Search Advanced

Quantitative Finance and Economics

2018, Volume 2, Issue 4: 884-903. doi: 10.3934/QFE.2018.4.884
Previous Article Next Article
Research article

The effects of oil prices on confidence and stock return in China, India and Russia

  • 1.
    Yildiz Technical University, FEAS, Department of Economics, Davutpasa Campus, Istanbul/Turkey
  • 2.
    Yildiz Technical University, Social Sciences Institute, Davutpasa Campus, Istanbul/Turkey
  • Received: 18 April 2018 Accepted: 26 October 2018 Published: 26 November 2018

  • JEL Codes: Q43, G12, E70

  • This study aims to investigate the relationships between oil price, business confidence and stock return for China, India and Russia by employing the Markov Switching Vector Auto Regressive(MS-VAR) and MS-Granger Causality(MS-GC) methods. For China, the causality relationship between business confidence and stock return differ from the results of Russia and India. For China, while there is unidirectional causality from stock return to business confidence for all regimes, in India there is the evidence of bidirectional causality in all regimes. For Russia, there is the evidence of a bidirectional causality between business confidence and stock return in the first regime, while there is none causality in the second regime. In all regimes for the selected countries, there is the evidence of a unidirectional causality from oil price to stock return. But there are different results between oil price and business confidence. The different results obtained for the selected countries are explained by the three different factors. One of the reasons is that the differences in oil reserves of the countries. The other one is the differences in oil demand of the countries' economies. The last one is that the selected countries have different business confidence that can be affected by various parameters of the economy.

    Citation: Melike E. Bildirici, Mesut M. Badur. The effects of oil prices on confidence and stock return in China, India and Russia[J]. Quantitative Finance and Economics, 2018, 2(4): 884-903. doi: 10.3934/QFE.2018.4.884

    Related Papers:

  • This study aims to investigate the relationships between oil price, business confidence and stock return for China, India and Russia by employing the Markov Switching Vector Auto Regressive(MS-VAR) and MS-Granger Causality(MS-GC) methods. For China, the causality relationship between business confidence and stock return differ from the results of Russia and India. For China, while there is unidirectional causality from stock return to business confidence for all regimes, in India there is the evidence of bidirectional causality in all regimes. For Russia, there is the evidence of a bidirectional causality between business confidence and stock return in the first regime, while there is none causality in the second regime. In all regimes for the selected countries, there is the evidence of a unidirectional causality from oil price to stock return. But there are different results between oil price and business confidence. The different results obtained for the selected countries are explained by the three different factors. One of the reasons is that the differences in oil reserves of the countries. The other one is the differences in oil demand of the countries' economies. The last one is that the selected countries have different business confidence that can be affected by various parameters of the economy.


