IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v9y2021i11p195-d671113.html
   My bibliography  Save this article

A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of the FTSE and S&P500 Indexes

Author

Listed:
  • David E. Allen

    (School of Mathematics and Statistics, University of Sydney, Sydney, NSW 2006, Australia
    Department of Finance, College of Management, Asia University, Taichung City 41354, Taiwan
    School of Business and Law, Edith Cowan University, Joondalup, WA 6027, Australia)

  • Michael McAleer

    (Department of Finance, College of Management, Asia University, Taichung City 41354, Taiwan
    Department of Bioinformatics and Medical Engineering, College of Information and Electrical Engineering, Asia University, Taichung City 41354, Taiwan
    Discipline of Business Analytics, University of Sydney Business School, Darlington, NSW 2006, Australia
    Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, 3062 PA Rotterdam, The Netherlands)

Abstract

The paper features an examination of the link between the behaviour of the FTSE 100 and S&P500 Indexes in both an autoregressive distributed lag ARDL, plus a nonlinear autoregressive distributed lag NARDL framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a daily FTSE adjusted price series, commencing in April 2009 and terminating in March 2021, and a corresponding daily S&P500 Index adjusted-price series obtained from Yahoo Finance. The data period includes all the gyrations caused by the Brexit vote in the UK, beginning with the vote to leave in 2016 and culminating in the actual agreement to withdraw in January 2020. It was then followed by the impact of the global spread of COVID-19 from the beginning of 2020. The results of the analysis suggest that movements in the contemporaneous levels of daily S&P500 Index levels have very significant effects on the behaviour of the levels of the daily FTSE 100 Index. They also suggest that negative movements have larger impacts than do positive movements in S&P500 levels, and that long-term multiplier impacts take about 10 days to take effect. These effects are supported by the results of quantile regression analysis. A key result is that weak form market efficiency does not apply in the second period.

Suggested Citation

  • David E. Allen & Michael McAleer, 2021. "A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of the FTSE and S&P500 Indexes," Risks, MDPI, vol. 9(11), pages 1-20, November.
    • Handle: RePEc:gam:jrisks:v:9:y:2021:i:11:p:195-:d:671113
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/9/11/195/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/9/11/195/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Delatte, Anne-Laure & López-Villavicencio, Antonia, 2012. "Asymmetric exchange rate pass-through: Evidence from major countries," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 833-844.
    2. David E. Allen & Michael McAleer, 2020. "A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of West Texas Intermediate Oil Prices and the DOW JONES Index," Energies, MDPI, vol. 13(15), pages 1-11, August.
    3. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    4. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiecheng Song & Merry Ma, 2023. "Climate Change: Linear and Nonlinear Causality Analysis," Stats, MDPI, vol. 6(2), pages 1-17, May.
    2. Youxue Jiang & Zakia Batool & Syed Muhammad Faraz Raza & Mohammad Haseeb & Sajjad Ali & Syed Zain Ul Abidin, 2022. "Analyzing the Asymmetric Effect of Renewable Energy Consumption on Environment in STIRPAT-Kaya-EKC Framework: A NARDL Approach for China," IJERPH, MDPI, vol. 19(12), pages 1-15, June.
    3. Asemahle Swapi & Joseph Akande & Yiseyon Sunday Hosu, 2024. "Wheat Value Chains and Vertical Price Transmission in South Africa: A Nonlinear Autoregressive Diagnostic Lag Bound Approach," Economies, MDPI, vol. 12(12), pages 1-22, December.
    4. Koushik Mandal & Radhika Prosad Datta, 2024. "Oil Price Dynamics and Sectoral Indices in India – Pre, Post and during COVID Pandemic: A Comparative Evidence from Wavelet-based Causality and NARDL," International Journal of Economics and Financial Issues, Econjournals, vol. 14(4), pages 18-33, July.
    5. Kleanthis Natsiopoulos & Nickolaos G. Tzeremes, 2024. "ARDL: An R Package for ARDL Models and Cointegration," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1757-1773, September.
    6. Deng, Xiang & Xu, Fang, 2024. "Asymmetric effects of international oil prices on China's PPI in different industries——Research based on NARDL model," Energy, Elsevier, vol. 290(C).
    7. Victoria Foye, 2022. "Climate Change and Macro Prices in Nigeria: A Nonlinear Analysis," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 20(2 (Summer), pages 167-203.

