Research Article
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Year 2024, Volume: 24 Issue: 4, 621 - 638, 01.11.2024
https://doi.org/10.21121/eab.20240409

Abstract

References

  • Ağaslan, E., & Alkan, B. (2021). Döviz kuru oynaklığı ve ekonomik büyüme ilişkisine yeniden bakış. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 23(3), 1001–1016. https://doi.org/10.26745/AHBVUIBFD.1001886
  • Ağaslan, E., & Gayaker, S. (2019). Türkiye’de para ikamesinin belirleyicileri doğrusal olmayan bir yaklaşım. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 21(2), 362–387.
  • Agresti, A. (2007). An introduction to categorical data analysis. Wiley-Interscience.
  • Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2003). Micro effects of macro announcements: Real-time price discovery in foreign exchange. American Economic Review, 93(1), 38–62. https://doi.org/10.1257/000282803321455151
  • Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2007). Real-time price discovery in global stock, bond and foreign exchange markets. Journal of International Economics, 73(2), 251–277. https://doi.org/10.1016/J.JINTECO.2007.02.004
  • Andersen, T. G., Bollerslev, T., Frederiksen, P., & Nielsen, M. Ø. (2010). Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns. Journal of Applied Econometrics, 25(2), 233–261. https://doi.org/10.1002/JAE.1105
  • Arita, S. (2003). The growth of the Korean middle class and its social consciousness. The Developing Economies, 41(2), 201–220. https://doi.org/10.1111/j.1746-1049.2003.tb00938.x
  • Auger, I. E., & Lawrance, C. E. (1989). Algorithms for the optimal identification of segment neighborhoods. Bulletin of Mathematical Biology, 51(1), 39–54. https://doi.org/10.1016/S0092-8240(89)80047-3
  • Ayadi, M. A., Omrane, W. B., & Das, D. K. (2024). Macroeconomic news, senior officials' speeches, and emerging currency markets: An intraday analysis of price jump reaction. Emerging Markets Review, 60, 101147.
  • Bian, H., Fattah, R., Zhong, S., & Zhang, X. (2020). An efficient rectilinear Gaussian beam tracing method for sound propagation modelling in a non-turbulent medium. The Journal of the Acoustical Society of America, 148(6), 4037. https://doi.org/10.1121/10.0002966
  • Bilson, J. F. O. (1978). The current experience with floating exchange rates: An appraisal of the monetary approach. The American Economic Review, 68(2), 392–397. https://www.jstor.org/stable/1816727
  • Bolton, R. J., & Hand, D. J. (2002). Statistical fraud fetection: A review. Https://Doi.Org/10.1214/Ss/1042727940, 17(3), 235–255. https://doi.org/10.1214/SS/1042727940
  • Boudt, K., Croux, C., & Laurent, S. (2011). Robust estimation of intraweek periodicity in volatility and jump detection. Journal of Empirical Finance, 18(2), 353–367. https://doi.org/10.1016/J.JEMPFIN.2010.11.005
  • Brown, R. G. (1963). Smoothing, forecasting and prediction of discrete time series. Prentice-Hall.
  • Bujang, M. A., Sa’at, N., & Bakar, T. M. I. T. A. (2017). Determination of minimum sample size requirement for multiple linear regression and analysis of covariance based on experimental and non-experimental studies. Epidemiology, biostatistics, and public health, 14(3).
  • Bulut, E. (2005). Döviz ekonomisi, (Piyasanın mikro yapısı). Platin Yayınları.
  • Cassel, G. (1918). Abnormal Deviations in International Exchanges. The Economic Journal, 28(112), 413–415. https://doi.org/10.2307/2223329
  • Chae-Deug, Y. (2024). Realized normal volatility and maximum outlying jumps in high frequency returns for Korean won–US Dollar. International Review of Financial Analysis, 95, 103344.
  • Chatrath, A., Miao, H., Ramchander, S., & Villupuram, S. (2014). Currency jumps, cojumps and the role of macro news. Journal of International Money and Finance, 40, 42–62. https://doi.org/10.1016/J.JIMONFIN.2013.08.018
  • Chen, J. (2012). Real exchange rate and economic growth: Evidence from Chinese provincial data (1992 - 2008). https://shs.hal.science/halshs-00667467
  • Claasen, E. M. (1996). Global monetary economics. Oxford University Press.
  • Copeland, L. S. (1989). Exchange rates and international finance. Addison Wesley.
  • Duffie, D., Pan, J., & Singleton, K. (2000). Transform analysis and asset pricing for affine jump-diffusions. Econometrica, 68(6), 1343–1376. https://doi.org/10.1111/1468-0262.00164
  • Eraker, B., Johannes, M., & Polson, N. (2003). The impact of jumps in volatility and returns. The Journal of Finance, 58(3), 1269–1300. https://doi.org/10.1111/1540-6261.00566
  • Frankel, J. A., Galli, Giampaolo., & Giovannini, Alberto. (1996). Why we need for microstructure? In The microstructure of foreign exchange markets (p. 346). University of Chicago Press.
  • Fuentes, M. (2009). Dollarization of debt contracts: Evidence from Chilean firms. The Developing Economies, 47(4), 458–487. https://doi.org/10.1111/j.1746-1049.2009.00094.x
  • Gala, P., & Libânio, G. (2010). Exchange rate policies, patterns of specialization and economic development: theory and evidence in developing countries. http://bibliotecadigital.fgv.br:80/dspace/handle/10438/6875
  • Gelbard, E., & Nagayasu, J. (2004). Determinants of Angola’s Real Exchange Rate, 1992–2002. The Developing Economies, 42(3), 392–404. https://doi.org/10.1111/j.1746-1049.2004.tb00944.x
  • Habib, M. M., Mileva, E., & Stracca, L. (2017). The real exchange rate and economic growth: Revisiting the case using external instruments. Journal of International Money and Finance, 73, 386–398. https://doi.org/10.1016/J.JIMONFIN.2017.02.014
  • Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning (Second Edition). Springer Verlag.
  • Hilbe, J. M. (2009). Logistic regression models. CRC Press.
  • Hosmer, D. W., & Lemeshow, S. (2000). Applied Logistic Regression. John Wiley & Sons, Inc. https://doi.org/10.1002/0471722146
  • Jackson, B., Scargle, J. D., Barnes, D., Arabhi, S., Alt, A., Gioumousis, P., Gwin, E., San, P., Tan, L., & Tun Tao Tsai. (2005). An algorithm for optimal partitioning of data on an interval. IEEE Signal Processing Letters, 12(2), 105–108. https://doi.org/10.1109/LSP.2001.838216
  • Karsmakers, P., Pelckmans, K., & Suykens, J. A. K. (2007). Multi-class kernel logistic regression: A fixed-size implementation. IEEE International Conference on Neural Networks - Conference Proceedings, 1756–1761. https://doi.org/10.1109/IJCNN.2007.4371223
  • Killick, R., Fearnhead, P., & Eckley, I. A. (2012). Optimal detection of changepoints with a linear computational cost. Http://Dx.Doi.Org/10.1080/01621459.2012.737745, 107(500), 1590–1598. https://doi.org/10.1080/01621459.2012.737745
  • Kim, A. Y., Marzban, C., Percival, D. B., & Stuetzle, W. (2009). Using labeled data to evaluate change detectors in a multivariate streaming environment. Signal Processing, 89(12), 2529–2536. https://doi.org/10.1016/J.SIGPRO.2009.04.011
  • King, G., & Zeng, L. (2001). Logistic regression in rare events data. Political Analysis, 9(2), 137–163. https://doi.org/10.1093/oxfordjournals.pan.a004868
  • Kleinbaum, D. G., & Klein, M. (2010). Ordinal Logistic Regression (pp. 463–488). https://doi.org/10.1007/978-1-4419-1742-3_13
  • Kleinbaum, David. G., Kupper, L. L., Nizam, A., & Rosenberg, S. E. (2007). Applied regression analysis and multivariable methods (4.th Edition). Duxbury Press.
  • Krugman, R. P., Obstfeld, M., & Melitz, M. (2014). International economics: Theory and policy (10th ed.). Pearson.
  • Lahaye, J., Laurent, S., & Neely, C. J. (2011). Jumps, cojumps and macro announcements. Journal of Applied Econometrics, 26(6), 893–921. https://doi.org/10.1002/JAE.1149
  • Lee, S. S., & Mykland, P. A. (2008). Jumps in financial markets: A new nonparametric test and jump dynamics. The Review of Financial Studies, 21(6), 2535–2563. https://doi.org/10.1093/RFS/HHM056
  • Lin, C.-J., Weng, R. C., & Keerthi, S. S. (2007). Trust region Newton methods for large-scale logistic regression. Proceedings of the 24th International Conference on Machine Learning, 561–568. https://doi.org/10.1145/1273496.1273567
  • Liu, J., Longstaff, F. A., & Pan, J. (2003). Dynamic asset allocation with event risk. The Journal of Finance, 58(1), 231–259. https://doi.org/10.1111/1540-6261.00523
  • Mampaey, M., Tatti, N., & Vreeken, J. (2011). Tell me what I need to know: Succinctly summarizing data with itemsets. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 573–581. https://doi.org/10.1145/2020408.2020499
  • Manner, H., Rodríguez, G., & Stöckler, F. (2024). A changepoint analysis of exchange rate and commodity price risks for Latin American stock markets. International Review of Economics & Finance, 89, 1385-1403.
  • McKinnon, R. I. (1982). Currency substitution and instability in the world dollar standard. The American Economic Review, 72(3), 320–333. https://www.jstor.org/stable/1831535
  • Meese, R. A., & Rogoff, K. (1983). Empirical exchange rate models of the seventies: Do they fit out of sample? Journal of International Economics, 14(1–2), 3–24. https://doi.org/10.1016/0022-1996(83)90017-X
  • Meese, R. A., & Rose, A. K. (1990). Nonlinear, nonparametric, nonessential exchange rate estimation. American Economic Association, 80(2), 192–296. https://www.jstor.org/stable/2006568
  • Muggeo, V. M. R., & Adelfio, G. (2011). Efficient change point detection for genomic sequences of continuous measurements. Bioinformatics, 27(2), 161–166. https://doi.org/10.1093/BIOINFORMATICS/BTQ647
  • Mussa, M. (1986). Nominal exchange rate regimes and the behavior of real exchange rates: Evidence and implications. Carnegie-Rochester Conference Series on Public Policy, 25(C), 117–214. https://doi.org/10.1016/0167-2231(86)90039-4
  • Obstfeld, M., Dornbusch, R., & McKinnon, R. (1995). International currency experience: new lessons and lessons relearned. Brookings Papers on Economic Activity, 1995(1), 119. https://doi.org/10.2307/2534574
  • Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996). A simulation study of the number of events per variable in logistic regression analysis. Journal of Clinical Epidemiology, 49(12), 1373–1379. https://doi.org/10.1016/S0895-4356(96)00236-3
  • Peruga, R. (1996). Learning and the exchange rate: Exchange rate responses to money announcements in the early 1980s. Journal of International Money and Finance, 15(2), 167–190. https://doi.org/10.1016/0261-5606(96)00004-6
  • Piazzesi, M. (2005). Bond yields and the federal reserve. Journal of Political Economy, 113(2), 311–344. https://doi.org/10.1086/427466
  • Rodrik, D. (2009). The real exchange rate and economic growth. Brookings Papers on Economic Activity, 2008(2), 365–412. https://doi.org/10.1353/ECA.0.0020
  • Scott, A. J., & Knott, M. (1974). A cluster analysis method for grouping means in the analysis of variance. Biometrics, 30(3), 507. https://doi.org/10.2307/2529204
  • Talih, M., & Hengartner, N. (2005). Structural learning with time-varying components: tracking the cross-section of financial time series. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67(3), 321–341. https://doi.org/10.1111/J.1467-9868.2005.00504.X
  • Tauchen, G., & Zhou, H. (2011). Realized jumps on financial markets and predicting credit spreads. Journal of Econometrics, 160(1), 102–118. https://doi.org/10.1016/J.JECONOM.2010.03.023
  • Trigg, D. W., & Leach, A. G. (1967). Exponential smoothing with an adaptive response rate. OR, 18(1), 53. https://doi.org/10.2307/3010768
  • Truong, C., Oudre, L., & Vayatis, N. (2020). Selective review of offline change point detection methods. Signal Processing, 167, 107299. https://doi.org/10.1016/J.SIGPRO.2019.107299
  • Uzun, S., Sensoy, A., & Nguyen, D. K. (2023). Jump forecasting in foreign exchange markets: A high‐frequency analysis. Journal of Forecasting, 42(3), 578-624.
  • Yao, Y.-C. (1984). Estimation of a noisy discrete-time step function: Bayes and empirical Bayes approaches. The Annals of Statistics, 12(4), 1434–1447. https://www.jstor.org/stable/2241012

Determinants of Exchange Rate Jumps in Türkiye

Year 2024, Volume: 24 Issue: 4, 621 - 638, 01.11.2024
https://doi.org/10.21121/eab.20240409

Abstract

This study examines the exchange rate jumps in Türkiye between 2013 and 2021 and the factors influencing these jumps. The Turkish Lira experienced a consistent depreciation against other currencies during this period. A closer examination of the depreciation timeline revealed that the Turkish Lira's depreciation was occasionally abrupt and exceedingly pronounced. The primary objective of this research is to identify these episodes of spikes, which can be characterized as jumps in exchange rates amid regular increases. To achieve this, the Pruned Exact Linear Time (PELT) algorithm was employed to detect sudden shifts in the exchange rate. Taking these points as dependent variables, a rare event logistic regression model was utilized to determine the probability of an exchange rate jump. The findings indicate that increased dollarization raises the likelihood of an exchange rate jump, while higher deposit rates and central bank reserves reduce the probability of a jump.

References

  • Ağaslan, E., & Alkan, B. (2021). Döviz kuru oynaklığı ve ekonomik büyüme ilişkisine yeniden bakış. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 23(3), 1001–1016. https://doi.org/10.26745/AHBVUIBFD.1001886
  • Ağaslan, E., & Gayaker, S. (2019). Türkiye’de para ikamesinin belirleyicileri doğrusal olmayan bir yaklaşım. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 21(2), 362–387.
  • Agresti, A. (2007). An introduction to categorical data analysis. Wiley-Interscience.
  • Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2003). Micro effects of macro announcements: Real-time price discovery in foreign exchange. American Economic Review, 93(1), 38–62. https://doi.org/10.1257/000282803321455151
  • Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2007). Real-time price discovery in global stock, bond and foreign exchange markets. Journal of International Economics, 73(2), 251–277. https://doi.org/10.1016/J.JINTECO.2007.02.004
  • Andersen, T. G., Bollerslev, T., Frederiksen, P., & Nielsen, M. Ø. (2010). Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns. Journal of Applied Econometrics, 25(2), 233–261. https://doi.org/10.1002/JAE.1105
  • Arita, S. (2003). The growth of the Korean middle class and its social consciousness. The Developing Economies, 41(2), 201–220. https://doi.org/10.1111/j.1746-1049.2003.tb00938.x
  • Auger, I. E., & Lawrance, C. E. (1989). Algorithms for the optimal identification of segment neighborhoods. Bulletin of Mathematical Biology, 51(1), 39–54. https://doi.org/10.1016/S0092-8240(89)80047-3
  • Ayadi, M. A., Omrane, W. B., & Das, D. K. (2024). Macroeconomic news, senior officials' speeches, and emerging currency markets: An intraday analysis of price jump reaction. Emerging Markets Review, 60, 101147.
  • Bian, H., Fattah, R., Zhong, S., & Zhang, X. (2020). An efficient rectilinear Gaussian beam tracing method for sound propagation modelling in a non-turbulent medium. The Journal of the Acoustical Society of America, 148(6), 4037. https://doi.org/10.1121/10.0002966
  • Bilson, J. F. O. (1978). The current experience with floating exchange rates: An appraisal of the monetary approach. The American Economic Review, 68(2), 392–397. https://www.jstor.org/stable/1816727
  • Bolton, R. J., & Hand, D. J. (2002). Statistical fraud fetection: A review. Https://Doi.Org/10.1214/Ss/1042727940, 17(3), 235–255. https://doi.org/10.1214/SS/1042727940
  • Boudt, K., Croux, C., & Laurent, S. (2011). Robust estimation of intraweek periodicity in volatility and jump detection. Journal of Empirical Finance, 18(2), 353–367. https://doi.org/10.1016/J.JEMPFIN.2010.11.005
  • Brown, R. G. (1963). Smoothing, forecasting and prediction of discrete time series. Prentice-Hall.
  • Bujang, M. A., Sa’at, N., & Bakar, T. M. I. T. A. (2017). Determination of minimum sample size requirement for multiple linear regression and analysis of covariance based on experimental and non-experimental studies. Epidemiology, biostatistics, and public health, 14(3).
  • Bulut, E. (2005). Döviz ekonomisi, (Piyasanın mikro yapısı). Platin Yayınları.
  • Cassel, G. (1918). Abnormal Deviations in International Exchanges. The Economic Journal, 28(112), 413–415. https://doi.org/10.2307/2223329
  • Chae-Deug, Y. (2024). Realized normal volatility and maximum outlying jumps in high frequency returns for Korean won–US Dollar. International Review of Financial Analysis, 95, 103344.
  • Chatrath, A., Miao, H., Ramchander, S., & Villupuram, S. (2014). Currency jumps, cojumps and the role of macro news. Journal of International Money and Finance, 40, 42–62. https://doi.org/10.1016/J.JIMONFIN.2013.08.018
  • Chen, J. (2012). Real exchange rate and economic growth: Evidence from Chinese provincial data (1992 - 2008). https://shs.hal.science/halshs-00667467
  • Claasen, E. M. (1996). Global monetary economics. Oxford University Press.
  • Copeland, L. S. (1989). Exchange rates and international finance. Addison Wesley.
  • Duffie, D., Pan, J., & Singleton, K. (2000). Transform analysis and asset pricing for affine jump-diffusions. Econometrica, 68(6), 1343–1376. https://doi.org/10.1111/1468-0262.00164
  • Eraker, B., Johannes, M., & Polson, N. (2003). The impact of jumps in volatility and returns. The Journal of Finance, 58(3), 1269–1300. https://doi.org/10.1111/1540-6261.00566
  • Frankel, J. A., Galli, Giampaolo., & Giovannini, Alberto. (1996). Why we need for microstructure? In The microstructure of foreign exchange markets (p. 346). University of Chicago Press.
  • Fuentes, M. (2009). Dollarization of debt contracts: Evidence from Chilean firms. The Developing Economies, 47(4), 458–487. https://doi.org/10.1111/j.1746-1049.2009.00094.x
  • Gala, P., & Libânio, G. (2010). Exchange rate policies, patterns of specialization and economic development: theory and evidence in developing countries. http://bibliotecadigital.fgv.br:80/dspace/handle/10438/6875
  • Gelbard, E., & Nagayasu, J. (2004). Determinants of Angola’s Real Exchange Rate, 1992–2002. The Developing Economies, 42(3), 392–404. https://doi.org/10.1111/j.1746-1049.2004.tb00944.x
  • Habib, M. M., Mileva, E., & Stracca, L. (2017). The real exchange rate and economic growth: Revisiting the case using external instruments. Journal of International Money and Finance, 73, 386–398. https://doi.org/10.1016/J.JIMONFIN.2017.02.014
  • Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning (Second Edition). Springer Verlag.
  • Hilbe, J. M. (2009). Logistic regression models. CRC Press.
  • Hosmer, D. W., & Lemeshow, S. (2000). Applied Logistic Regression. John Wiley & Sons, Inc. https://doi.org/10.1002/0471722146
  • Jackson, B., Scargle, J. D., Barnes, D., Arabhi, S., Alt, A., Gioumousis, P., Gwin, E., San, P., Tan, L., & Tun Tao Tsai. (2005). An algorithm for optimal partitioning of data on an interval. IEEE Signal Processing Letters, 12(2), 105–108. https://doi.org/10.1109/LSP.2001.838216
  • Karsmakers, P., Pelckmans, K., & Suykens, J. A. K. (2007). Multi-class kernel logistic regression: A fixed-size implementation. IEEE International Conference on Neural Networks - Conference Proceedings, 1756–1761. https://doi.org/10.1109/IJCNN.2007.4371223
  • Killick, R., Fearnhead, P., & Eckley, I. A. (2012). Optimal detection of changepoints with a linear computational cost. Http://Dx.Doi.Org/10.1080/01621459.2012.737745, 107(500), 1590–1598. https://doi.org/10.1080/01621459.2012.737745
  • Kim, A. Y., Marzban, C., Percival, D. B., & Stuetzle, W. (2009). Using labeled data to evaluate change detectors in a multivariate streaming environment. Signal Processing, 89(12), 2529–2536. https://doi.org/10.1016/J.SIGPRO.2009.04.011
  • King, G., & Zeng, L. (2001). Logistic regression in rare events data. Political Analysis, 9(2), 137–163. https://doi.org/10.1093/oxfordjournals.pan.a004868
  • Kleinbaum, D. G., & Klein, M. (2010). Ordinal Logistic Regression (pp. 463–488). https://doi.org/10.1007/978-1-4419-1742-3_13
  • Kleinbaum, David. G., Kupper, L. L., Nizam, A., & Rosenberg, S. E. (2007). Applied regression analysis and multivariable methods (4.th Edition). Duxbury Press.
  • Krugman, R. P., Obstfeld, M., & Melitz, M. (2014). International economics: Theory and policy (10th ed.). Pearson.
  • Lahaye, J., Laurent, S., & Neely, C. J. (2011). Jumps, cojumps and macro announcements. Journal of Applied Econometrics, 26(6), 893–921. https://doi.org/10.1002/JAE.1149
  • Lee, S. S., & Mykland, P. A. (2008). Jumps in financial markets: A new nonparametric test and jump dynamics. The Review of Financial Studies, 21(6), 2535–2563. https://doi.org/10.1093/RFS/HHM056
  • Lin, C.-J., Weng, R. C., & Keerthi, S. S. (2007). Trust region Newton methods for large-scale logistic regression. Proceedings of the 24th International Conference on Machine Learning, 561–568. https://doi.org/10.1145/1273496.1273567
  • Liu, J., Longstaff, F. A., & Pan, J. (2003). Dynamic asset allocation with event risk. The Journal of Finance, 58(1), 231–259. https://doi.org/10.1111/1540-6261.00523
  • Mampaey, M., Tatti, N., & Vreeken, J. (2011). Tell me what I need to know: Succinctly summarizing data with itemsets. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 573–581. https://doi.org/10.1145/2020408.2020499
  • Manner, H., Rodríguez, G., & Stöckler, F. (2024). A changepoint analysis of exchange rate and commodity price risks for Latin American stock markets. International Review of Economics & Finance, 89, 1385-1403.
  • McKinnon, R. I. (1982). Currency substitution and instability in the world dollar standard. The American Economic Review, 72(3), 320–333. https://www.jstor.org/stable/1831535
  • Meese, R. A., & Rogoff, K. (1983). Empirical exchange rate models of the seventies: Do they fit out of sample? Journal of International Economics, 14(1–2), 3–24. https://doi.org/10.1016/0022-1996(83)90017-X
  • Meese, R. A., & Rose, A. K. (1990). Nonlinear, nonparametric, nonessential exchange rate estimation. American Economic Association, 80(2), 192–296. https://www.jstor.org/stable/2006568
  • Muggeo, V. M. R., & Adelfio, G. (2011). Efficient change point detection for genomic sequences of continuous measurements. Bioinformatics, 27(2), 161–166. https://doi.org/10.1093/BIOINFORMATICS/BTQ647
  • Mussa, M. (1986). Nominal exchange rate regimes and the behavior of real exchange rates: Evidence and implications. Carnegie-Rochester Conference Series on Public Policy, 25(C), 117–214. https://doi.org/10.1016/0167-2231(86)90039-4
  • Obstfeld, M., Dornbusch, R., & McKinnon, R. (1995). International currency experience: new lessons and lessons relearned. Brookings Papers on Economic Activity, 1995(1), 119. https://doi.org/10.2307/2534574
  • Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996). A simulation study of the number of events per variable in logistic regression analysis. Journal of Clinical Epidemiology, 49(12), 1373–1379. https://doi.org/10.1016/S0895-4356(96)00236-3
  • Peruga, R. (1996). Learning and the exchange rate: Exchange rate responses to money announcements in the early 1980s. Journal of International Money and Finance, 15(2), 167–190. https://doi.org/10.1016/0261-5606(96)00004-6
  • Piazzesi, M. (2005). Bond yields and the federal reserve. Journal of Political Economy, 113(2), 311–344. https://doi.org/10.1086/427466
  • Rodrik, D. (2009). The real exchange rate and economic growth. Brookings Papers on Economic Activity, 2008(2), 365–412. https://doi.org/10.1353/ECA.0.0020
  • Scott, A. J., & Knott, M. (1974). A cluster analysis method for grouping means in the analysis of variance. Biometrics, 30(3), 507. https://doi.org/10.2307/2529204
  • Talih, M., & Hengartner, N. (2005). Structural learning with time-varying components: tracking the cross-section of financial time series. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67(3), 321–341. https://doi.org/10.1111/J.1467-9868.2005.00504.X
  • Tauchen, G., & Zhou, H. (2011). Realized jumps on financial markets and predicting credit spreads. Journal of Econometrics, 160(1), 102–118. https://doi.org/10.1016/J.JECONOM.2010.03.023
  • Trigg, D. W., & Leach, A. G. (1967). Exponential smoothing with an adaptive response rate. OR, 18(1), 53. https://doi.org/10.2307/3010768
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There are 63 citations in total.

Details

Primary Language English
Subjects Business Systems in Context (Other)
Journal Section Research Article
Authors

Erkan Ağaslan 0000-0002-9293-9052

Savaş Gayaker 0000-0002-7186-1532

Erol Bulut 0000-0002-9293-9052

Early Pub Date October 24, 2024
Publication Date November 1, 2024
Acceptance Date August 28, 2024
Published in Issue Year 2024 Volume: 24 Issue: 4

Cite

APA Ağaslan, E., Gayaker, S., & Bulut, E. (2024). Determinants of Exchange Rate Jumps in Türkiye. Ege Academic Review, 24(4), 621-638. https://doi.org/10.21121/eab.20240409
AMA Ağaslan E, Gayaker S, Bulut E. Determinants of Exchange Rate Jumps in Türkiye. ear. November 2024;24(4):621-638. doi:10.21121/eab.20240409
Chicago Ağaslan, Erkan, Savaş Gayaker, and Erol Bulut. “Determinants of Exchange Rate Jumps in Türkiye”. Ege Academic Review 24, no. 4 (November 2024): 621-38. https://doi.org/10.21121/eab.20240409.
EndNote Ağaslan E, Gayaker S, Bulut E (November 1, 2024) Determinants of Exchange Rate Jumps in Türkiye. Ege Academic Review 24 4 621–638.
IEEE E. Ağaslan, S. Gayaker, and E. Bulut, “Determinants of Exchange Rate Jumps in Türkiye”, ear, vol. 24, no. 4, pp. 621–638, 2024, doi: 10.21121/eab.20240409.
ISNAD Ağaslan, Erkan et al. “Determinants of Exchange Rate Jumps in Türkiye”. Ege Academic Review 24/4 (November 2024), 621-638. https://doi.org/10.21121/eab.20240409.
JAMA Ağaslan E, Gayaker S, Bulut E. Determinants of Exchange Rate Jumps in Türkiye. ear. 2024;24:621–638.
MLA Ağaslan, Erkan et al. “Determinants of Exchange Rate Jumps in Türkiye”. Ege Academic Review, vol. 24, no. 4, 2024, pp. 621-38, doi:10.21121/eab.20240409.
Vancouver Ağaslan E, Gayaker S, Bulut E. Determinants of Exchange Rate Jumps in Türkiye. ear. 2024;24(4):621-38.