IDEAS home Printed from https://ideas.repec.org/r/eee/empfin/v10y2003i5p623-640.html
   My bibliography  Save this item

Nonlinear prediction of exchange rates with monetary fundamentals

Citations

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


Cited by:

  1. Emekter, Riza & Jirasakuldech, Benjamas & Snaith, Sean M., 2009. "Nonlinear dynamics in foreign exchange excess returns: Tests of asymmetry," Journal of Multinational Financial Management, Elsevier, vol. 19(3), pages 179-192, July.
  2. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
  3. Rakesh K. Bissoondeeal & Michail Karoglou & Alicia M. Gazely, 2011. "Forecasting The Uk/Us Exchange Rate With Divisia Monetary Models And Neural Networks," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(1), pages 127-152, February.
  4. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
  5. Patro, Dilip K. & Wu, Yangru, 2004. "Predictability of short-horizon returns in international equity markets," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 553-584, September.
  6. Clements, Kenneth W. & Lan, Yihui, 2010. "A new approach to forecasting exchange rates," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1424-1437, November.
  7. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
  8. Grossmann, Axel & Simpson, Marc W., 2010. "Forecasting the Yen/U.S. Dollar exchange rate: Empirical evidence from a capital enhanced relative PPP-based model," Journal of Asian Economics, Elsevier, vol. 21(5), pages 476-484, October.
  9. Clements, Kenneth & Lan, Yihui & Roberts, John, 2008. "Exchange-rate economics for the resources sector," Resources Policy, Elsevier, vol. 33(2), pages 102-117, June.
  10. Yuan, Chunming, 2011. "The exchange rate and macroeconomic determinants: Time-varying transitional dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 22(2), pages 197-220, August.
  11. Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
  12. Catullo, Ermanno & Gallegati, Mauro & Russo, Alberto, 2022. "Forecasting in a complex environment: Machine learning sales expectations in a stock flow consistent agent-based simulation model," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
  13. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
  14. Craig Ellis & Patrick J. Wilson & Ralf Zurbruegg, 2007. "Real Estate ‘Value’ Stocks and International Diversification," Journal of Property Research, Taylor & Francis Journals, vol. 24(3), pages 265-287, September.
  15. Anatolyev, Stanislav, 2009. "Nonparametric Retrospection and Monitoring of Predictability of Financial Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 149-160.
  16. Nikola Gradojević & Vladimir Djaković & Goran Andjelić, 2010. "Random Walk Theory and Exchange Rate Dynamics in Transition Economies," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 57(3), pages 303-320, September.
  17. Manish Kumar, 2010. "A Time-Varying Parameter Vector Autoregression Model for Forecasting Emerging Market Exchange Rates," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 3(2), pages 21-39, December.
  18. Manish Kumar, 2010. "Modelling Exchange Rate Returns Using Non-linear Models," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 4(1), pages 101-125, January.
  19. Ebrahim Hadian; & Najmeh Sajedianfard, 2018. "Monetary Fundamental-Based Exchange Rate Model in Iran: Applying a MS-TVTP Approach," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 22(2), pages 557-578, Spring.
  20. Sarantis, Nicholas, 2006. "On the short-term predictability of exchange rates: A BVAR time-varying parameters approach," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2257-2279, August.
  21. 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.
  22. Corina SAMAN, 2015. "Out-Of-Sample Forecasting Performance Of A Robust Neural Exchange Rate Model Of Ron/Usd," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-106, March.
  23. Joseph Zhi Bin Ling & Albert K. Tsui & Zhaoyong Zhang, 2021. "Trading Macro-Cycles of Foreign Exchange Markets Using Hybrid Models," Sustainability, MDPI, vol. 13(17), pages 1-20, September.
  24. Tseng, Chih-Hsiung & Cheng, Sheng-Tzong & Wang, Yi-Hsien & Peng, Jin-Tang, 2008. "Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3192-3200.
  25. Axel Grossmann & Marc Simpson, 2011. "Predictability of the U.S. Dollar Index using a U.S. export and import price index-based relative PPP model," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 35(4), pages 417-433, October.
  26. Manish KUMAR, 2009. "Exploiting The Information Of Stock Market To Forecast Exchange Rate Movements," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 563-575, November.
  27. Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
  28. Axel Grossmann & Marc Simpson & Teofilo Ozuna, 2014. "Investigating the PPP hypothesis using constructed U.S. dollar equilibrium exchange rate misalignments over the post-bretton woods period," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(2), pages 235-268, April.
  29. Samuel W. Malone & Robert B. Gramacy & Enrique Ter Horst, 2016. "Timing Foreign Exchange Markets," Econometrics, MDPI, vol. 4(1), pages 1-23, March.
  30. Chua, Choong Tze & Lai, Sandy & Wu, Yangru, 2008. "Effective fair pricing of international mutual funds," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2307-2324, November.
  31. 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.
  32. Tao You & Paweł Fiedor & Artur Hołda, 2015. "Network Analysis of the Shanghai Stock Exchange Based on Partial Mutual Information," JRFM, MDPI, vol. 8(2), pages 1-19, June.
  33. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
  34. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
  35. Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.