(1), pages 29-39, January.
    18. Eugene F. Fama & Kenneth R. French, 2004. "The Capital Asset Pricing Model: Theory and Evidence," Journal of Economic Perspectives, American Economic Association, vol. 18(3), pages 25-46, Summer.
    19. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    20. Lakonishok, Josef & Shapiro, Alan C., 1986. "Systematic risk, total risk and size as determinants of stock market returns," Journal of Banking & Finance, Elsevier, vol. 10(1), pages 115-132, March.
    21. Ehrmann, Michael & Fratzscher, Marcel, 2004. "Taking stock: monetary policy transmission to equity markets," Working Paper Series 354, European Central Bank.
    22. Fama, Eugene F, et al, 1969. "The Adjustment of Stock Prices to New Information," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(1), pages 1-21, February.
    23. Patelis, Alex D, 1997. "Stock Return Predictability and the Role of Monetary Policy," Journal of Finance, American Finance Association, vol. 52(5), pages 1951-1972, December.
    24. Michael D. Bordo & Michael J. Dueker & David C. Wheelock, 2008. "Inflation, Monetary Policy and Stock Market Conditions," NBER Working Papers 14019, National Bureau of Economic Research, Inc.
    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. Sonntag, Dominik, 2018. "Die Theorie der fairen geometrischen Rendite [The Theory of Fair Geometric Returns]," MPRA Paper 87082, University Library of Munich, Germany.
    2. Fernando Rubio, 2005. "Eficiencia De Mercado, Administracion De Carteras De Fondos Y Behavioural Finance," Finance 0503028, University Library of Munich, Germany, revised 23 Jul 2005.
    3. Mariia Bondarenko & Karel Brůna, 2021. "The Impact of FX Exposure on the Firm's Stock Market Return," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2021(1), pages 45-70.
    4. Shahzad, Syed Jawad Hussain & Zakaria, Muhammad & Raza, Naveed, 2014. "Sensitivity Analysis of CAPM Estimates: Data Frequency and Time Frame," MPRA Paper 60110, University Library of Munich, Germany.
    5. Cujean, Julien & Andrei, Daniel & Fournier, Mathieu, 2019. "The Low-Minus-High Portfolio and the Factor Zoo," CEPR Discussion Papers 14153, C.E.P.R. Discussion Papers.
    6. Michael Curran & Adnan Velic, 2020. "The CAPM, National Stock Market Betas, and Macroeconomic Covariates: a Global Analysis," Open Economies Review, Springer, vol. 31(4), pages 787-820, September.
    7. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    8. Rolf Bühner, 1998. "Unternehmensspaltung — Motive und Aktienmarktreaktionen," Schmalenbach Journal of Business Research, Springer, vol. 50(9), pages 809-840, September.
    9. Syed Jawad Hussain Shahzad & Saniya Khalid & Saba Ameer, 2016. "CAPM estimates: Can data frequency and time period lend a hand?," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 1-12, June.
    10. Guermat, Cherif & Freeman, Mark C., 2010. "A net beta test of asset pricing models," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 1-9, January.
    11. Amir Amel†Zadeh, 2011. "The Return of the Size Anomaly: Evidence from the German Stock Market," European Financial Management, European Financial Management Association, vol. 17(1), pages 145-182, January.
    12. John Y. Campbell, 2000. "Asset Pricing at the Millennium," Journal of Finance, American Finance Association, vol. 55(4), pages 1515-1567, August.
    13. Michael Dempsey, 2015. "Stock Markets, Investments and Corporate Behavior:A Conceptual Framework of Understanding," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number p1007, August.
    14. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
    15. Huang, Tao & Li, Junye, 2019. "Option-Implied variance asymmetry and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 21-36.
    16. Yi-Cheng Shih & Sheng-Syan Chen & Cheng-Few Lee & Po-Jung Chen, 2014. "The evolution of capital asset pricing models," Review of Quantitative Finance and Accounting, Springer, vol. 42(3), pages 415-448, April.
    17. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
    18. Keith Lam & Frank Li, 2008. "The risk premiums of the four-factor asset pricing model in the Hong Kong stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 18(20), pages 1667-1680.
    19. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2018. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Journal of Asian Economics, Elsevier, vol. 59(C), pages 29-47.
    20. İbrahim Ethem Güney & Abdullah Kazdal & Doruk Küçüksaraç & Muhammed Hasan Yılmaz, 2021. "Exchange Rate Sensitivity of Firm Value: Evidence from Nonfinancial Firms Listed on Borsa Istanbul," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 141-165, Springer.

    More about this item

    Keywords

    Monetary Policy; Banks; Manufacturing Firms; PDOLS; Causality;
    All these keywords.

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:brc:brccej:v:7:y:2022:i:3:p:171-193. 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: Cristina GANESCU (email available below). General contact details of provider: http://www.univcb.ro/ .

    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.