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DÖVİZ KURU VOLATİLİTESİNİN DOĞRUSAL VE DOĞRUSAL OLMAYAN YÖNTEMLER İLE İNCELENMESİ

Year 2020, Volume: 19 Issue: 39, 952 - 974, 27.12.2020
https://doi.org/10.46928/iticusbe.763980

Abstract

Bu çalışma Dolar/TL döviz kuru volatilitesini modellemeyi amaçlamaktadır. Bu doğrultuda çalışmada geleneksel değişen varyans tekniklerinin yanı sıra zaman serilerinin kırılma ve asimetri gibi doğrusal olmayan özelliklerini dikkate alan Markov Rejim Değişimi GARCH (MSGARCH) yöntemi kullanılmıştır. Çalışma kapsamında döviz kuru volatilitesi Temmuz 2001’den Şubat 2020’ye kadar uzanan konjonktürel dalgalanmaları ve yapısal değişimleri içeren uzunca bir dönem için incelenmiştir. Diğer yöntemlere göre daha iyi sonuçların elde edildiği MSGARCH modeli bulguları kurda yüksek ve düşük riskli rejimler olduğunu ve bu rejimler arasında sıklıkla geçişler yaşandığını göstermektedir. Düşük volatilite rejiminden yüksek volatiliteye geçiş ani, çok keskin ve yüksek düzeyde gerçekleşmektedir. Buna rağmen volatilitenin yüksek riskli rejimde kararlı bir yapıda olmadığı ve riskin daha düşük olduğu rejime doğru bir eğilim sergilediği tespit edilmiştir. Döviz kurunda yaşanan ani sıçramaların bir süre sonra dengeye gelmesi bunu doğrulamaktadır. Diğer taraftan düşük riskli rejim dönemlerinde ise meydana gelen dalgalanmaların etkileri ortadan kalkmayıp kur üzerinde bunlar korunmakta ve dolayısı ile kur uzun dönemde bir artış trendi göstermektedir.

