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Geleneksel olmayan para politikası uygulamaları döneminde Dolar-TL’nin volatilite dinamiklerinin incelenmesi: Asimetrik stokastik volatilite modeline dayalı analizler

Year 2020, Volume: 13 Issue: 1, 1 - 17, 30.06.2020

Abstract

Bu çalışmada geleneksel
olmayan para politikası uygulamalarının 
söz konusu  olduğu dönemde Dolar-TL
volatilitesinin temel dinamikleri incelenmiştir. Çalışmada student t dağılımı
varsayımı altında asimetrik stokastik volatilite (ASV) modelinden  yararlanılmış ve bu modelin  parametrelerinin tahmininde Bayesyen  yaklaşımına dayalı  MCMC (Markov Chain Monte Carlo, MCMC)
algoritması kullanılmıştır. Çalışma 2 Ocak 2002 ile 29 Eylül 2017 dönemini
kapsamakta ve günlük verilerden oluşmaktadır. Çalışma bulguları geleneksel
olmayan para politikası  uygulamalarının
söz konusu  olduğu döneminde hem Dolar-TL
volatilitesindeki değişkenliğin hem de Dolar-TL kaynaklı finansal riskin
geleneksel para politikası uygulamalarının söz konusu olduğu  göre  döneme  göre  azaldığını 
göstermektedir.

