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Power Of The Neural Network Linearity Test
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Cited by:
- Richard Ashley, 2012.
"On the Origins of Conditional Heteroscedasticity in Time Series,"
Korean Economic Review, Korean Economic Association, vol. 28, pages 5-25.
- Richard Ashley, 2010. "On the Origins of Conditional Heteroscedasticity in Time Series," Working Papers e07-23, Virginia Polytechnic Institute and State University, Department of Economics.
- Bogdan Dima & Stefana Maria Dima & Anca-Adriana Saraolu (Ionascuti), 2024. "The Time Dependence and Interconnectedness of Developed Stock Markets," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 16(2), pages 273-293, December.
- Frédy Pokou & Jules Sadefo Kamdem & François Benhmad, 2024.
"Hybridization of ARIMA with Learning Models for Forecasting of Stock Market Time Series,"
Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1349-1399, April.
- Frédy Valé Manuel Pokou & Jules Sadefo Kamdem & François Benhmad, 2023. "Hybridization of ARIMA with Learning Models for Forecasting of Stock Market Time Series," Post-Print hal-04312314, HAL.
- Jens Krueger & Uwe Cantner & Horst Hanusch, 1998.
"Explaining International Productivity Differences,"
Discussion Paper Series
179, Universitaet Augsburg, Institute for Economics.
- Krüger, Jens & Cantner, Uwe & Hanusch, Horst, 2003. "Explaining International Productivity Differences," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 34385, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
- Anne Péguin-Feissolle & Bilel Sanhaji, 2016.
"Tests of the Constancy of Conditional Correlations of Unknown Functional Form in Multivariate GARCH Models,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 77-101.
- Anne Péguin-Feissolle & Bilel Sanhaji, 2016. "Tests of the Constancy of Conditional Correlations of Unknown Functional Form in Multivariate GARCH Models," Post-Print hal-01448238, HAL.
- Heather M. Anderson & Farshid Vahid, 2005.
"Nonlinear Correlograms and Partial Autocorrelograms,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 957-982, December.
- Heather M. Anderson & Farshid Vahid, 2003. "Nonlinear Correlograms and Partial Autocorrelograms," Monash Econometrics and Business Statistics Working Papers 19/03, Monash University, Department of Econometrics and Business Statistics.
- Gaies, Brahim & Chaâbane, Najeh & Bouzouita, Nesrine, 2024. "Navigating the storm: Time-frequency quantile dependence and non-linear causality between crypto-currency market volatility and financial instability," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 43-70.
- Jorge Belaire-Franch & Amado Peiró, 2015. "Asymmetry in the relationship between unemployment and the business cycle," Empirical Economics, Springer, vol. 48(2), pages 683-697, March.
- Bruno, Giancarlo, 2008.
"Forecasting Using Functional Coefficients Autoregressive Models,"
MPRA Paper
42335, University Library of Munich, Germany.
- Giancarlo Bruno, 2008. "Forecasting Using Functional Coefficients Autoregressive Models," ISAE Working Papers 98, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
- Kapetanios, George & Mitchell, James & Shin, Yongcheol, 2014.
"A nonlinear panel data model of cross-sectional dependence,"
Journal of Econometrics, Elsevier, vol. 179(2), pages 134-157.
- Dr. James Mitchell, 2010. "A Nonlinear Panel Data Model of Cross-sectional Dependence," National Institute of Economic and Social Research (NIESR) Discussion Papers 370, National Institute of Economic and Social Research.
- James Mitchell & George Kapetanios & Yongcheol Shin, 2012. "A Nonlinear Panel Data Model of Cross-Sectional Dependence," Discussion Papers in Economics 12/01, Division of Economics, School of Business, University of Leicester.
- Fabio Gobbi, 2021. "Evaluating Forecasts from State-Dependent Autoregressive Models for US GDP Growth Rate. Comparison with Alternative Approaches," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(6), pages 1-7.
- Farman Ullah Khan & Faridoon Khan & Parvez Ahmed Shaikh, 2023. "Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
- Anoop S. KUMAR & Bandi KAMAIAH, 2016. "Efficiency, non-linearity and chaos: evidences from BRICS foreign exchange markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(1(606), S), pages 103-118, Spring.
- Ali Taiebnia & Shapour Mohammadi, 2023. "Forecast accuracy of the linear and nonlinear autoregressive models in macroeconomic modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2045-2062, December.
- Marcelo C. Medeiros & Alvaro Veiga, 2003.
"Diagnostic Checking in a Flexible Nonlinear Time Series Model,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 461-482, July.