References

  • Abtahi, S. Y., & Amrollahi Bioki, E. (2020). The Dynamics of Exchange Market Pressure and Inflation in Iran: Regime switching Approach. Iranian Journal of Economic Studies, 8(1), 185-206.
  • Adam, T., Benecká, S., & Matějů, J. (2018). Financial stress and its non-linear impact on CEE exchange rates. Journal of Financial Stability, 36, 346-360.
  • Antonakakis, N., & Darby, J. (2013). Forecasting volatility in developing countries’ nominal exchange returns. Applied Financial Economics, 23(21), 1675-1691.
  • Ardia, D., Bluteau, K., Boudt, K., Catania, L., & Trottier, D. A. (2019). Markov-switching GARCH models in R: The MSGARCH package. Journal of Statistical Software, 91(4), 17 Şubat 2020 tarihinde https://cran.r-project.org/web/packages/MSGARCH/index.html adresinden erişildi.
  • Aysoy, C., Balaban, E., Kogar, C., & Ozcan, C. (1996). Daily volatility in the Turkish foreign exchange market. Discussion Papers No. 9625, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  • Baillie, R. T., & Bollerslev, T. (1989). The message in daily exchange rates: a conditional-variance tale. Journal of Business & Economic Statistics, 7(3), 297-305.
  • Beine, M., Laurent, S., & Lecourt, C. (2003). Official central bank interventions and exchange rate volatility: Evidence from a regime-switching analysis. European Economic Review, 47(5), 891-911.
  • Black, F. (1976). Studies of stock market volatility changes. Proceedings of the American Statistical Association Bisiness and Economic Statistics Section, Washington DC, 177-181.
  • Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
  • Broock, W. A., Scheinkman, J. A., Dechert, W. D., & LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric Reviews, 15(3), 197-235.
  • Brooks, C. (2008). Introductory Econometrics for Finance. 2nd Edition, Cambridge University Press.
  • Chan, K. S., Petruccelli, J. D., Tong, H., & Woolford, S. W. (1985). A multiple-threshold AR (1) model. Journal of Applied Probability, 22(2), 267-279.
  • Chen, R., & Tsay, R. S. (1991). On the ergodicity of TAR (1) processes. The Annals of Applied Probability, 613-634.
  • Cheung, Y. W., & Erlandsson, U. G. (2005). Exchange rates and Markov switching Dynamics. Journal of Business & Economic Statistics, 23(3), 314-320.
  • Christie, A. A. (1982). The stochastic behavior of common stock variances: Value, leverage and interest rate effects. Journal of Financial Economics, 10(4), 407-432.
  • Çağlayan, E., & Dayıoğlu, T. (2009). Döviz Kuru Getiri Volatilitesinin Koşullu Değişen Varyans Modelleri ile Öngörüsü. Ekonometri ve İstatistik e-Dergisi, (9), 1-16.
  • Demirgil, H., & Kesekler, S. (2019). Döviz Kurlarında Oynaklık Yayılım Etkilerinin MGARCH Yöntemi ile Modellenmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 24(4), 1167-1180.
  • Demirgil, H., Yıldırım, S., & Çiçek, Z. (2019). Döviz Kuru Oynaklığında Asimetrik İşaret ve Boyut Yanlılığının Test Edilmesi: Euro/TL Kur Oynaklığı Üzerine Bir İnceleme. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 10(25), 485-494.
  • Ding, Z., Granger, C. W., & Engle, R. F. (1993). A long memory property of stock market returns and a new model. Journal of Empirical Finance, 1(1), 83-106.
  • Engel, C. (1994). Can the Markov switching model forecast exchange rates? Journal of International Economics, 36(1-2), 151-165.
  • Engel, C., & Hamilton, J. D. (1990). Long swings in the dollar: Are they in the data and do markets know it? The American Economic Review, 689-713.
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 987-1007.
  • Engle, R. F., & Ng, V. K. (1993). Measuring and testing the impact of news on volatility. The Journal of Finance, 48(5), 1749-1778.
  • Epaphra, M. (2017). Modeling exchange rate volatility: Application of the GARCH and EGARCH models. Journal of Mathematical Finance, 7(1), 121-143.
  • Fama, E. F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34-105.
  • French, K. R., Schwert, G. W., & Stambaugh, R. F. (1987). Expected stock returns and volatility. Journal of Financial Economics, 19(1), 3-29.
  • Friedman, D., & Vandersteel, S. (1982). Short-run fluctuations in foreign exchange rates. Journal of International Economics, 13(1), 171-186.
  • Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779-1801.
  • Granger, C. W., Newbold, P., & Econom, J. (1974). Spurious regressions in econometrics. Baltagi, Badi H. A Companion of Theoretical Econometrics, 557-561.
