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Developing an early warning system to predict currency crises

Citations

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Cited by:

  1. Chih-Hao Wen & Ping-Yu Hsu & Ming-Shien Cheng, 2017. "Applying intelligent methods in detecting maritime smuggling," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 573-599, August.
  2. Balaga Mohana Rao & Puja Padhi, 2020. "Common Determinants of the Likelihood of Currency Crises in BRICS," Global Business Review, International Management Institute, vol. 21(3), pages 698-712, June.
  3. Matthias Bogaert & Michel Ballings & Martijn Hosten & Dirk Van den Poel, 2017. "Identifying Soccer Players on Facebook Through Predictive Analytics," Decision Analysis, INFORMS, vol. 14(4), pages 274-297, December.
  4. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos & Verousis, Thanos, 2020. "A conditional fuzzy inference approach in forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 196-216.
  5. Tjeerd M. Boonman & Jan P. A. M. Jacobs & Gerard H. Kuper & Alberto Romero, 2019. "Early Warning Systems for Currency Crises with Real-Time Data," Open Economies Review, Springer, vol. 30(4), pages 813-835, September.
  6. Kriebel, Johannes & Stitz, Lennart, 2022. "Credit default prediction from user-generated text in peer-to-peer lending using deep learning," European Journal of Operational Research, Elsevier, vol. 302(1), pages 309-323.
  7. Wenting Zhang & Shigeyuki Hamori, 2020. "Do Machine Learning Techniques and Dynamic Methods Help Forecast US Natural Gas Crises?," Energies, MDPI, vol. 13(9), pages 1-22, May.
  8. Van Nguyen, Truong & Zhou, Li & Chong, Alain Yee Loong & Li, Boying & Pu, Xiaodie, 2020. "Predicting customer demand for remanufactured products: A data-mining approach," European Journal of Operational Research, Elsevier, vol. 281(3), pages 543-558.
  9. Kizilaslan, Recep & Freund, Steven & Iseri, Ali, 2016. "A data analytic approach to forecasting daily stock returns in an emerging marketAuthor-Name: Oztekin, Asil," European Journal of Operational Research, Elsevier, vol. 253(3), pages 697-710.
  10. Zhi-Qiang Jiang & Gang-Jin Wang & Askery Canabarro & Boris Podobnik & Chi Xie & H. Eugene Stanley & Wei-Xing Zhou, 2018. "Short term prediction of extreme returns based on the recurrence interval analysis," Quantitative Finance, Taylor & Francis Journals, vol. 18(3), pages 353-370, March.
  11. Kim, A. & Yang, Y. & Lessmann, S. & Ma, T. & Sung, M.-C. & Johnson, J.E.V., 2020. "Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 217-234.
  12. Yazan F. Roumani & Yaman Roumani & Joseph K. Nwankpa & Mohan Tanniru, 2018. "Classifying readmissions to a cardiac intensive care unit," Annals of Operations Research, Springer, vol. 263(1), pages 429-451, April.
  13. Feuerriegel, Stefan & Gordon, Julius, 2019. "News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions," European Journal of Operational Research, Elsevier, vol. 272(1), pages 162-175.
  14. Ari, Ali & Cergibozan, Raif, 2018. "Currency crises in Turkey: An empirical assessment," Research in International Business and Finance, Elsevier, vol. 46(C), pages 281-293.
  15. Peiwan Wang & Lu Zong & Ye Ma, 2019. "An Integrated Early Warning System for Stock Market Turbulence," Papers 1911.12596, arXiv.org.
  16. Cueyt SEVIM & Taylan Taner DOGAN, 2016. "Turkiye Ekonomisinde Ihracat ve Doviz Kuru Oynakligi Iliskisi," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 16(2), pages 303-318.
  17. Balaga Mohana Rao & Puja Padhi, 2019. "Identifying the Early Warnings of Currency Crisis in India," Foreign Trade Review, , vol. 54(4), pages 269-299, November.
  18. Kolesnikova, A. & Yang, Y. & Lessmann, S. & Ma, T. & Sung, M.-C. & Johnson, J.E.V., 2019. "Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting," IRTG 1792 Discussion Papers 2019-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  19. Tsionas, Mike G. & Philippas, Dionisis & Philippas, Nikolaos, 2022. "Multivariate stochastic volatility for herding detection: Evidence from the energy sector," Energy Economics, Elsevier, vol. 109(C).
  20. Iqbal, Muhammad & Kusuma, Hadri & Sunaryati, Sunaryati, 2022. "Vulnerability of Islamic banking in ASEAN," Islamic Economic Studies, The Islamic Research and Training Institute (IRTI), vol. 29, pages 159-168.
  21. Kazim Topuz & Hasmet Uner & Asil Oztekin & Mehmet Bayram Yildirim, 2018. "Predicting pediatric clinic no-shows: a decision analytic framework using elastic net and Bayesian belief network," Annals of Operations Research, Springer, vol. 263(1), pages 479-499, April.
  22. Ali, Amjad & Audi, Marc, 2023. "Analyzing the Impact of Foreign Capital Inflows on the Current Account Balance in Developing Economies: A Panel Data Approach," MPRA Paper 118173, University Library of Munich, Germany.
  23. Yulian Zhang & Shigeyuki Hamori, 2020. "Forecasting Crude Oil Market Crashes Using Machine Learning Technologies," Energies, MDPI, vol. 13(10), pages 1-14, May.