    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. Kashif Islam & Ahmad Raza Bilal & Syed Anees Haider Zaidi, 2022. "Symmetric and asymmetric nexus between economic freedom and stock market development in Pakistan," Economic Change and Restructuring, Springer, vol. 55(4), pages 2391-2421, November.
    2. Emmanouil Mavrakis & Christos Alexakis, 2018. "Statistical Arbitrage Strategies under Different Market Conditions: The Case of the Greek Banking Sector," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2), pages 159-185, August.
    3. Tarbert, Heather, 1998. "The long-run diversification benefits available from investing across geographical regions and property type: evidence from cointegration tests1," Economic Modelling, Elsevier, vol. 15(1), pages 49-65, January.
    4. Rosa, Franco & Vasciaveo, Michela & Weaver, Robert D., 2014. "Agricultural and oil commodities: price transmission and market integration between US and Italy," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 3(2), pages 1-25, August.
    5. Kühl, Michael, 2007. "Cointegration in the foreign exchange market and market efficiency since the introduction of the Euro: Evidence based on bivariate cointegration analyses," University of Göttingen Working Papers in Economics 68, University of Goettingen, Department of Economics.
    6. Jung, Young Cheol & Das, Anupam & McFarlane, Adian, 2020. "The asymmetric relationship between the oil price and the US-Canada exchange rate," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 198-206.
    7. Gil-Alana, Luis A. & Yaya, OlaOluwa S. & Akinsomi, Omokolade & Coskun, Yener, 2020. "How do stocks in BRICS co-move with real estate stocks?," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 93-101.
    8. Alia Afzal & Philipp Sibbertsen, 2021. "Modeling fractional cointegration between high and low stock prices in Asian countries," Empirical Economics, Springer, vol. 60(2), pages 661-682, February.
    9. Schwert, G. William, 1996. "Markup pricing in mergers and acquisitions," Journal of Financial Economics, Elsevier, vol. 41(2), pages 153-192, June.
    10. Guneratne Banda Wickremasinghe, 2004. "Efficiency of the Foreign Exchange Market of Papua New Guinea During the Recent Float," International Trade 0406007, University Library of Munich, Germany.
    11. J. Doyne Farmer, 2002. "Market force, ecology and evolution," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(5), pages 895-953, November.
    12. Huaibing Yu, 2019. "Long-run Cointegration and Market Equilibrium in Large Cap Stocks," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 8(1), pages 1-2.
    13. Pramod Kumar, Naik & Puja, Padhi, 2012. "The impact of Macroeconomic Fundamentals on Stock Prices revisited: An Evidence from Indian Data," MPRA Paper 38980, University Library of Munich, Germany.
    14. Haugom, Erik & Ullrich, Carl J., 2012. "Market efficiency and risk premia in short-term forward prices," Energy Economics, Elsevier, vol. 34(6), pages 1931-1941.
    15. H. Holly Wang & Bingfan Ke, 2005. "Efficiency tests of agricultural commodity futures markets in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 49(2), pages 125-141, June.
    16. Bahmani-Oskooee, Mohsen & Motavallizadeh-Ardakani, Amid, 2017. "On the value of the dollar and income inequality: Asymmetric evidence from state level data in the U.S," The Journal of Economic Asymmetries, Elsevier, vol. 16(C), pages 64-78.
    17. Bahmani-Oskooee, Mohsen & Nouira, Ridha, 2021. "The nonlinear ARDL approach and productivity bias hypothesis: Evidence from 68 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 80-89.
    18. Sousa, Ricardo M., 2010. "Consumption, (dis)aggregate wealth, and asset returns," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 606-622, September.
    19. Nikitas Niarchos & Christos Alexakis, 1998. "Stock market prices, 'causality' and efficiency: evidence from the Athens stock exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 8(2), pages 167-174.
    20. Álvarez-Díaz, Marcos & González-Gómez, Manuel & Otero-Giráldez, María Soledad, 2018. "Main determinants of export-oriented bleached eucalyptus kraft pulp (BEKP) demand from the north-western regions of Spain," Forest Policy and Economics, Elsevier, vol. 96(C), pages 112-119.

    More about this item

    Keywords

    NARDL; bounds tests; ARDL; FTSE; asymmetries; multiplier effects; S&P500;
    All these keywords.

    JEL classification:

    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:gam:jrisks:v:9:y:2021:i:11:p:195-:d:671113. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.