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Developing an early warning system to predict currency crises

Citations

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Cited by:

  1. 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.
  2. 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.
  3. 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.
  4. Jing, Zhongbo & Li, Qin & Zhao, Hongyi & Zhao, Yang, 2024. "Predicting stock price crash risk in China: A modified graph WaveNet model," Finance Research Letters, Elsevier, vol. 64(C).
  5. 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.
  6. 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.
  7. Sinem Guler Kangalli Uyar & Umut Uyar & Emrah Balkan, 2024. "Fundamental predictors of price bubbles in precious metals: a machine learning analysis," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 37(1), pages 65-87, March.
  8. 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.
  9. Fabozzi, Frank J. & Recchioni, Maria Cristina & Renò, Roberto, 2025. "Fifty years at the interface between financial modeling and operations research," European Journal of Operational Research, Elsevier, vol. 327(1), pages 1-21.
  10. 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.
  11. 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).
  12. Yulian Zhang & Shigeyuki Hamori, 2020. "Forecasting Crude Oil Market Crashes Using Machine Learning Technologies," Energies, MDPI, vol. 13(10), pages 1-14, May.
  13. Tang, Pan & Xu, Wei & Wang, Haosen, 2024. "Network-Based prediction of financial cross-sector risk spillover in China: A deep learning approach," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
  14. 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.
  15. 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.
  16. 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).
  17. 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.
  18. Ni Zhan, 2021. "Where does the Stimulus go? Deep Generative Model for Commercial Banking Deposits," Papers 2101.09230, arXiv.org.
  19. Maurizio Bovi & Roy Cerqueti, 2016. "Forecasting macroeconomic fundamentals in economic crises," Annals of Operations Research, Springer, vol. 247(2), pages 451-469, December.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. Asil Oztekin, 0. "Information fusion-based meta-classification predictive modeling for ETF performance," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
  25. Sreenivasulu Puli & Nagaraju Thota & A. C. V. Subrahmanyam, 2024. "Assessing Machine Learning Techniques for Predicting Banking Crises in India," JRFM, MDPI, vol. 17(4), pages 1-16, March.
  26. 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.
  27. 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.
  28. Mehmet Sahiner, 2024. "Volatility Spillovers and Contagion During Major Crises: An Early Warning Approach Based on a Deep Learning Model," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2435-2499, June.
  29. 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.
  30. Barthélémy, Sylvain & Gautier, Virginie & Rondeau, Fabien, 2026. "Convolutional neural networks to signal currency crises: From the Asian financial crisis to the Covid crisis," International Review of Economics & Finance, Elsevier, vol. 105(C).
  31. Huang, Hsiao-Tzu & Hwang, Yawen & Chan, Linus Fang-Shu & Tsai, Chenghsien Jason, 2024. "Value-enhancing modeling of surrenders and lapses," Insurance: Mathematics and Economics, Elsevier, vol. 119(C), pages 48-63.
  32. Wang, Bo & Yan, Ruolan & Chen, Yang, 2025. "Predicting abnormal capital flow episodes with machine learning methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 103(C).
  33. Zhao, Xian & Huang, Chuangxia & Yang, Xiaoguang & Cao, Jie & Yang, Xin, 2025. "Can we better predict financial crisis? The role of Laplacian-energy-like measure," International Review of Economics & Finance, Elsevier, vol. 103(C).
  34. 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.
  35. 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.
  36. 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.
  37. 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.
  38. Peiwan Wang & Lu Zong & Ye Ma, 2019. "An Integrated Early Warning System for Stock Market Turbulence," Papers 1911.12596, arXiv.org.
  39. 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.
  40. 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".
  41. Muhammad Iqbal & Hadri Kusuma & Sunaryati Sunaryati, 2022. "Vulnerability of Islamic banking in ASEAN," Islamic Economic Studies, The Islamic Research and Training Institute (IRTI), vol. 29, pages 159-168.
  42. 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.
  43. 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.
  44. 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.
  45. 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).
  46. 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.
  47. Burak Cankaya & Robin Roberts & Stephanie Douglas & Rachel Vigness & Asil Oztekin, 2025. "What postpones degree completion? Discovering key predictors of undergraduate degree completion through explainable artificial intelligence (XAI)," Journal of Marketing Analytics, Palgrave Macmillan, vol. 13(2), pages 514-536, June.
  48. 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.
  49. 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.
  50. 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.
  51. 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.
  52. Asil Oztekin, 2018. "Information fusion-based meta-classification predictive modeling for ETF performance," Information Systems Frontiers, Springer, vol. 20(2), pages 223-238, April.
  53. 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.
  54. 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.
  55. 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.
  56. 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.
  57. 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.
  58. 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.
  59. 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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