  24. Ajitha Kumari Vijayappan Nair Biju & Ann Susan Thomas & J Thasneem, 2024. "Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere—a bibliometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 849-878, February.
  25. Fu, Junhui & Zhou, Qingling & Liu, Yufang & Wu, Xiang, 2020. "Predicting stock market crises using daily stock market valuation and investor sentiment indicators," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  26. Murtaza Nasir & Nichalin Summerfield & Ali Dag & Asil Oztekin, 2020. "A service analytic approach to studying patient no-shows," Service Business, Springer;Pan-Pacific Business Association, vol. 14(2), pages 287-313, June.
  27. Lorenzo Danieli & Petr Jakubik, 2022. "Early Warning System for the European Insurance Sector," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(1), pages 3-21, January.
  28. Medina Moral, Eva & Salvador Perucha, David, 2018. "Medición de la vulnerabilidad monetaria en el área latinoamericana bajo un enfoque de señales ?móviles?/Measurement of Monetary Vulnerability in the Latin American Area using a," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 603-634, Mayo.
  29. Wang, Peiwan & Zong, Lu, 2023. "Does machine learning help private sectors to alarm crises? Evidence from China’s currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
  30. Geng, Ruibin & Bose, Indranil & Chen, Xi, 2015. "Prediction of financial distress: An empirical study of listed Chinese companies using data mining," European Journal of Operational Research, Elsevier, vol. 241(1), pages 236-247.
  31. Gilles Dufrénot & Anne-Charlotte Paret, 2018. "Sovereign debt in emerging market countries: not all of them are serial defaulters," Applied Economics, Taylor & Francis Journals, vol. 50(59), pages 6406-6443, December.
  32. Jian Huang & Junyi Chai & Stella Cho, 2020. "Deep learning in finance and banking: A literature review and classification," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-24, December.
  33. Grabowski, Wojciech & Welfe, Aleksander, 2020. "The Tobit cointegrated vector autoregressive model: An application to the currency market," Economic Modelling, Elsevier, vol. 89(C), pages 88-100.
  34. Hossein Dastkhan, 2021. "Network‐based early warning system to predict financial crisis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 594-616, January.
  35. Asil Oztekin, 2018. "Information fusion-based meta-classification predictive modeling for ETF performance," Information Systems Frontiers, Springer, vol. 20(2), pages 223-238, April.
  36. Ni Zhan, 2021. "Where does the Stimulus go? Deep Generative Model for Commercial Banking Deposits," Papers 2101.09230, arXiv.org.
  37. Maurizio Bovi & Roy Cerqueti, 2016. "Forecasting macroeconomic fundamentals in economic crises," Annals of Operations Research, Springer, vol. 247(2), pages 451-469, December.
  38. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
  39. Huang, Yan & Kou, Gang & Peng, Yi, 2017. "Nonlinear manifold learning for early warnings in financial markets," European Journal of Operational Research, Elsevier, vol. 258(2), pages 692-702.
  40. Matthias Bogaert & Michel Ballings & Dirk Van den Poel, 2018. "Evaluating the importance of different communication types in romantic tie prediction on social media," Annals of Operations Research, Springer, vol. 263(1), pages 501-527, April.
  41. Lei Xu & Takuji Kinkyo & Shigeyuki Hamori, 2018. "Predicting Currency Crises: A Novel Approach Combining Random Forests and Wavelet Transform," JRFM, MDPI, vol. 11(4), pages 1-11, December.
  42. Lutfa Tilat Ferdous & Khnd Md Mostafa Kamal & Amirul Ahsan & Nhung Hong Thuy Hoang & Munshi Samaduzzaman, 2022. "An Early Warning System for Currency Crises in Emerging Countries," JRFM, MDPI, vol. 15(4), pages 1-25, April.
  43. Ivana Marjanoviæ & Milan Markoviæ, 2019. "Determinants of currency crises in the Republic of Serbia," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(1), pages 191-212.
  44. Muhammad Iqbal & Hadri Kusuma & Sunaryati Sunaryati, 2022. "Vulnerability of Islamic banking in ASEAN," Islamic Economic Studies, Emerald Group Publishing Limited, vol. 29(2), pages 159-168, May.
  45. Delen, Dursun & Topuz, Kazim & Eryarsoy, Enes, 2020. "Development of a Bayesian Belief Network-based DSS for predicting and understanding freshmen student attrition," European Journal of Operational Research, Elsevier, vol. 281(3), pages 575-587.
  46. Asil Oztekin, 2018. "Creating a marketing strategy in healthcare industry: a holistic data analytic approach," Annals of Operations Research, Springer, vol. 270(1), pages 361-382, November.
  47. Asil Oztekin, 0. "Information fusion-based meta-classification predictive modeling for ETF performance," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
  48. Cui, Hailong & Rajagopalan, Sampath & Ward, Amy R., 2020. "Predicting product return volume using machine learning methods," European Journal of Operational Research, Elsevier, vol. 281(3), pages 612-627.
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