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Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures

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  • Khurshid Kiani
  • Terry Kastens

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  • Khurshid Kiani & Terry Kastens, 2008. "Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 383-406, November.
    • Handle: RePEc:kap:compec:v:32:y:2008:i:4:p:383-406
    DOI: 10.1007/s10614-008-9144-4
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    1. Sweeney, Richard J, 1986. "Beating the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 41(1), pages 163-182, March.
    2. Zhang, Gioqinang & Hu, Michael Y., 1998. "Neural network forecasting of the British Pound/US Dollar exchange rate," Omega, Elsevier, vol. 26(4), pages 495-506, August.
    3. Lisi, Francesco & Schiavo, Rosa A., 1999. "A comparison between neural networks and chaotic models for exchange rate prediction," Computational Statistics & Data Analysis, Elsevier, vol. 30(1), pages 87-102, March.
    4. Engel, Charles, 1994. "Can the Markov switching model forecast exchange rates?," Journal of International Economics, Elsevier, vol. 36(1-2), pages 151-165, February.
    5. Hutchinson, James M & Lo, Andrew W & Poggio, Tomaso, 1994. "A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks," Journal of Finance, American Finance Association, vol. 49(3), pages 851-889, July.
    6. Meese, Richard A & Rose, Andrew K, 1990. "Nonlinear, Nonparametric, Nonessential Exchange Rate Estimation," American Economic Review, American Economic Association, vol. 80(2), pages 192-196, May.
    7. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    8. Gencay, Ramazan, 1998. "The predictability of security returns with simple technical trading rules," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 347-359, October.
    9. Bradshaw, Girard W. & Orden, David, 1990. "Granger Causality From The Exchange Rate To Agricultural Prices And Export Sales," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 15(1), pages 1-11, July.
    10. Terry L. Kastens & Gary W. Brester, 1996. "Model Selection and Forecasting Ability of Theory-Constrained Food Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 301-312.
    11. Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
    12. Garcia, Rene & Gencay, Ramazan, 2000. "Pricing and hedging derivative securities with neural networks and a homogeneity hint," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 93-115.
    13. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    14. Pamela K. Coats & L. Franklin Fant, 1993. "Recognizing Financial Distress Patterns Using a Neural Network Tool," Financial Management, Financial Management Association, vol. 22(3), Fall.
    15. Medeiros, Marcelo & Veiga, Alvaro, 2000. "A Flexible Coefficient Smooth Transition Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 360, Stockholm School of Economics, revised 29 Apr 2004.
    16. Richard A. Meese & Andrew K. Rose, 1991. "An Empirical Assessment of Non-Linearities in Models of Exchange Rate Determination," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 603-619.
    17. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    18. Qi, Min & Wu, Yangru, 2003. "Nonlinear prediction of exchange rates with monetary fundamentals," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 623-640, December.
    19. Diebold, Francis X. & Nason, James A., 1990. "Nonparametric exchange rate prediction?," Journal of International Economics, Elsevier, vol. 28(3-4), pages 315-332, May.
    20. Conrad, Jennifer & Kaul, Gautam, 1988. "Time-Variation in Expected Returns," The Journal of Business, University of Chicago Press, vol. 61(4), pages 409-425, October.
    21. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    22. Yongmiao Hong & Tae-Hwy Lee, 2003. "Inference on Predictability of Foreign Exchange Rates via Generalized Spectrum and Nonlinear Time Series Models," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1048-1062, November.
    23. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    24. Khurshid Kiani, 2005. "Detecting Business Cycle Asymmetries Using Artificial Neural Networks and Time Series Models," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 65-89, August.
    25. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    26. Wolff, Christian C. P., 1988. "Models of exchange rates : A comparison of forecasting results," International Journal of Forecasting, Elsevier, vol. 4(4), pages 605-607.
    27. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    28. Kuan, Chung-Ming & Liu, Tung, 1995. "Forecasting Exchange Rates Using Feedforward and Recurrent Neural Networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 347-364, Oct.-Dec..
    29. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    30. Marimon, Ramon & McGrattan, Ellen & Sargent, Thomas J., 1990. "Money as a medium of exchange in an economy with artificially intelligent agents," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 329-373, May.
    31. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    32. Gencay, Ramazan, 1999. "Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules," Journal of International Economics, Elsevier, vol. 47(1), pages 91-107, February.
    33. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-275, July.
    34. Bessler, David A. & Brandt, Jon A., 1992. "An analysis of forecasts of livestock prices," Journal of Economic Behavior & Organization, Elsevier, vol. 18(2), pages 249-263, July.
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    Cited by:

    1. Alexander Jakob Dautel & Wolfgang Karl Härdle & Stefan Lessmann & Hsin-Vonn Seow, 2020. "Forex exchange rate forecasting using deep recurrent neural networks," Digital Finance, Springer, vol. 2(1), pages 69-96, September.
    2. Sermpinis, Georgios & Theofilatos, Konstantinos & Karathanasopoulos, Andreas & Georgopoulos, Efstratios F. & Dunis, Christian, 2013. "Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization," European Journal of Operational Research, Elsevier, vol. 225(3), pages 528-540.
    3. Pedram Pishgah Hadiyan & Ramtin Moeini & Eghbal Ehsanzadeh & Monire Karvanpour, 2022. "Trend Analysis of Water Inflow Into the Dam Reservoirs Under Future Conditions Predicted By Dynamic NAR and NARX Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2703-2723, June.
    4. Amirhosein Torabi & Sayyed Ali Kiaian Mousavy & Vahideh Dashti & Mohammadhossein Saeedi & Nasser Yousefi, 2019. "A New Prediction Model Based on Cascade NN for Wind Power Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1219-1243, March.
    5. Firat Melih Yilmaz & Ozer Arabaci, 2021. "Should Deep Learning Models be in High Demand, or Should They Simply be a Very Hot Topic? A Comprehensive Study for Exchange Rate Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 217-245, January.
    6. Elsy Gómez-Ramos & Francisco Venegas-Martínez, 2013. "A Review of Artificial Neural Networks: How Well Do They Perform in Forecasting Time Series?," Analítika, Analítika - Revista de Análisis Estadístico/Journal of Statistical Analysis, vol. 6(2), pages 7-15, Diciembre.
    7. Christian L Dunis & Spiros D Likothanassis & Andreas S Karathanasopoulos & Georgios S Sermpinis & Konstantinos A Theofilatos, 2013. "A hybrid genetic algorithm–support vector machine approach in the task of forecasting and trading," Journal of Asset Management, Palgrave Macmillan, vol. 14(1), pages 52-71, February.
    8. Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.
    9. Kiani, Khurshid M., 2016. "On business cycle fluctuations in USA macroeconomic time series," Economic Modelling, Elsevier, vol. 53(C), pages 179-186.
    10. Hannah Thinyane & Jonathan Millin, 2011. "An Investigation into the Use of Intelligent Systems for Currency Trading," Computational Economics, Springer;Society for Computational Economics, vol. 37(4), pages 363-374, April.
    11. Anderson, Richard G. & Binner, Jane M. & Schmidt, Vincent A., 2012. "Connectionist-based rules describing the pass-through of individual goods prices into trend inflation in the United States," Economics Letters, Elsevier, vol. 117(1), pages 174-177.
    12. Rua-Haun Tsaih & Hsiou-Wei Lin & Wen-Chyan Ke, 2014. "An Abductive-Reasoning Guide for Finance Practitioners," Computational Economics, Springer;Society for Computational Economics, vol. 43(4), pages 411-431, April.
    13. Leandro Maciel & Rosangela Ballini, 2021. "Functional Fuzzy Rule-Based Modeling for Interval-Valued Data: An Empirical Application for Exchange Rates Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 743-771, February.
    14. D. Th. Vezeris & C. J. Schinas & G. Papaschinopoulos, 2018. "Profitability Edge by Dynamic Back Testing Optimal Period Selection for Technical Parameters Optimization, in Trading Systems with Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 761-807, April.

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    More about this item

    Keywords

    Exchange rate forecasts; Feed forward neural networks; Recurrent neural network; In-sample forecasts; Out-of-sample forecasts; ARMA; State space; C32; C45; E37; F31;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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