References

  • [1] E.Başçı, H. Kara, 2011, Finansal istikrara ve para politikası, İktisat İşletme ve Finans, 26 (302), 9-25.
  • [2] A.H. Kara, 2012, Küresel kriz sonrası para politikası, İktisat İşletme ve Finans, 27 (315), 9-36.
  • [3] M. Mühleisen, 2010, A New Index of Currency Mismatch and Systemic Risk, IMF Working Paper WP/10/263. file:///C:/Users/asus/Downloads/_wp10263.pdf
  • [4] M.R. King, C. Osler, D. Rime, 2011, Foreign exchange market structure, players and evolution, Norges Bank Working Paper, No:10.Erişim tarihi:07.02.2014. http://www.unich.it/ ~vitale/ Rime-2.pdf.
  • [5] N. Foley-Fisher, R. Ramcharan, E. Yu, 2016, The impact of unconventional monetary policy on firm financing constraints: Evidence from the maturity extension program, Journal of Financial Economics, 122 (2), 409-429.
  • [6] P. Puonti, 2019, Data-driven structural BVAR analysis of unconventional monetary policy, Journal of Macroeconomics, 61, 103-131.
  • [7] L. Wang, 2019, Measuring the effects of unconventional monetary policy on MBS spreads: A comparative study, The North American Journal of Economics and Finance, 49, 235-251.
  • [8] J.C. Wu, J. Zhang, 2019, Global effective lower bound and unconventional monetary policy, Journal of International Economics, 118, 200-216.
  • [9] M. McMahon, M.U. Peiris, H. Polemarchakis, 2018, Perils of unconventional monetary policy, Journal of Economic Dynamics and Control, 93, 92-114.
  • [10] K. D. Sheedy, 2017, Conventional and unconventional monetary policy rules, Journal of Macroeconomics, 54, 127-147.
  • [11] S. Ambler, F. Rumler, 2019, The effectiveness of unconventional monetary policy announcements in the euro area: An event and econometric study, Journal of International Money and Finance, 94, 48- 61.
  • [12] D. Kenourgios, E. Drakonaki, D. Dimitriou, 2019, ECB’s unconventional monetary policy and cross-financial-market correlation dynamics, The North American Journal of Economics and Finance, 50, 1010-45.
  • [13] E. Galariotis, P. Makrichoriti, S. Spyrou, 2018, The impact of conventional and unconventional monetary policy on expectations and sentiment, Journal of Banking & Finance, 86, 1-20.
  • [14] S. Papadamou, Ν. A. Kyriazis, P. G. Tzeremes, 2019, Unconventional monetary policy effects on output and inflation: A meta-analysis, International Review of Financial Analysis, 61, 295-305.
  • [15] C. Lutz, 2015, The impact of conventional and unconventional monetary policy on investor sentiment, Journal of Banking & Finance, 61, 89-105.
  • [16] C. Dreger, J. Wolters, 2015, Unconventional monetary policy and money demand, Journal of Macroeconomics, 46, 40-54.
  • [17] Y. Kiendrebeogo, 2016, Unconventional monetary policy and capital flows, Economic Modelling, 54, 412-424.
  • [18] E. Mamatzakis, T. Bermpei, 2016, What is the effect of unconventional monetary policy on bank performance?, Journal of International Money and Finance, 67, 239-263.
  • [19] L. Wang, 2016, Unconventional monetary policy and aggregate bank lending: Does financial structure matter?, Journal of Policy Modeling, 38 (6), 1060-1077.
  • [20] F. Ferrante, 2019, Risky lending, bank leverage and unconventional monetary policy, Journal of Monetary Economics, 101, 100-127.
  • [21] C. J. Neely, 2015, Unconventional monetary policy had large international effects, Journal of Banking & Finance, 52, 101-111.
  • [22] M. Binici, H. Kara, P. Özlü, 2016, Faiz koridoru ve banka faizleri : Parasal aktarım mekanizmasına dair bazı bulgular, Türkiye Cumhuriyet Merkez Bankası Çalışma Tebliği, No: 16/ 08. http://www.tcmb.gov.tr/wps/wcm/ connect/10f843d3-2e9a-4652-880a-54741d03a396/wp1608.pdf?. ( Erişim Tarihi, Mayıs 2017).
  • [23] H.A. Küçükgöde, 2016, Türkiye Cumhuriyet Merkez Bankası’nın faiz koridoru politikasının etkinliği, İşletme İktisadi Enstitüsü Yönetim Dergisi, 81, 11-25.
  • [24] S. Varlik, H. Berumet, 2017, Multiple policy interest rates and economic performance in a multiple monetary-policy-tool environment, International Review of Economics and Finance, 52, 107-126.
  • [25] Inoue, B. Rossi, 2019, The effects of conventional and unconventional monetary policy on exchange rates, Journal of International Economics, 118, 419–447.
  • [26] J. Rogers, C. Scotti, J.H. Wright, 2014, Evaluating asset-market effects of unconventional monetary policy: amulti-country review, Economic Policy, 29, 3–50.
  • [27] J. Rogers, C. Scotti, J.H. Wright, 2016, Unconventional monetary policy and international risk premia, Board of Governors IFD Papers, No. 1172.
