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A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of the FTSE and S&P500 Indexes
Open accessAbstract
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.
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“Allen and McAleer (2021) applied the NARDL model to show that negative economic shocks have more substantial and lasting effects on global financial indicators.”
From Passenger and Freight Demand under Macroeconomic Volatility: Evidence from South Korea and The United States (2026) · cites this paper as Allen and McAleer (2021)
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Cites
Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework
Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014) · Festschrift in Honor of Peter Schmidt · doi:10.1007/978-1-4899-8008-3_9 · Cited by 3,835
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Cited by
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Jung, N. (2026) · Transport and Telecommunication Journal · doi:10.2478/ttj-2026-0011 · Cited by 1
“Allen and McAleer (2021) applied the NARDL model to show that negative economic shocks have more substantial and lasting effects on global financial indicators.”
Metadata
- Authors
- Allen, D., & McAleer, M.
- Affiliations
- Edith Cowan University (AU)
- Universidad Complutense de Madrid (ES)
- Corresponding author
- Allen, David
- Venue
- Risks
- Publisher
- MDPI AG
- Published
- 2021-11-03
- Volume
- 9
- Issue
- 11
- Pages
- 195
- ISSN
- 2227-9091 (ISSN-L)
- OpenAlex
- W3209176190
- Cited by
- 35
- References
- 1
- Citations by year
- 2026: 8 · 2025: 8 · 2024: 9 · 2023: 7 · 2022: 3
- FWCI
- 3.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Risks (publishedVersion, cc-by)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, cc-by)
- Australasian Journal of Paramedicine (submittedVersion, cc-by)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Econstor (Econstor) (submittedVersion, cc-by)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Market Dynamics and Volatility
- Keywords
- FTSE 100, S&P 500, stock market linkages, nonlinear autoregressive distributed lag, asymmetric price effects, Brexit, COVID-19 market impact, weak-form market efficiency, quantile regression, daily stock prices
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