    加载中
    [1] Anderson K, Brooks C, Katsaris A (2010) Speculative bubbles in the S&P 500: was the tech bubble confined to the tech sector? J Empir Financ 17: 345–361. doi: 10.1016/j.jempfin.2009.12.004
    [2] Apergis N, Miller SM (2009) Do structural oil-market shocks affects stock return. Energy Econ 31: 569–575. doi: 10.1016/j.eneco.2009.03.001
    [3] Arouri MEH, Rault C (2011) On the influence of oil prices on stock markets: evidence from panel analysis in GCC countries. Int J Financ Econ 3: 242–253.
    [4] Arouri MEH, Jouini J, Nguyen DK (2012) On the impacts of oil price fluctuations on European equity markets: volatility spillover and hedging effectiveness. Energy Econ 34: 611–617. doi: 10.1016/j.eneco.2011.08.009
    [5] Baker M, Wurgler J (2007) Investor sentiment in the stock market. J Econ Perspectives 21: 129–152. doi: 10.1257/jep.21.2.129
    [6] Beckman J, Belke A, Kühl M (2011) Global integration of central and eastern european financial markets-the role of economic sentiments. Rev Int Econ 19: 137–157. doi: 10.1111/j.1467-9396.2010.00937.x
    [7] Bildirici M (2012a) Economic growth and energy consumption in G7 countries: ms-var and ms-granger causality analysis. The J of Energy and Development 38: 1–30.
    [8] Bildirici M (2012b) The relationship between economic growth and electricity consumption in africa: ms-var and ms-granger causality analysis. The J of Energy and Development 37: 179–207.
    [9] Bildirici M (2013) Economic growth and electricity consumption: MS-VAR and MS-Granger causality analysis. OPEC Energy Rev 38: 447–476.
    [10] Brown GW, Cliff MT (2005) Investor sentiment and asset valuation. J of Business 78: 405–440. doi: 10.1086/427633
    [11] Campbell JY (1991) A variance decomposition for stock returns. Econ J 101: 157–179. doi: 10.2307/2233809
    [12] Chen NF, Roll RS, Ross A (1986) Economic Forces and the Stock Market. J of Business 59: 383–403. doi: 10.1086/296344
    [13] Chen SS (2010) Do higher oil prices push the stock market into bear territory? Energy Econ 32: 490–495. doi: 10.1016/j.eneco.2009.08.018
    [14] Ciner C (2001) Energy shocks and financial markets: nonlinear linkages. Studies in Non-Linear Dynamics and Econ 5: 203–212. doi: 10.1162/10811820160080095
    [15] Chang TP, Hu JL (2009) Incorporating a leading indicator into the trading rule through the markov-switching vector autoregression model. Appl Econ 16: 1255–1259.
    [16] Cong RG, Wei YM, Jiao JL et al. (2008) Relationships between oil price shocks and stock market: An empirical analysis from China. Energy Policy 36: 3544–3553. doi: 10.1016/j.enpol.2008.06.006
    [17] Degiannakis S, Filis G, Kizys R (2014) The effects of oil price shocks on stock market volatility: evidence from European data. Energy J 35: 35–56.
    [18] DG Sanco Final Report by Europe Economics (2007) An analysis of the issue of consumer detriment and the most appropriate methodologies to estimate it. 1–574. Available from: http://www.europe-economics.com/publications/study_consumer_detriment.pdf .
    [19] Ding Z, Liu Z, Zhang Y, et al. (2017) The contagion effect of international crude oil price fluctuations on chinese stock market investor sentiment. Appl Energy 187: 27–36. doi: 10.1016/j.apenergy.2016.11.037
    [20] Electronic Data Delivery System. Available from: https://evds2.tcmb.gov.tr/.
    [21] Energy Information Administration. Available from: https://www.eia.gov/.
    [22] Ewing B, Thmpson M (2007) Dynamic cyclical comovements of oil prices with industrial production, consumer prices, unemployment, and stock prices. Energy Policy 35: 5535–5540. doi: 10.1016/j.enpol.2007.05.018
    [23] European Central Bank Monthly Bulletin. 45–58. Available from: https://www.ecb.europa.eu/pub/pdf/mobu/mb201301en.pdf.
    [24] Faff RW, Brailsford TJ (1999) Oil price risk and the Australian stock market. J of Energy and Financ Development 4: 69–87. doi: 10.1016/S1085-7443(99)00005-8
    [25] Fallahi F, Rodriguez G (2007) Using markov-switching models to identify the link between unemployment and criminality. Available from: https://sciencessociales.uottawa.ca/economics/sites/socialsciences.uottawa.ca.economics/files/0701E.pdf.
    [26] Falahi F (2011) Causal relationship between energy consumption (ec) and gdp: a markov-switching (ms) causality. Energy 36: 4165–4170. doi: 10.1016/j.energy.2011.04.027
    [27] Fisher I (1906) The Nature of Capital and Income, New York, Macmillan.
    [28] Hamilton JD (1988) Rational-expectations econometric analysis of changes in regime: An investigation of the term structure of interest rates. J of Econ Dynamics and Control 12: 385–423. doi: 10.1016/0165-1889(88)90047-4
    [29] Hamilton JD (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econ 57: 357–384. doi: 10.2307/1912559
    [30] Hamilton JD (1990) Analysis of time series subject to changes in regime. J of Econ 45: 39–70. doi: 10.1016/0304-4076(90)90093-9