  • Gray, S. F. (1996). Modeling the conditional distribution of interest rates as a regime-switching process. Journal of Financial Economics, 42(1), 27-62.
  • Güloğlu, B., & Akman, A. (2007). Türkiye’de döviz kuru oynaklığının SWARCH yöntemi ile analizi. Finans Politik & Ekonomik Yorumlar, 44(512), 43-51.
  • Gür, T. H., & Ertuğrul, H. M. (2012). Döviz kuru volatilitesi modelleri: Türkiye uygulaması. İktisat, İşletme ve Finans, 27(310), 53-77.
  • Gürsakal, S. (2009). Varyans Kırılması Gözlemlenen Serilerde Garch Modelleri: Döviz Kuru Oynaklığı Örneği. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, (32), 319-337.
  • Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica: Journal of the Econometric Society, 357-384.
  • Hamilton, J. D. (1990). Analysis of time series subject to changes in regime. Journal of Econometrics, 45(1-2), 39-70.
  • Higgins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 137-158.
  • Hsieh, D. A, (1988). The statistical properties of daily foreign exchange rates: 1974–1983. Journal of International Economics, 24(1-2), 129-145.
  • Inclan, C., & Tiao, G. C. (1994). Use of cumulative sums of squares for retrospective detection of changes of variance. Journal of the American Statistical Association, 89(427), 913-923.
  • Kiran, B. (2008). Döviz Kuru Volatilitesinin Asimetrik Üslü ARCH (APARCH) Modeli İle Tahmini. Review of Social, Economic & Business Studies, 11/12, 1-18.
  • Klaassen F. (2002). Improving GARCH volatility forecasts with regime-switching GARCH, In: Hamilton J.D., Raj B. (eds) Advances in Markov-Switching Models Studies in Empirical Economics. pp. 223-254. Physica, Heidelberg.
  • Koy, A. (2017). Spot ve Vadeli Piyasa İlişkilerine Markov Rejim Değişim Modelleri Yaklaşımı. Bankacılar Dergisi, 101, 70-87.
  • Koy, A. (2018). Regime Related Volatility in Oil Futures Prices. Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 15(41), 175-184.
  • Kula, V., & Baykut, E. (2017). BIST Banka Endeksi’nin (XBANK) Volatilite Yapısının Markov Rejim Değişimi GARCH Modeli (MSGARCH) ile Analizi. Bankacılar Dergisi, 102, 89-110.
  • Mandelbrot, B. (1963). The variation of some other speculative prices. The Journal of Business, 36(4), 394-414.
  • Mapa, D. S. (2004). A Forecast Comparison of Financial Volatility Models: GARCH (1, 1) is not Enough. The Philippine Statistician, 53(1-4), 1-10.
  • McKenzie, M., & Mitchell, H. (2002). Generalized asymmetric power ARCH modelling of exchange rate volatility. Applied Financial Economics, 12(8), 555-564.
  • Miletić, S. (2015). Modeling and forecasting exchange rate volatility: comparison between EEC and Developed countries. Industrija, 43(1), 7-24.
  • Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347-370.
  • Pehlivanlı, D. (2020). Ulusal Risk Raporu 2020. 1 Şubat 2020 tarihinde https://www.paraborsa.net/i/ulusal-risk-raporu-2020/ adresinden erişildi.
  • Roubaud, D., & Arouri, M. (2018). Oil prices, exchange rates and stock markets under uncertainty and regime-switching. Finance Research Letters, 27, 28-33.
  • Sandoval, J. (2006). Do asymmetric GARCH models fit better exchange rate volatilities on emerging markets? Odeon, 3, 97-116, Universidad Externado de Colombia.
  • Schwert, G. W. (1990). Stock volatility and the crash of’87. The Review of Financial Studies, 3(1), 77-102.
  • Stillwagon, J., & Sullivan, P. (2019). Markov switching in exchange rate models: will more regimes help? Empirical Economics, 1-24.
  • Tong, H. (1983). Threshold models in non-linear time series analysis. Lecture Notes in Statistics. New York, Springer-Verlag.
  • Tsay, R. S. (1989). Testing and modeling threshold autoregressive processes. Journal of the American Statistical Association, 84(405), 231-240.
  • Tsay, R. S. (2005). Analysis of Financial Time Series. 2nd Edition. New Jersey: John Wiley & Sons.
  • Turanlı, M., Cengiz, D., & Parım, C. (2015). Volatility modelling for Euro in Turkey. European Journal of Business and Social Sciences, 3(10), 34-41.
  • Vee, D. C., Gonpot, P. N., & Sookia, N. (2011). Forecasting Volatility of USD/MUR Exchange Rate using a GARCH (1, 1) model with GED and Student’st errors. University of Mauritius Research Journal, 17(1), 1-14.
  • Yaman, M., & Koy, A. (2019). ABD Doları/Türk Lirası Döviz Kuru Volatilitesinin Modellenmesi: 2001-2018 Dönemi. Muhasebe ve Finans İncelemeleri Dergisi, 2(2), 118-129.
  • Zakoian, J. M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
Year 2020, Volume: 19 Issue: 39, 952 - 974, 27.12.2020
https://doi.org/10.46928/iticusbe.763980

