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The Relationship between the Exchange Rates and Stock Returns in Turkey: MS-VAR Approach

Yıl 2021, Cilt: 35 Sayı: 2, 551 - 576, 18.04.2021
https://doi.org/10.16951/atauniiibd.789496

Öz

In this study; the relationship between exchange rate and stock prices, which may affect economic activity by showing sensitive changes against social, economic and political factors, is examined. In the literatüre, this relationship is based on two approaches, traditional and portfolio. There is a positive causal relationship between the variables from exchange rates to stock prices in the traditional approach. There is a negative causal relationship between the variables from stock prices to exchange rates in the portfolio approach. In the study, the period 03:0:2003-04:11:2019 (weekly) were investigated for Turkey. For this purpose, traditional Granger test, traditional impulse-response analyzes, Diks-Panchenko nonlinear causality test, MS-VAR model, MS-Granger test and impulse-response analyzes based on regimes were estimated. According to the results, it is appropriate to use two-regime MS-VAR model, low and high volatility period, for the relationship between exchange rate and stock prices. MS-VAR test results showed that there was a negative and significant relationship between the variables. Both nonlinear test and MS-Granger test showed that the direction of causality was unidirectional from stock prices to exchange rate. The findings shows that, in the studied period, the portfolio approach is valid for Turkey