  • [28] R.Glick, S. Leduc, 2015, Unconventional monetary policy and the dollar: Conventional signs, unconventional magnitudes, Federal Reserve Bank of San Francisco W.P (2015–18).
  • [29] P. Anaya, M. Hachula, C. J. Offermanns, 2017, Spillovers of U.S. unconventional monetary policy to emerging markets: The role of capital flows, Journal of International Money and Finance, 73, 275-295.
  • [30] A. Apostolou, J. Beirne, 2019, Volatility spillovers of unconventional monetary policy to emerging market economies, Economic Modelling, 79, 118-129.
  • [31] E. Claus, I. Claus, L. Krippner, 2018, Asset market responses to conventional and unconventional monetary policy shocks in the United States, Journal of Banking & Finance, 97, 270-282.
  • [32] J. Thornton, C. di Tommaso,2018, Unconventional monetary policy and the ‘currency wars’, Finance Research Letters, 26, 250-254.
  • [33] S. Bernhard, T. Ebner, 2017, Cross-border spillover effects of unconventional monetary policies on Swiss asset prices, Journal of International Money and Finance, 75, 109-127.
  • [34] Y.Yalçın, 2007, Stokastik oynaklık modeli ile İstanbul Menkul Kıymetler Borsası’nda kaldıraç etkisinin incelenmesi, Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Dergisi, 22(2), 357- 365.
  • [35] A.Özün, M. Türk, 2008, Döviz kurlarının öngörüsünde stokastik oynaklık modelleri, İktisat İşletme ve Finans, 23 (265), 50-67.
  • [36] V.Abiyev, 2015, Time-varying beta and its modeling techniques for Turkish industry portfolio, İktisat İşletme ve Finans, 30(352), 79-108.
  • [37] Ö.Göktaş, Hepsağ, 2016, BIST100 endeksinin volatil davranışlarının simetrik ve asimetrik stokastik volatilite modelleri ile Analizi, Ekonomik Yaklaşım, 27 (99), 1-15.
  • [38] E.Jacquier, N.G. Polson, P.E. Rossi, 2004, Bayesian analysis of stochastic volatility models with fat-tails and correlated errors, Journal of Econometrics, 122, 185-212.
  • [39] J.J.J. Wang, J.S.K. Chan, S.T.B. Choy, 2011, Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures, Computational Statistics & Data Analysis, 55(1), 852-862.
  • [40] A.Assaf, 2017, The stochastic volatility model , regime switching and Value-at-Risk (VaR) in international equity markets, Journal of Mathematical Finance, 7, 491-512.
  • [41] N.Krichene, 2003, Modeling stochastic volatility with application to stock returns, IMF Working Paper, No:03/125. https://www.imf.org/en/Publications/WP/Issues/2016/12/30 /.
  • [42] H.Küçük, P. Özlü, A. Takaslı, D. Ünalmış, C. Yüksel, 2013, Likidite yönetimi ve BIST faiz farkı, Türkiye Cumhuriyet Merkez Bankası Ekonomi Notları, Sayı: 2013-25/ 23 Ekim 2013.http://www.academia.edu/4870 421/Likidite_Y%C3%B6netimi_ve_BIST_Faiz_Fark%C4%B1. ( Erişim Tarihi, Nisan 2017).
  • [43] Y.Omori, S.Chib, N. Shephard, J. Nakajima, 2007, Stochastic volatility with leverage: Fast and efficient likelihood inferences, Journal of Econometrics, 140, 425-449.
  • [44] F. Selçuk, (2004), Free float and stochastic volatility: The experience of a small open economy, Physica A: Statistical Mechanics and its Applications 342(3-4).
  • [45] D.Hendricks,1996, Evaluation of value at risk modeling using historical data, Economics Policy Review, Federal Reserve Bank of New York.
  • [46] P.Giot, S. Laurent, 2003. Market risk in commodity markets: A VaR approach, Energy Economics, 25, 435–457.
  • [47] J.Nakajima, Y. Omori, 2009, Leverage, heavy-tails and correlated jumps in stochastic volatiliy models, Computational Statistics and Data Analysis, 53, 2335-2353.
  • [48] J.Nakajima, 2008, EGARCH and stochastic volatility: Modeling jumps and heavy-tails for stock returns, IMES Institute for Monetary and Economic Studies, Bank of Japan, No: 2008-E-23. https://www.imes.boj.or.jp/ research/abstracts/english/08-E23.html.
  • [49] J.Nakajima, Y. Omori, 2012, Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution, Computational Statistics and Data Anlysis, 56, 3690-3704.
  • [50] S.Kim, N. Shephard, S. Chib, 1998, Stochastic Volatility: Likelihood inference and comparison with ARCH models, Review of Economic Studies, 65, 361-393.
  • [51] J. Yu, 2005, On leverage in a stochastic volatility model, Journal of Econometrics, 127, 165-178.
  • [52] P.L. Lafosse, G. Rodriguez, 2018, An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns, The Quarterly Review of Economics and Finance, 69, 155-173.
Year 2020, Volume: 13 Issue: 1, 1 - 17, 30.06.2020