- Medeiros, Marcelo & Veiga, Alvaro, 2000. "Diagnostic Checking in a Flexible Nonlinear Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 386, Stockholm School of Economics, revised 15 Jan 2001.
- Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005.
"Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination,"
International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
- Teräsvirta, Timo & van Dijk, Dick & Medeiros, Marcelo, 2004. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," SSE/EFI Working Paper Series in Economics and Finance 561, Stockholm School of Economics, revised 09 Nov 2004.
- Timo Teräsvirta & Dick van Dijk & Marcelo Cunha Medeiros, 2004. "Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination," Textos para discussão 485, Department of Economics PUC-Rio (Brazil).
- Castle, Jennifer L. & Hendry, David F., 2010.
"A low-dimension portmanteau test for non-linearity,"
Journal of Econometrics, Elsevier, vol. 158(2), pages 231-245, October.
- Jennifer Castle & David Hendry, 2010. "A Low-Dimension Portmanteau Test for Non-linearity," Economics Series Working Papers 471, University of Oxford, Department of Economics.
- Alagidede, Paul, 2011. "Return behaviour in Africa's emerging equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 133-140, May.
- Jorge Belaire-Franch & Kwaku Opong, 2013. "A Time Series Analysis of U.K. Construction and Real Estate Indices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 516-542, April.
- Koller, Wolfgang & Fischer, Manfred M., 2001.
"Testing for Non-Linear Dependence in Univariate Time Series An Empirical Investigation of the Austrian Unemployment Rate,"
MPRA Paper
77809, University Library of Munich, Germany.
- Manfred M. Fischer & Wolfgang Koller, 2001. "Testing for Non-Linear Dependence in Univariate Time Series: An Empirical Investigation of the Austrian Unemployment Rate," ERSA conference papers ersa01p233, European Regional Science Association.
- Shintani, Mototsugu, 2008.
"A dynamic factor approach to nonlinear stability analysis,"
Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2788-2808, September.
- Mototsugu Shintani, 2004. "A Dynamic Factor Approach to Nonlinear Stability Analysis," Levine's Bibliography 122247000000000621, UCLA Department of Economics.
- Mototsugu Shintani, 2004. "A Dynamic Factor Approach to Nonlinear Stability Analysis," Vanderbilt University Department of Economics Working Papers 0418, Vanderbilt University Department of Economics.
- Mototsugu Shintani, 2004. "A Dynamic Factor Approach to Nonlinear Stability Analysis," Econometric Society 2004 Far Eastern Meetings 538, Econometric Society.
- Omane-Adjepong, Maurice & Alagidede, Imhotep Paul, 2020. "High- and low-level chaos in the time and frequency market returns of leading cryptocurrencies and emerging assets," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
- Stan Hurn & Ralf Becker, 2009.
"Testing for Nonlinearity in Mean in the Presence of Heteroskedasticity,"
Economic Analysis and Policy, Elsevier, vol. 39(2), pages 311-326, September.
- Stan Hurn, 2004. "Testing for Nonlinearity in Mean in the Presence of Heteroskedasticity," Econometric Society 2004 Australasian Meetings 348, Econometric Society.
- Stan Hurn & Ralf Becker, 2006. "Testing for nonlinearity in mean in the presence of heteroskedasticity," Stan Hurn Discussion Papers 2006-02, School of Economics and Finance, Queensland University of Technology.
- Bruno, Giancarlo, 2009.
"Non-linear relation between industrial production and business surveys data,"
MPRA Paper
42337, University Library of Munich, Germany.
- Giancarlo Bruno, 2009. "Non-linear relation between industrial production and business surveys data," ISAE Working Papers 119, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
- Long Wen & Chang Liu & Haiyan Song, 2019. "Forecasting tourism demand using search query data: A hybrid modelling approach," Tourism Economics, , vol. 25(3), pages 309-329, May.
- Valerie Herzberg & George Kapetanios & Simon Price, 2003. "Import prices and exchange rate pass-through: theory and evidence from the United Kingdom," Bank of England working papers 182, Bank of England.
- Ralf Becker & Walter Enders & A. Stan Hurn, 2001. "Testing for Time Dependence in Parameters," Research Paper Series 58, Quantitative Finance Research Centre, University of Technology, Sydney.
- Lingaraj Mallick & Smruti Ranjan Behera & Mita Bhattacharya, 2024. "Impact of Exchange Rate on Trade Balance of India: Evidence from Threshold Cointegration with Asymmetric Error Correction Approach," Foreign Trade Review, , vol. 59(2), pages 279-308, May.