Kaynakça

  • Ahmed Z. I., Mustafa K. (2019). “Regime-Dependent Effects on Stock Market Return Dynamics: Evidence From Saarc Countries”. Asian Development Policy Review, 7 (2), 111-132.
  • Arat, K. (2003). “Türkiye’de Optimum Döviz Kuru Rejimi Seçimi ve Döviz Kurlarından Fiyatlara Geçiş Etkisinin İncelenmesi”. Uzmanlık Yeterlilik Tezi, Türkiye Cumhuriyet Merkez Bankası Dış İlişkiler Genel Müdürlüğü, Ankara.
  • Brock, W. A., Dechert, W. D., Scheinkman, J. A., LeBaron, B. (1996). “A Test for Independence Based on The Correlation Dimension”. Econometric Reviews, 15(3), 197-235.
  • Chkili, W., Nguyen, D. K. (2014). “Exchange Rate Movements and Stock Market Returns in a Regime-Switching Environment: Evidence for BRICS Countries”. Research in International Business and Finance. 31, 46-56.
  • Çevik, E.İ., Çevik, N., Gürkan, S. (2012). “ABD, Almanya ve Türkiye Hisse Senedi Piyasaları Arasındaki İlişkinin MS-VAR Model ile Analizi”. BDDK Bankacılık ve Finansal Piyasalar, 6(1), 133-155.
  • Davies, N., C. M., Triggsan, D. P. Newbold (1977). “Significance of The Box-Pierce Portmanteau Statistics in Finite Samples”. Biometrika, 64, 517-522.
  • Davies, R. B. (1987): "Hypothesis Testing when a Nuisance Parameter is Present Only Under The Alternative," Biometrika, 74(1), 33-43.
  • Dickey, D. A., Fuller, W. A. (1979). “Distribution of The Estimators for Autoregressive Time Series With A Unit Root”. Journal of American Statistical Association, 74(366), 427-431.
  • Diks, C., Panchenko V. (2006). “A New Statistic and Practical Guidelines for Nonparametric Granger Causality Testing” Journal of Economic Dynamics and Control, 30, 1647-1669
  • Di Sanzo S. (2009). “Testing for Linearity in Markov Switching Models: A Bootstrap Approach”. Statistical Methods and Applications, 18(2), 153–168. Droumaguet M. (2012). “Markov-Switching Vector Autoregressive Models: Monte Carlo Experiment, Impulse Response Analysis and Granger Causal Analysis”. Europen Universisty Institute, PhD Thesis
  • Droumaguet, M., Warne, A., Woźniak, T. (2016). “Granger Causality and Regime Inference in Markov Switching VAR Models with Bayesian Methods”. Journal of Applied Econometrics, 32(4), 802–818.
  • Ehrmann M., Ellison M., Valla N. (2001). “Regime Dependent Impulse Response Functions in A Markov-Switching Vector Autoregression Model”. Discussion Paper, Bank of Finland, 11, 1-25.
  • Ehrmann M., Ellison M., Valla N. (2003). “Regime Dependent Impulse Response Functions in a Markov Switching Vector Autoregression Model”. Economics Letters, 78, 295-299.
  • Granger, C. W. J., (1969). “Investigating Causal Relations by Econometric Models and Cross - Spectral Methods”. Econometrica, 37(3), 424-438.
  • Hamilton, J. D. (1989). “A New Approach to The Economic Analysis of Nonstationary Time Series and The Business Cycle”. Econometrica, 57(2), 357–384.
  • Ilzetzki, E., Reinhart C. M., Rogoff, K. S.(2017). “The Country Chronologies to Exchange Rate Arrangements Into The 21st Century: Will The Anchor Currency Hold? Working Paper NBER No:23135
  • Ismail, M. T., Isa Z. B. (2009). “Modelling The Interactions of Stock Price and Exchange Rate in Malaysia”. The Singapore Economic Review, 54(4), 605-619.
  • Koy, A. (2016). “Borsa İstanbul’un Doğrusal Olmayan Dinamiklerinin Markov Rejim Değişim Modelleriyle Açıklanması”. 1. Lisansüstü İşletme Öğrencileri Sempozyum Bildirileri, Nisan 2016, (ss.175-180), İstanbul: İstanbul Ticaret Üniversitesi.
  • Krolzig, H. M. (1997). Markov Switching Vector Autoregressions. Modelling, Statis‐ tical Inference and Application to Business Cycle Analysis. Berlin: Springer.
  • Krolzig, H. M.,Toro, J. (1999). “A New Approach to The Analysis of Shocks and The Cycle in A Model of Output and Employment”. Economics Working Papers eco99/30, European University Institute.
  • Krolzig H. M. (2000). “Predicting Markov-Switching Vector Autoregressive Processes, Oxford University”. Working Paper 2000W31.
  • Krolzig H. M. (2003). “Constructing Turning Point Chronologies with Markov-Switching Vector Autoregressive Models : The Euro – Zone Business Cycle”. Department of Economics and Nuffield College, Oxford University, 1-38.
  • Krolzig H. M. (2006). “Impulse-Response Analysis in Markov Switching Vector Autoregressive Models”. Economics Department, University of Kent, Keynes College, Canterbury CT2 7NP, 1-17.
  • Leybourne, S., Newbold, P., Vougas, D. (1998). Unit Roots And Smooth Transitions, Journal of Time Series Analysis, 19(1), 83-96. McLeod, A. I., Li, W. K. (1983). “Diagnostic Checking ARMA Time Series Models Using Squared Residual Autocorrelations”. Journal of Time Series Analysis, 4(4), 269-273.
  • Psaradakis Z., Ravn M., Sola M. (2005). “Markov Switching Causality and Money-Output Relationship”. Journal of Policy Modeling, 20, 665-683. Sierimo, C. (2002). Testing The Effıcient Market Hypothesis of The Helsinki Stock Exchange Further Empirical Evidence Based on Nonlinear Models. (Research Reports) Helsinki: University of Helsinki.
  • Sosa, M., Ortiz, E., Cabello, A. (2018). “Dynamic Linkages Between Stock Market and Exchange Rate in MILA Countries: A Markov Regime Switching Approach (2003-2016)”. Análisis Económico, 33(83), 57-74.
  • Warne A. (2000). “Causality and Regime Inference in a Markov Switching VAR”. Sveriges Riksbank, 1-41.

Türkiye’de Döviz ve Hisse Senedi Getirileri Arasındaki İlişki: MS-VAR Yaklaşımı

Yıl 2021, Cilt: 35 Sayı: 2, 551 - 576, 18.04.2021
https://doi.org/10.16951/atauniiibd.789496

Öz

Bu çalışmada; sosyal, ekonomik ve siyasi faktörler karşısında hassas değişimler göstererek ekonomik aktiviteyi etkileyebilen döviz kuru ile hisse senedi fiyatları arasındaki ilişki incelenmiştir. Bu ilişki literatürde geleneksel ve portföy olmak üzere iki yaklaşıma dayanmaktadır. Geleneksel yaklaşımda, döviz kurlarından hisse senedi fiyatlarına doğru olmak üzere aynı yönlü bir nedensellik ilişkisi bulunmaktadır. Portföy yaklaşımında ise hisse senedi fiyatlarından döviz kurlarına doğru olmak üzere ters yönlü bir nedensellik ilişkisi bulunmaktadır. Çalışmada, 03:01:2003-04:11:2019 dönemi (haftalık) alınmıştır. Bu amaçla Türkiye için geleneksel Granger nedensellik sınaması, geleneksel etki tepki analizleri, Diks-Panchenko doğrusal olmayan nedensellik sınaması, MS-VAR modeli, MS-Granger nedensellik sınaması ve rejimlere bağlı etki tepki analizleri tahmin edilmiştir. Bulgulara göre dolar kuru ile hisse senedi fiyatları arasındaki ilişki düşük ve yüksek oynaklık dönemi olmak üzere iki rejimli MS-VAR modeli ile temsil edilmiştir. MS-VAR modeline göre değişkenler arasında ters yönlü ve anlamlı bir ilişki bulunmuştur. Doğrusal olmayan nedensellik sınama ve MS-Granger sınaması ilişkinin yönünü hisse senedi fiyatlarından dolar kuruna doğru olmak üzere tek yönlü bir şekilde belirlemiştir. Bu çalışılan dönem için Türkiye’de portföy yaklaşımının geçerli olduğunu göstermektedir.

Kaynakça

  • Ahmed Z. I., Mustafa K. (2019). “Regime-Dependent Effects on Stock Market Return Dynamics: Evidence From Saarc Countries”. Asian Development Policy Review, 7 (2), 111-132.
  • Arat, K. (2003). “Türkiye’de Optimum Döviz Kuru Rejimi Seçimi ve Döviz Kurlarından Fiyatlara Geçiş Etkisinin İncelenmesi”. Uzmanlık Yeterlilik Tezi, Türkiye Cumhuriyet Merkez Bankası Dış İlişkiler Genel Müdürlüğü, Ankara.
  • Brock, W. A., Dechert, W. D., Scheinkman, J. A., LeBaron, B. (1996). “A Test for Independence Based on The Correlation Dimension”. Econometric Reviews, 15(3), 197-235.
  • Chkili, W., Nguyen, D. K. (2014). “Exchange Rate Movements and Stock Market Returns in a Regime-Switching Environment: Evidence for BRICS Countries”. Research in International Business and Finance. 31, 46-56.
  • Çevik, E.İ., Çevik, N., Gürkan, S. (2012). “ABD, Almanya ve Türkiye Hisse Senedi Piyasaları Arasındaki İlişkinin MS-VAR Model ile Analizi”. BDDK Bankacılık ve Finansal Piyasalar, 6(1), 133-155.
  • Davies, N., C. M., Triggsan, D. P. Newbold (1977). “Significance of The Box-Pierce Portmanteau Statistics in Finite Samples”. Biometrika, 64, 517-522.
  • Davies, R. B. (1987): "Hypothesis Testing when a Nuisance Parameter is Present Only Under The Alternative," Biometrika, 74(1), 33-43.
  • Dickey, D. A., Fuller, W. A. (1979). “Distribution of The Estimators for Autoregressive Time Series With A Unit Root”. Journal of American Statistical Association, 74(366), 427-431.
  • Diks, C., Panchenko V. (2006). “A New Statistic and Practical Guidelines for Nonparametric Granger Causality Testing” Journal of Economic Dynamics and Control, 30, 1647-1669
  • Di Sanzo S. (2009). “Testing for Linearity in Markov Switching Models: A Bootstrap Approach”. Statistical Methods and Applications, 18(2), 153–168. Droumaguet M. (2012). “Markov-Switching Vector Autoregressive Models: Monte Carlo Experiment, Impulse Response Analysis and Granger Causal Analysis”. Europen Universisty Institute, PhD Thesis
  • Droumaguet, M., Warne, A., Woźniak, T. (2016). “Granger Causality and Regime Inference in Markov Switching VAR Models with Bayesian Methods”. Journal of Applied Econometrics, 32(4), 802–818.
  • Ehrmann M., Ellison M., Valla N. (2001). “Regime Dependent Impulse Response Functions in A Markov-Switching Vector Autoregression Model”. Discussion Paper, Bank of Finland, 11, 1-25.
  • Ehrmann M., Ellison M., Valla N. (2003). “Regime Dependent Impulse Response Functions in a Markov Switching Vector Autoregression Model”. Economics Letters, 78, 295-299.
  • Granger, C. W. J., (1969). “Investigating Causal Relations by Econometric Models and Cross - Spectral Methods”. Econometrica, 37(3), 424-438.
  • Hamilton, J. D. (1989). “A New Approach to The Economic Analysis of Nonstationary Time Series and The Business Cycle”. Econometrica, 57(2), 357–384.
  • Ilzetzki, E., Reinhart C. M., Rogoff, K. S.(2017). “The Country Chronologies to Exchange Rate Arrangements Into The 21st Century: Will The Anchor Currency Hold? Working Paper NBER No:23135
  • Ismail, M. T., Isa Z. B. (2009). “Modelling The Interactions of Stock Price and Exchange Rate in Malaysia”. The Singapore Economic Review, 54(4), 605-619.
  • Koy, A. (2016). “Borsa İstanbul’un Doğrusal Olmayan Dinamiklerinin Markov Rejim Değişim Modelleriyle Açıklanması”. 1. Lisansüstü İşletme Öğrencileri Sempozyum Bildirileri, Nisan 2016, (ss.175-180), İstanbul: İstanbul Ticaret Üniversitesi.
  • Krolzig, H. M. (1997). Markov Switching Vector Autoregressions. Modelling, Statis‐ tical Inference and Application to Business Cycle Analysis. Berlin: Springer.
  • Krolzig, H. M.,Toro, J. (1999). “A New Approach to The Analysis of Shocks and The Cycle in A Model of Output and Employment”. Economics Working Papers eco99/30, European University Institute.
  • Krolzig H. M. (2000). “Predicting Markov-Switching Vector Autoregressive Processes, Oxford University”. Working Paper 2000W31.
  • Krolzig H. M. (2003). “Constructing Turning Point Chronologies with Markov-Switching Vector Autoregressive Models : The Euro – Zone Business Cycle”. Department of Economics and Nuffield College, Oxford University, 1-38.
  • Krolzig H. M. (2006). “Impulse-Response Analysis in Markov Switching Vector Autoregressive Models”. Economics Department, University of Kent, Keynes College, Canterbury CT2 7NP, 1-17.
  • Leybourne, S., Newbold, P., Vougas, D. (1998). Unit Roots And Smooth Transitions, Journal of Time Series Analysis, 19(1), 83-96. McLeod, A. I., Li, W. K. (1983). “Diagnostic Checking ARMA Time Series Models Using Squared Residual Autocorrelations”. Journal of Time Series Analysis, 4(4), 269-273.
  • Psaradakis Z., Ravn M., Sola M. (2005). “Markov Switching Causality and Money-Output Relationship”. Journal of Policy Modeling, 20, 665-683. Sierimo, C. (2002). Testing The Effıcient Market Hypothesis of The Helsinki Stock Exchange Further Empirical Evidence Based on Nonlinear Models. (Research Reports) Helsinki: University of Helsinki.
  • Sosa, M., Ortiz, E., Cabello, A. (2018). “Dynamic Linkages Between Stock Market and Exchange Rate in MILA Countries: A Markov Regime Switching Approach (2003-2016)”. Análisis Económico, 33(83), 57-74.
  • Warne A. (2000). “Causality and Regime Inference in a Markov Switching VAR”. Sveriges Riksbank, 1-41.
Toplam 27 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Funda Durgun 0000-0001-7254-227X

Mehmet Temurlenk 0000-0002-7910-0885

Yayımlanma Tarihi 18 Nisan 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 35 Sayı: 2

Kaynak Göster

APA Durgun, F., & Temurlenk, M. (2021). Türkiye’de Döviz ve Hisse Senedi Getirileri Arasındaki İlişki: MS-VAR Yaklaşımı. Atatürk Üniversitesi İktisadi Ve İdari Bilimler Dergisi, 35(2), 551-576. https://doi.org/10.16951/atauniiibd.789496

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