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A Radial Basis Function Artificial Neural Network Test for ARCH

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Abstract

We propose a test for ARCH that uses a radial basis function artificial neural network. It outperforms alternative neural network tests in a variety of Monte Carlo experiments.

Suggested Citation

  • Andrew Blake, 1999. "A Radial Basis Function Artificial Neural Network Test for ARCH," National Institute of Economic and Social Research (NIESR) Discussion Papers 154, National Institute of Economic and Social Research.
    • Handle: RePEc:nsr:niesrd:154
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    Cited by:

    1. Benigno, Pierpaolo & Woodford, Michael, 2012. "Linear-quadratic approximation of optimal policy problems," Journal of Economic Theory, Elsevier, vol. 147(1), pages 1-42.
    2. Hong, Seung Hyun & Phillips, Peter C. B., 2010. "Testing Linearity in Cointegrating Relations With an Application to Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 96-114.
    3. Di Bartolomeo, Giovanni & Di Pietro, Marco & Giannini, Bianca, 2016. "Optimal monetary policy in a New Keynesian model with heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 373-387.
    4. Andrew P. Blake & George Kapetanios, 2003. "Pure Significance Tests of the Unit Root Hypothesis Against Nonlinear Alternatives," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(3), pages 253-267, May.
    5. Paez-Farrell, Juan, 2011. "Timeless perspective versus discretionary policymaking when the degree of inflation persistence is unknown," Economic Modelling, Elsevier, vol. 28(6), pages 2432-2438.
    6. Brendon, C. & Ellison, M., 2018. "Time-Consistently Undominated Policies," Cambridge Working Papers in Economics 1809, Faculty of Economics, University of Cambridge.
    7. Yen-Ming Chiang & Wei-Guo Cheng & Fi-John Chang, 2012. "A hybrid artificial neural network-based agri-economic model for predicting typhoon-induced losses," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 63(2), pages 769-787, September.
    8. George Kapetanios & Andrew P. Blake, 2007. "Testing the Martingale Difference Hypothesis Using Neural Network Approximations," Working Papers 601, Queen Mary University of London, School of Economics and Finance.
    9. Jensen, Christian, 2016. "Discretion Rather than Rules? Binding Commitments versus Discretionary Policymaking," MPRA Paper 76838, University Library of Munich, Germany.
    10. George A. Waters, 2015. "Careful Price Level Targeting," International Symposia in Economic Theory and Econometrics, in: William A. Barnett & Fredj Jawadi (ed.), Monetary Policy in the Context of the Financial Crisis: New Challenges and Lessons, volume 24, pages 29-40, Emerald Publishing Ltd.
    11. George Kapetanios & Andrew P. Blake, 2007. "Boosting Estimation of RBF Neural Networks for Dependent Data," Working Papers 588, Queen Mary University of London, School of Economics and Finance.
    12. Lee Tae-Hwy, 2001. "Neural Network Test and Nonparametric Kernel Test for Neglected Nonlinearity in Regression Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(4), pages 1-15, January.
    13. Thierry Warin & Aleksandar Stojkov, 2021. "Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature," JRFM, MDPI, vol. 14(7), pages 1-31, July.
    14. Blake, Andrew P. & Kapetanios, George, 2007. "Testing for ARCH in the presence of nonlinearity of unknown form in the conditional mean," Journal of Econometrics, Elsevier, vol. 137(2), pages 472-488, April.
    15. Andrew P. Blake & George Kapetanios, 2007. "Testing for Neglected Nonlinearity in Cointegrating Relationships," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(6), pages 807-826, November.
    16. Kanazawa, Nobuyuki, 2020. "Radial basis functions neural networks for nonlinear time series analysis and time-varying effects of supply shocks," Journal of Macroeconomics, Elsevier, vol. 64(C).
    17. Blake, Andrew P. & Kirsanova, Tatiana, 2004. "A note on timeless perspective policy design," Economics Letters, Elsevier, vol. 85(1), pages 9-16, October.
    18. Nikoleta Anesti & Eleni Kalamara & George Kapetanios, 2021. "Forecasting UK GDP growth with large survey panels," Bank of England working papers 923, Bank of England.
    19. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.

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