Abstract

References

  • Abtahi, S. Y., & Amrollahi Bioki, E. (2020). The Dynamics of Exchange Market Pressure and Inflation in Iran: Regime switching Approach. Iranian Journal of Economic Studies, 8(1), 185-206.
  • Adam, T., Benecká, S., & Matějů, J. (2018). Financial stress and its non-linear impact on CEE exchange rates. Journal of Financial Stability, 36, 346-360.
  • Antonakakis, N., & Darby, J. (2013). Forecasting volatility in developing countries’ nominal exchange returns. Applied Financial Economics, 23(21), 1675-1691.
  • Ardia, D., Bluteau, K., Boudt, K., Catania, L., & Trottier, D. A. (2019). Markov-switching GARCH models in R: The MSGARCH package. Journal of Statistical Software, 91(4), 17 Şubat 2020 tarihinde https://cran.r-project.org/web/packages/MSGARCH/index.html adresinden erişildi.
  • Aysoy, C., Balaban, E., Kogar, C., & Ozcan, C. (1996). Daily volatility in the Turkish foreign exchange market. Discussion Papers No. 9625, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  • Baillie, R. T., & Bollerslev, T. (1989). The message in daily exchange rates: a conditional-variance tale. Journal of Business & Economic Statistics, 7(3), 297-305.
  • Beine, M., Laurent, S., & Lecourt, C. (2003). Official central bank interventions and exchange rate volatility: Evidence from a regime-switching analysis. European Economic Review, 47(5), 891-911.
  • Black, F. (1976). Studies of stock market volatility changes. Proceedings of the American Statistical Association Bisiness and Economic Statistics Section, Washington DC, 177-181.
  • Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
  • Broock, W. A., Scheinkman, J. A., Dechert, W. D., & LeBaron, B. (1996). A test for independence based on the correlation dimension. Econometric Reviews, 15(3), 197-235.
  • Brooks, C. (2008). Introductory Econometrics for Finance. 2nd Edition, Cambridge University Press.
  • Chan, K. S., Petruccelli, J. D., Tong, H., & Woolford, S. W. (1985). A multiple-threshold AR (1) model. Journal of Applied Probability, 22(2), 267-279.
  • Chen, R., & Tsay, R. S. (1991). On the ergodicity of TAR (1) processes. The Annals of Applied Probability, 613-634.
  • Cheung, Y. W., & Erlandsson, U. G. (2005). Exchange rates and Markov switching Dynamics. Journal of Business & Economic Statistics, 23(3), 314-320.
  • Christie, A. A. (1982). The stochastic behavior of common stock variances: Value, leverage and interest rate effects. Journal of Financial Economics, 10(4), 407-432.
  • Çağlayan, E., & Dayıoğlu, T. (2009). Döviz Kuru Getiri Volatilitesinin Koşullu Değişen Varyans Modelleri ile Öngörüsü. Ekonometri ve İstatistik e-Dergisi, (9), 1-16.
  • Demirgil, H., & Kesekler, S. (2019). Döviz Kurlarında Oynaklık Yayılım Etkilerinin MGARCH Yöntemi ile Modellenmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 24(4), 1167-1180.
  • Demirgil, H., Yıldırım, S., & Çiçek, Z. (2019). Döviz Kuru Oynaklığında Asimetrik İşaret ve Boyut Yanlılığının Test Edilmesi: Euro/TL Kur Oynaklığı Üzerine Bir İnceleme. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 10(25), 485-494.
  • Ding, Z., Granger, C. W., & Engle, R. F. (1993). A long memory property of stock market returns and a new model. Journal of Empirical Finance, 1(1), 83-106.
  • Engel, C. (1994). Can the Markov switching model forecast exchange rates? Journal of International Economics, 36(1-2), 151-165.
  • Engel, C., & Hamilton, J. D. (1990). Long swings in the dollar: Are they in the data and do markets know it? The American Economic Review, 689-713.
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 987-1007.
  • Engle, R. F., & Ng, V. K. (1993). Measuring and testing the impact of news on volatility. The Journal of Finance, 48(5), 1749-1778.
  • Epaphra, M. (2017). Modeling exchange rate volatility: Application of the GARCH and EGARCH models. Journal of Mathematical Finance, 7(1), 121-143.
  • Fama, E. F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34-105.
  • French, K. R., Schwert, G. W., & Stambaugh, R. F. (1987). Expected stock returns and volatility. Journal of Financial Economics, 19(1), 3-29.
  • Friedman, D., & Vandersteel, S. (1982). Short-run fluctuations in foreign exchange rates. Journal of International Economics, 13(1), 171-186.
  • Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779-1801.
  • Granger, C. W., Newbold, P., & Econom, J. (1974). Spurious regressions in econometrics. Baltagi, Badi H. A Companion of Theoretical Econometrics, 557-561.
  • Gray, S. F. (1996). Modeling the conditional distribution of interest rates as a regime-switching process. Journal of Financial Economics, 42(1), 27-62.
  • Güloğlu, B., & Akman, A. (2007). Türkiye’de döviz kuru oynaklığının SWARCH yöntemi ile analizi. Finans Politik & Ekonomik Yorumlar, 44(512), 43-51.