    [31] Hicks JR (1934a) Application of mathematical methods to the theory of risk. Econ 4: 194–5.
    [32] Hicks JR (1934b) A note on the elasticity of supply. Rev of Econ Studies 10: 31–7.
    [33] Huang RD, Masulis RW, Stoll HR (1996) Energy shocks and financial markets. J Futures Mark 16: 1–27. doi: 10.1002/(SICI)1096-9934(199602)16:1<1::AID-FUT1>3.0.CO;2-Q
    [34] Jones CM, Kaul G (1996) Oil and the stock markets. J Financ 51: 463–491. doi: 10.1111/j.1540-6261.1996.tb02691.x
    [35] Kang W, Ratti RA, Yoon KH (2015) The impact of oil price shocks on the stock market return and volatility relationship, Journal of International Financial Markets. Institutions and Money 34: 41–54. doi: 10.1016/j.intfin.2014.11.002
    [36] Kaul G, Seyhun HN (1990) Relative price variability, real shocks, and the stock market. The j of financ 45: 479–496. doi: 10.1111/j.1540-6261.1990.tb03699.x
    [37] Keynes JM (1936) The General Theory Of Employment, Interest And Money, Palgrave MacMillan, London.
    [38] Kilian L, Park C (2009) The impact of oil price shocks on the US stock market. Int Econ Rev 50: 1267–128. doi: 10.1111/j.1468-2354.2009.00568.x
    [39] Kling JL (1985) Oil Price Shocks and Stock-Market Behavior. J of Portfolio Management 12: 34–39. doi: 10.3905/jpm.1985.409034
    [40] Krolzig HM (1997a) International business cycles: Regime shifts in the stochastic process of economic growth. Applied Economics Discussion Paper 194, University of Oxford.
    [41] Krolzig HM (1997b) Markov Switching Vector Autoregressions. Modelling, Statistical Inference and Application to Business Cycle Analysis. Berlin: Springer.
    [42] Krolzig HM (1998) Econometric modelling of Markov-switching vector autoregressions using MSVAR for Ox. Discussion paper, Institute of Economics and Statistics, University of Oxford.
    [43] Krolzig HM (2000) Predicting Markov-switching vector autoregressive processes. Economics discussion paper 2000–W31, Nuffield College, Oxford.
    [44] Krolzig HM, Marcellino M, Mizon GE (2002) A Markov-switching vector equilibrium correction model of the UK labour market, In: Hamilton J.D. Raj B, Advances in Markov-Switching Models, Studies in Empirical Economics, Physica, Heidelberg.
    [45] Krolzig HM (2001) Business cycle measurement in the presence of structural change: International evidence. Int J Forecast 17: 349–368. doi: 10.1016/S0169-2070(01)00099-1
    [46] Lemmon M, Portniaguina E (2006) Consumer confidence and asset prices: some empirical evidence. Rev Financ Stud 19: 1499–1529. doi: 10.1093/rfs/hhj038
    [47] Malik F, Ewing BT (2009) Volatility transmission between oil prices and equity sector returns. Int Rev Financ Anal 18: 95–100. doi: 10.1016/j.irfa.2009.03.003
    [48] Miller JI, Ratti RA (2009) Crude oil and stock markets: stability, instability and bubbles. Energy Econ 31: 559–568. doi: 10.1016/j.eneco.2009.01.009
    [49] Nandha M, Faff R (2008) Does oil move equity prices? A global view. Energy Econ 30: 986–997.
    [50] Park J, Ratti RA (2008) Oil price shocks and stock markets in the US and 13 European countries. Energy Econ 30: 2587–2608. doi: 10.1016/j.eneco.2008.04.003
    [51] Qadan M, Nama H (2018) Investor sentiment and the price of oil. Energy Econ 69: 42–58. doi: 10.1016/j.eneco.2017.10.035
    [52] Sadorsky P (1999) Oil price shocks and stock market activity. Energy Econ 21:449–469. doi: 10.1016/S0140-9883(99)00020-1
    [53] Schmeling M (2009) Investor sentiment and stock returns: Some international evidence. J Empir Financ 16: 394–408. doi: 10.1016/j.jempfin.2009.01.002
    [54] Shigeki O (2017) Oil price shocks and stock markets in BRICs. The European J of Comparative Econ: EJCE 14: 29–45.
    [55] University of Michigan Surveys of Consumers. Available from: http://www.sca.isr.umich.edu/.
    [56] Vo M (2011) Oil and stock market volatility: a multivariate stochastic volatility perspective. Energy Econ 33: 956–965. doi: 10.1016/j.eneco.2011.03.005
    [57] Wei Y, Guo X (2017) Oil price shocks and china's stock market. Energy 140: 185–197. doi: 10.1016/j.energy.2017.07.137
    [58] Wei C (2003) Energy, the Stock Market, and the Putty-Clay Investment Model. Am Econ Rev 93: 311–323. doi: 10.1257/000282803321455313
    [59] Yahoo Finance. Available from: https://finance.yahoo.com/quote/DATA/.
    [60] Zak PJ, Knack S (2001) Trust and growth. The Econ J 111: 295–321. doi: 10.1111/1468-0297.00609
    [61] Zouaoui M (2011) How does investor sentiment affect stock market crises? evidence from panel data. The Fianc Rev 46: 723–747.
  • Reader Comments
  • © 2018 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Quantitative Finance and Economics
3.2 0.3

Metrics

Article views(4763) PDF downloads(922) Cited by(18)

Preview PDF
Download XML
Export Citation
Article outline

Figures and Tables

Tables(8)

Other Articles By Authors

Related pages

Tools

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog