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Do Presidential Elections Affect Stock Market Returns In Nigeria?

Author

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  • Shehu U.R. Aliyu

    (Department of Economics, Bayero University Kano, Nigeria)

Abstract

Evidences thrive on the effects of political regimes and presidential elections on stock market returns. This paper investigates the effects of presidential elections on stock returns around the election periods at the Nigerian Stock Exchange (NSE) market. A sample of five (5) months each for a total of six (6) presidential elections held between 1999 and 2019 was employed. Returns were calculated using daily closing prices of NSE’s all share index (ASI). Afterwards, the regime heteroskedastic Markov switching model was found fit for the data. Empirical results typify the daily stock returns in terms of bear (low) and bull (high) regimes. Bear regime (1) leads across the 6 election horizons with lower volatility while the bull regime (2) records higher volatility in addition to more positive returns. Specifically, presidential election impacts positively on stock returns only during the 2011 election. Besides, findings show that stock market returns during presidential elections when the PDP government was in office were bearish whereas the market returns were bullish for elections held when the APC government was in office. To achieve stability in the market and the economy at large, restraints on the side of fiscal authority and setting limits on election/campaign spending could help in forestalling upheavals in the market around presidential elections in Nigeria.

Suggested Citation

  • Shehu U.R. Aliyu, 2019. "Do Presidential Elections Affect Stock Market Returns In Nigeria?," West African Journal of Monetary and Economic Integration, West African Monetary Institute, vol. 19(1), pages 40-56, June.
  • Handle: RePEc:wam:journl:v:19:y:2019:i:1:p:40-56
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    1. Lee A. Smales, 2017. "“Brexit”: A Case Study in the Relationship Between Political and Financial Market Uncertainty," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 451-459, September.
    2. Ahmed, Walid M.A., 2018. "How do Islamic versus conventional equity markets react to political risk? Dynamic panel evidence," International Economics, Elsevier, vol. 156(C), pages 284-304.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Andreas Haupenthal & Matthias Neuenkirch, 2017. "Grexit news and stock returns," Applied Economics, Taylor & Francis Journals, vol. 49(39), pages 3891-3898, August.
    5. Aliyu, Shehu Usman Rano, 2011. "Reactions of stock market to monetary policy shocks during the global financial crisis: the Nigerian case," MPRA Paper 35581, University Library of Munich, Germany, revised 28 Dec 2011.
    6. Booth, James R. & Booth, Lena Chua, 2003. "Is presidential cycle in security returns merely a reflection of business conditions?," Review of Financial Economics, Elsevier, vol. 12(2), pages 131-159.
    7. In Huh & Ju Hyun Pyun, 2018. "Does Nuclear Uncertainty Threaten Financial Markets? The Attention Paid to North Korean Nuclear Threats and Its Impact on South Korea's Financial Markets," Asian Economic Journal, East Asian Economic Association, vol. 32(1), pages 55-82, March.
    8. Blomberg, S. Brock & Hess, Gregory D., 2003. "Is the political business cycle for real?," Journal of Public Economics, Elsevier, vol. 87(5-6), pages 1091-1121, May.
    9. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    10. Christopher N. Ekong & Ekpeno L. Effiong, 2015. "Oil Price Shocks and Nigeria’s Macroeconomy: Disentangling the Dynamics of Crude Oil Market Shocks," Global Business Review, International Management Institute, vol. 16(6), pages 920-935, December.
    11. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    12. Walid M.A. Ahmed, 2018. "How do Islamic versus conventional equity markets react to political risk? Dynamic panel evidence," International Economics, CEPII research center, issue 156, pages 284-304.
    13. Rogoff, Kenneth, 1990. "Equilibrium Political Budget Cycles," American Economic Review, American Economic Association, vol. 80(1), pages 21-36, March.
    14. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    15. 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.
    16. Li, Qingyuan & Li, Si & Xu, Li, 2018. "National elections and tail risk: International evidence," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 113-128.
    17. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 60-67, January.
    18. Christopher A. Hartwell, 2018. "The effect of political volatility on capital markets in EU accession and neighborhood countries," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 21(4), pages 260-280, October.
    19. Aliyu, Shehu Usman Rano, 2009. "Stock Prices and Exchange Rate Interactions in Nigeria: An Intra-Global Financial Crisis Maiden Investigation," MPRA Paper 13283, University Library of Munich, Germany, revised 09 Feb 2009.
    20. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    21. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    22. Olivier Jean Blanchard & Christopher G. Collins & Mohammad Jahan-Parvar & Thomas Pellet & Beth Anne Wilson, 2018. "Why Has the Stock Market Risen So Much Since the US Presidential Election?," International Finance Discussion Papers 1235, Board of Governors of the Federal Reserve System (U.S.).
    23. William D. Nordhaus, 1975. "The Political Business Cycle," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 42(2), pages 169-190.
    24. Shehu Usman Rano Aliyu, 2009. "Stock Prices and Exchange Rate Interactions in Nigeria: A Maiden Intra-Global Financial Crisis Investigation," The IUP Journal of Financial Economics, IUP Publications, vol. 0(3 & 4), pages 7-23, September.
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    Cited by:

    1. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
    2. Yaya, OlaOluwa S & Adekoya, Oluwasegun B. & Adesiyan, Femi, 2020. "The Persistence of Stock Market Returns during the Presidential elections in Nigeria," MPRA Paper 99390, University Library of Munich, Germany.

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    More about this item

    Keywords

    Presidential election; stock market returns; Markov regime switching model; dummy variable;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • P16 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Capitalist Institutions; Welfare State

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