Abstract

References

  • [1] E.Başçı, H. Kara, 2011, Finansal istikrara ve para politikası, İktisat İşletme ve Finans, 26 (302), 9-25.
  • [2] A.H. Kara, 2012, Küresel kriz sonrası para politikası, İktisat İşletme ve Finans, 27 (315), 9-36.
  • [3] M. Mühleisen, 2010, A New Index of Currency Mismatch and Systemic Risk, IMF Working Paper WP/10/263. file:///C:/Users/asus/Downloads/_wp10263.pdf
  • [4] M.R. King, C. Osler, D. Rime, 2011, Foreign exchange market structure, players and evolution, Norges Bank Working Paper, No:10.Erişim tarihi:07.02.2014. http://www.unich.it/ ~vitale/ Rime-2.pdf.
  • [5] N. Foley-Fisher, R. Ramcharan, E. Yu, 2016, The impact of unconventional monetary policy on firm financing constraints: Evidence from the maturity extension program, Journal of Financial Economics, 122 (2), 409-429.
  • [6] P. Puonti, 2019, Data-driven structural BVAR analysis of unconventional monetary policy, Journal of Macroeconomics, 61, 103-131.
  • [7] L. Wang, 2019, Measuring the effects of unconventional monetary policy on MBS spreads: A comparative study, The North American Journal of Economics and Finance, 49, 235-251.
  • [8] J.C. Wu, J. Zhang, 2019, Global effective lower bound and unconventional monetary policy, Journal of International Economics, 118, 200-216.
  • [9] M. McMahon, M.U. Peiris, H. Polemarchakis, 2018, Perils of unconventional monetary policy, Journal of Economic Dynamics and Control, 93, 92-114.
  • [10] K. D. Sheedy, 2017, Conventional and unconventional monetary policy rules, Journal of Macroeconomics, 54, 127-147.
  • [11] S. Ambler, F. Rumler, 2019, The effectiveness of unconventional monetary policy announcements in the euro area: An event and econometric study, Journal of International Money and Finance, 94, 48- 61.
  • [12] D. Kenourgios, E. Drakonaki, D. Dimitriou, 2019, ECB’s unconventional monetary policy and cross-financial-market correlation dynamics, The North American Journal of Economics and Finance, 50, 1010-45.
  • [13] E. Galariotis, P. Makrichoriti, S. Spyrou, 2018, The impact of conventional and unconventional monetary policy on expectations and sentiment, Journal of Banking & Finance, 86, 1-20.
  • [14] S. Papadamou, Ν. A. Kyriazis, P. G. Tzeremes, 2019, Unconventional monetary policy effects on output and inflation: A meta-analysis, International Review of Financial Analysis, 61, 295-305.
  • [15] C. Lutz, 2015, The impact of conventional and unconventional monetary policy on investor sentiment, Journal of Banking & Finance, 61, 89-105.
  • [16] C. Dreger, J. Wolters, 2015, Unconventional monetary policy and money demand, Journal of Macroeconomics, 46, 40-54.
  • [17] Y. Kiendrebeogo, 2016, Unconventional monetary policy and capital flows, Economic Modelling, 54, 412-424.
  • [18] E. Mamatzakis, T. Bermpei, 2016, What is the effect of unconventional monetary policy on bank performance?, Journal of International Money and Finance, 67, 239-263.
  • [19] L. Wang, 2016, Unconventional monetary policy and aggregate bank lending: Does financial structure matter?, Journal of Policy Modeling, 38 (6), 1060-1077.
  • [20] F. Ferrante, 2019, Risky lending, bank leverage and unconventional monetary policy, Journal of Monetary Economics, 101, 100-127.
  • [21] C. J. Neely, 2015, Unconventional monetary policy had large international effects, Journal of Banking & Finance, 52, 101-111.
  • [22] M. Binici, H. Kara, P. Özlü, 2016, Faiz koridoru ve banka faizleri : Parasal aktarım mekanizmasına dair bazı bulgular, Türkiye Cumhuriyet Merkez Bankası Çalışma Tebliği, No: 16/ 08. http://www.tcmb.gov.tr/wps/wcm/ connect/10f843d3-2e9a-4652-880a-54741d03a396/wp1608.pdf?. ( Erişim Tarihi, Mayıs 2017).
  • [23] H.A. Küçükgöde, 2016, Türkiye Cumhuriyet Merkez Bankası’nın faiz koridoru politikasının etkinliği, İşletme İktisadi Enstitüsü Yönetim Dergisi, 81, 11-25.
  • [24] S. Varlik, H. Berumet, 2017, Multiple policy interest rates and economic performance in a multiple monetary-policy-tool environment, International Review of Economics and Finance, 52, 107-126.
  • [25] Inoue, B. Rossi, 2019, The effects of conventional and unconventional monetary policy on exchange rates, Journal of International Economics, 118, 419–447.
  • [26] J. Rogers, C. Scotti, J.H. Wright, 2014, Evaluating asset-market effects of unconventional monetary policy: amulti-country review, Economic Policy, 29, 3–50.
  • [27] J. Rogers, C. Scotti, J.H. Wright, 2016, Unconventional monetary policy and international risk premia, Board of Governors IFD Papers, No. 1172.
  • [28] R.Glick, S. Leduc, 2015, Unconventional monetary policy and the dollar: Conventional signs, unconventional magnitudes, Federal Reserve Bank of San Francisco W.P (2015–18).