  • Gür, T. H., & Ertuğrul, H. M. (2012). Döviz kuru volatilitesi modelleri: Türkiye uygulaması. İktisat, İşletme ve Finans, 27(310), 53-77.
  • Gürsakal, S. (2009). Varyans Kırılması Gözlemlenen Serilerde Garch Modelleri: Döviz Kuru Oynaklığı Örneği. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, (32), 319-337.
  • Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica: Journal of the Econometric Society, 357-384.
  • Hamilton, J. D. (1990). Analysis of time series subject to changes in regime. Journal of Econometrics, 45(1-2), 39-70.
  • Higgins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 137-158.
  • Hsieh, D. A, (1988). The statistical properties of daily foreign exchange rates: 1974–1983. Journal of International Economics, 24(1-2), 129-145.
  • Inclan, C., & Tiao, G. C. (1994). Use of cumulative sums of squares for retrospective detection of changes of variance. Journal of the American Statistical Association, 89(427), 913-923.
  • Kiran, B. (2008). Döviz Kuru Volatilitesinin Asimetrik Üslü ARCH (APARCH) Modeli İle Tahmini. Review of Social, Economic & Business Studies, 11/12, 1-18.
  • Klaassen F. (2002). Improving GARCH volatility forecasts with regime-switching GARCH, In: Hamilton J.D., Raj B. (eds) Advances in Markov-Switching Models Studies in Empirical Economics. pp. 223-254. Physica, Heidelberg.
  • Koy, A. (2017). Spot ve Vadeli Piyasa İlişkilerine Markov Rejim Değişim Modelleri Yaklaşımı. Bankacılar Dergisi, 101, 70-87.
  • Koy, A. (2018). Regime Related Volatility in Oil Futures Prices. Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 15(41), 175-184.
  • Kula, V., & Baykut, E. (2017). BIST Banka Endeksi’nin (XBANK) Volatilite Yapısının Markov Rejim Değişimi GARCH Modeli (MSGARCH) ile Analizi. Bankacılar Dergisi, 102, 89-110.
  • Mandelbrot, B. (1963). The variation of some other speculative prices. The Journal of Business, 36(4), 394-414.
  • Mapa, D. S. (2004). A Forecast Comparison of Financial Volatility Models: GARCH (1, 1) is not Enough. The Philippine Statistician, 53(1-4), 1-10.
  • McKenzie, M., & Mitchell, H. (2002). Generalized asymmetric power ARCH modelling of exchange rate volatility. Applied Financial Economics, 12(8), 555-564.
  • Miletić, S. (2015). Modeling and forecasting exchange rate volatility: comparison between EEC and Developed countries. Industrija, 43(1), 7-24.
  • Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347-370.
  • Pehlivanlı, D. (2020). Ulusal Risk Raporu 2020. 1 Şubat 2020 tarihinde https://www.paraborsa.net/i/ulusal-risk-raporu-2020/ adresinden erişildi.
  • Roubaud, D., & Arouri, M. (2018). Oil prices, exchange rates and stock markets under uncertainty and regime-switching. Finance Research Letters, 27, 28-33.
  • Sandoval, J. (2006). Do asymmetric GARCH models fit better exchange rate volatilities on emerging markets? Odeon, 3, 97-116, Universidad Externado de Colombia.
  • Schwert, G. W. (1990). Stock volatility and the crash of’87. The Review of Financial Studies, 3(1), 77-102.
  • Stillwagon, J., & Sullivan, P. (2019). Markov switching in exchange rate models: will more regimes help? Empirical Economics, 1-24.
  • Tong, H. (1983). Threshold models in non-linear time series analysis. Lecture Notes in Statistics. New York, Springer-Verlag.
  • Tsay, R. S. (1989). Testing and modeling threshold autoregressive processes. Journal of the American Statistical Association, 84(405), 231-240.
  • Tsay, R. S. (2005). Analysis of Financial Time Series. 2nd Edition. New Jersey: John Wiley & Sons.
  • Turanlı, M., Cengiz, D., & Parım, C. (2015). Volatility modelling for Euro in Turkey. European Journal of Business and Social Sciences, 3(10), 34-41.
  • Vee, D. C., Gonpot, P. N., & Sookia, N. (2011). Forecasting Volatility of USD/MUR Exchange Rate using a GARCH (1, 1) model with GED and Student’st errors. University of Mauritius Research Journal, 17(1), 1-14.
  • Yaman, M., & Koy, A. (2019). ABD Doları/Türk Lirası Döviz Kuru Volatilitesinin Modellenmesi: 2001-2018 Dönemi. Muhasebe ve Finans İncelemeleri Dergisi, 2(2), 118-129.
  • Zakoian, J. M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
There are 60 citations in total.

Details

Primary Language Turkish
Journal Section Research Articles
Authors

Musa Gün 0000-0002-5020-9342

Publication Date December 27, 2020
Submission Date July 4, 2020
Acceptance Date September 20, 2020
Published in Issue Year 2020 Volume: 19 Issue: 39

Cite

APA Gün, M. (2020). DÖVİZ KURU VOLATİLİTESİNİN DOĞRUSAL VE DOĞRUSAL OLMAYAN YÖNTEMLER İLE İNCELENMESİ. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(39), 952-974. https://doi.org/10.46928/iticusbe.763980