- Psaradakis Zacharias & Spagnolo Nicola, 2002. "Power Properties of Nonlinearity Tests for Time Series with Markov Regimes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-16, November.
- Dahl, Christian M. & Gonzalez-Rivera, Gloria, 2003. "Testing for neglected nonlinearity in regression models based on the theory of random fields," Journal of Econometrics, Elsevier, vol. 114(1), pages 141-164, May.
- Babangida, Jamilu Said, 2023. "Nonlinearity in emerging market indices: A comprehensive study of stock exchange market dynamics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 72, pages 23-37.
- Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006.
"Building neural network models for time series: a statistical approach,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
- Medeiros, Marcelo C. & Teräsvirta, Timo & Rech, Gianluigi, 2002. "Building neural network models for time series: A statistical approach," SSE/EFI Working Paper Series in Economics and Finance 508, Stockholm School of Economics.
- Marcelo C. Medeiros & Timo Terasvirta & Gianluigi Rech, 2002. "Building Neural Network Models for Time Series: A Statistical Approach," Textos para discussão 461, Department of Economics PUC-Rio (Brazil).
- Terasvirta, Timo, 2006.
"Forecasting economic variables with nonlinear models,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457,
Elsevier.
- Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005.
- Anderson, Heather M. & Vahid, Farshid, 1998. "Testing multiple equation systems for common nonlinear components," Journal of Econometrics, Elsevier, vol. 84(1), pages 1-36, May.
- Shintani, Mototsugu, 2005.
"Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 517-538, June.
- Mototsugu Shintani, 2003. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Vanderbilt University Department of Economics Working Papers 0322, Vanderbilt University Department of Economics, revised Apr 2004.
- Mototsugu Shintani, 2010. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Levine's Working Paper Archive 506439000000000168, David K. Levine.
- Messaoud, Amor & Weihs, Claus & Hering, Franz, 2008. "Detection of chatter vibration in a drilling process using multivariate control charts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3208-3219, February.
- Adrian Pagan & Hashem Pesaran, 2007. "Econometric Analysis of Structural Systems with Permanent and Transitory Shocks. Working paper #7," NCER Working Paper Series 7, National Centre for Econometric Research.
- Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
- Robert J Bianchi & Adam E Clements & Michael E Drew, 2009. "HACking at Non-linearity: Evidence from Stocks and Bonds," School of Economics and Finance Discussion Papers and Working Papers Series 244, School of Economics and Finance, Queensland University of Technology.
- Manzan, Sebastiano & Zerom, Dawit, 2008. "A bootstrap-based non-parametric forecast density," International Journal of Forecasting, Elsevier, vol. 24(3), pages 535-550.
- You, Zhongyuan & Goodwin, Barry K. & Guney, Selin, 2023. "A semi-parametric study on dynamic linkages among international real interest rates," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 215-229.
- Chen, Gong & Fricke, Hartmut & Okhrin, Ostap & Rosenow, Judith, 2024. "Flight delay propagation inference in air transport networks using the multilayer perceptron," Journal of Air Transport Management, Elsevier, vol. 114(C).
- Henrik Amilon, 2003. "A neural network versus Black-Scholes: a comparison of pricing and hedging performances," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 317-335.
- Choe, Kyoungin & Goodwin, Barry K., 2022. "Nonlinear Aspects of Integration of the US Corn Market," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322158, Agricultural and Applied Economics Association.
- Annette Detken, 2002. "Nonlinearities in Swiss macroeconomic data," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 138(I), pages 39-60, March.
- Kempf, Alexander & Korn, Olaf, 1999. "Market depth and order size1," Journal of Financial Markets, Elsevier, vol. 2(1), pages 29-48, February.
- Zhaoyan Liu & Min Shu & Wei Zhu, 2024. "Contrastive Learning Framework for Bitcoin Crash Prediction," Stats, MDPI, vol. 7(2), pages 1-32, May.
- Vincenzo Candila & Lucio Palazzo, 2020. "Neural Networks and Betting Strategies for Tennis," Risks, MDPI, vol. 8(3), pages 1-19, June.
- Dimitris Christopoulos & Peter McAdam & Elias Tzavalis, 2023. "Exploring Okun's law asymmetry: An endogenous threshold logistic smooth transition regression approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(1), pages 123-158, February.
- Li, Haiqi & Kim, Myeong Jun & Park, Sung Y., 2016. "Nonlinear relationship between crude oil price and net futures positions: A dynamic conditional distribution approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 217-225.
- Kempf, Alexander & Korn, Olaf, 1998. "Market depth and order size: an analysis of permanent price effects of DAX futures' trades," ZEW Discussion Papers 98-10, ZEW - Leibniz Centre for European Economic Research.
- Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
- Szafranek, Karol, 2019.
"Bagged neural networks for forecasting Polish (low) inflation,"
International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
- Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
- Francesco Virili & Bernd Freisleben, 2001. "Neural Network Model Selection for Financial Time Series Prediction," Computational Statistics, Springer, vol. 16(3), pages 451-463, September.
- Dagum, Estela Bee & Giannerini, Simone, 2006. "A critical investigation on detrending procedures for non-linear processes," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 175-191, March.
- Yang, Haolin & Schell, Kristen R., 2021. "Real-time electricity price forecasting of wind farms with deep neural network transfer learning and hybrid datasets," Applied Energy, Elsevier, vol. 299(C).
- Twumasi, Clement & Twumasi, Juliet, 2022. "Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1258-1277.
- Zhang, Yu & Li, Yanting & Zhang, Guangyao, 2020. "Short-term wind power forecasting approach based on Seq2Seq model using NWP data," Energy, Elsevier, vol. 213(C).
- Tea Šestanović & Josip Arnerić, 2021. "Can Recurrent Neural Networks Predict Inflation in Euro Zone as Good as Professional Forecasters?," Mathematics, MDPI, vol. 9(19), pages 1-13, October.
- Ngene, Geoffrey M. & Lee Kim, Yea & Wang, Jinghua, 2019. "Who poisons the pool? Time-varying asymmetric and nonlinear causal inference between low-risk and high-risk bonds markets," Economic Modelling, Elsevier, vol. 81(C), pages 136-147.
- Ulrich Anders & Andrea Szczesny, 1998. "Prognose von Insolvenzwahrscheinlichkeiten mit Hilfe logistischer neuronaler Netzwerke," Schmalenbach Journal of Business Research, Springer, vol. 50(10), pages 892-915, October.
- A. Ford Ramsey & Barry K. Goodwin & William F. Hahn & Matthew T. Holt, 2021. "Impacts of COVID‐19 and Price Transmission in U.S. Meat Markets," Agricultural Economics, International Association of Agricultural Economists, vol. 52(3), pages 441-458, May.
- 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.
- Panja, Madhurima & Chakraborty, Tanujit & Nadim, Sk Shahid & Ghosh, Indrajit & Kumar, Uttam & Liu, Nan, 2023. "An ensemble neural network approach to forecast Dengue outbreak based on climatic condition," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
- Thiyanga S Talagala & Rob J Hyndman & George Athanasopoulos, 2018. "Meta-learning how to forecast time series," Monash Econometrics and Business Statistics Working Papers 6/18, Monash University, Department of Econometrics and Business Statistics.
- Barry K. Goodwin & Matthew T. Holt & Jeffrey P. Prestemon, 2021. "Semi-parametric models of spatial market integration," Empirical Economics, Springer, vol. 61(5), pages 2335-2361, November.
- Raimundo Soto, "undated". "Nonlinearities in the Demand for money: A Neural Network Approach," ILADES-UAH Working Papers inv107, Universidad Alberto Hurtado/School of Economics and Business.
- Wu, Wanshan & Tiwari, Aviral Kumar & Gozgor, Giray & Leping, Huang, 2021. "Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures," Research in International Business and Finance, Elsevier, vol. 58(C).
- Soares, Lacir J. & Medeiros, Marcelo C., 2008. "Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data," International Journal of Forecasting, Elsevier, vol. 24(4), pages 630-644.
- Yuehjen E. Shao & Yi-Shan Tsai, 2018. "Electricity Sales Forecasting Using Hybrid Autoregressive Integrated Moving Average and Soft Computing Approaches in the Absence of Explanatory Variables," Energies, MDPI, vol. 11(7), pages 1-22, July.
- Canaydin, Ada & Fu, Chun & Balint, Attila & Khalil, Mohamad & Miller, Clayton & Kazmi, Hussain, 2024. "Interpretable domain-informed and domain-agnostic features for supervised and unsupervised learning on building energy demand data," Applied Energy, Elsevier, vol. 360(C).
- Becker, R. & Hurn, A.S., 2004. "Using discrete-time techniques to test continuous-time models for nonlinearity in drift," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(1), pages 121-131.
- Hadhri, Sinda & Ftiti, Zied, 2017. "Stock return predictability in emerging markets: Does the choice of predictors and models matter across countries?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 39-60.
- Pelin Akçagün-Narin & Adem Yavuz Elveren, 2024. "Financialization and Militarization: An Empirical Investigation," Review of Radical Political Economics, Union for Radical Political Economics, vol. 56(1), pages 70-100, March.