  • [29] P. Anaya, M. Hachula, C. J. Offermanns, 2017, Spillovers of U.S. unconventional monetary policy to emerging markets: The role of capital flows, Journal of International Money and Finance, 73, 275-295.
  • [30] A. Apostolou, J. Beirne, 2019, Volatility spillovers of unconventional monetary policy to emerging market economies, Economic Modelling, 79, 118-129.
  • [31] E. Claus, I. Claus, L. Krippner, 2018, Asset market responses to conventional and unconventional monetary policy shocks in the United States, Journal of Banking & Finance, 97, 270-282.
  • [32] J. Thornton, C. di Tommaso,2018, Unconventional monetary policy and the ‘currency wars’, Finance Research Letters, 26, 250-254.
  • [33] S. Bernhard, T. Ebner, 2017, Cross-border spillover effects of unconventional monetary policies on Swiss asset prices, Journal of International Money and Finance, 75, 109-127.
  • [34] Y.Yalçın, 2007, Stokastik oynaklık modeli ile İstanbul Menkul Kıymetler Borsası’nda kaldıraç etkisinin incelenmesi, Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Dergisi, 22(2), 357- 365.
  • [35] A.Özün, M. Türk, 2008, Döviz kurlarının öngörüsünde stokastik oynaklık modelleri, İktisat İşletme ve Finans, 23 (265), 50-67.
  • [36] V.Abiyev, 2015, Time-varying beta and its modeling techniques for Turkish industry portfolio, İktisat İşletme ve Finans, 30(352), 79-108.
  • [37] Ö.Göktaş, Hepsağ, 2016, BIST100 endeksinin volatil davranışlarının simetrik ve asimetrik stokastik volatilite modelleri ile Analizi, Ekonomik Yaklaşım, 27 (99), 1-15.
  • [38] E.Jacquier, N.G. Polson, P.E. Rossi, 2004, Bayesian analysis of stochastic volatility models with fat-tails and correlated errors, Journal of Econometrics, 122, 185-212.
  • [39] J.J.J. Wang, J.S.K. Chan, S.T.B. Choy, 2011, Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures, Computational Statistics & Data Analysis, 55(1), 852-862.
  • [40] A.Assaf, 2017, The stochastic volatility model , regime switching and Value-at-Risk (VaR) in international equity markets, Journal of Mathematical Finance, 7, 491-512.
  • [41] N.Krichene, 2003, Modeling stochastic volatility with application to stock returns, IMF Working Paper, No:03/125. https://www.imf.org/en/Publications/WP/Issues/2016/12/30 /.
  • [42] H.Küçük, P. Özlü, A. Takaslı, D. Ünalmış, C. Yüksel, 2013, Likidite yönetimi ve BIST faiz farkı, Türkiye Cumhuriyet Merkez Bankası Ekonomi Notları, Sayı: 2013-25/ 23 Ekim 2013.http://www.academia.edu/4870 421/Likidite_Y%C3%B6netimi_ve_BIST_Faiz_Fark%C4%B1. ( Erişim Tarihi, Nisan 2017).
  • [43] Y.Omori, S.Chib, N. Shephard, J. Nakajima, 2007, Stochastic volatility with leverage: Fast and efficient likelihood inferences, Journal of Econometrics, 140, 425-449.
  • [44] F. Selçuk, (2004), Free float and stochastic volatility: The experience of a small open economy, Physica A: Statistical Mechanics and its Applications 342(3-4).
  • [45] D.Hendricks,1996, Evaluation of value at risk modeling using historical data, Economics Policy Review, Federal Reserve Bank of New York.
  • [46] P.Giot, S. Laurent, 2003. Market risk in commodity markets: A VaR approach, Energy Economics, 25, 435–457.
  • [47] J.Nakajima, Y. Omori, 2009, Leverage, heavy-tails and correlated jumps in stochastic volatiliy models, Computational Statistics and Data Analysis, 53, 2335-2353.
  • [48] J.Nakajima, 2008, EGARCH and stochastic volatility: Modeling jumps and heavy-tails for stock returns, IMES Institute for Monetary and Economic Studies, Bank of Japan, No: 2008-E-23. https://www.imes.boj.or.jp/ research/abstracts/english/08-E23.html.
  • [49] J.Nakajima, Y. Omori, 2012, Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution, Computational Statistics and Data Anlysis, 56, 3690-3704.
  • [50] S.Kim, N. Shephard, S. Chib, 1998, Stochastic Volatility: Likelihood inference and comparison with ARCH models, Review of Economic Studies, 65, 361-393.
  • [51] J. Yu, 2005, On leverage in a stochastic volatility model, Journal of Econometrics, 127, 165-178.
  • [52] P.L. Lafosse, G. Rodriguez, 2018, An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns, The Quarterly Review of Economics and Finance, 69, 155-173.
There are 52 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Önder Büberkökü 0000-0002-7140-557X

Publication Date June 30, 2020
Published in Issue Year 2020 Volume: 13 Issue: 1

Cite

IEEE Ö. Büberkökü, “Geleneksel olmayan para politikası uygulamaları döneminde Dolar-TL’nin volatilite dinamiklerinin incelenmesi: Asimetrik stokastik volatilite modeline dayalı analizler”, JSSA, vol. 13, no. 1, pp. 1–17, 2020.