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FORECAST OF CDS PREMIUM WITH ANFIS METHOD: THE CASE OF TURKEY

Yıl 2021, Cilt 17, Sayı 4, 1175 - 1197, 31.12.2021
https://doi.org/10.17130/ijmeb.816813

Öz

CDS premium expresses the risk levels and investability of countries. Investors who can correctly forecast the CDS premium can transfer their funds to reliable countries and correct sources. This study was forecasted by Turkey's CDS premium ANFIS method. Exchange rate, credit rating, interest rate, stock price, stock volatility and stock return were selected as input variables for the study. A daily data set covering the period 2015-2020 was used for the study. As a result of the input selection with the ANFIS method, the most effective input variables in estimating the CDS premium are; exchange rate, stock price and interest rate. After training the model, in order to test the consistency of the ANFIS model, CDS estimation was made with the test data set shown to the model for the first time, and it was observed that the ANFIS model CDS predictive values were very close to the actual CDS values. Finally, ANFIS prediction model and multiple linear regression analysis results were compared to evaluate the predictive performance of ANFIS model. It is concluded that the ANFIS prediction model has a better prediction performance.

Kaynakça

  • Abid, F., & Naifar, N. (2006). The determinants of credit default swap rates: An explanatory study. International Journal of Theoretical and Applied Finance, 9(1), 23–42. https://doi.org/10.1142/S0219024906003445
  • Afonso, A., Furceri, D., & Gomes, P. (2012). Sovereign credit ratings and financial markets linkages: Application to European data. Journal of International Money and Finance, 31(3), 606–638. https://doi.org/10.1016/j.jimonfin.2012.01.016
  • Alexander, C., & Kaeck, A. (2008). Regime dependent determinants of credit default swap spreads. Journal of Banking & Finance, 32, 1008–1021. https://doi.org/10.1016/j.jbankfin.2007.08.002
  • Amato, J. (2005). Risk Aversion and Risk Premia in the CDS Market. BIS Quarterly Review, 55–68. Retrieved from http://scholar.google.com/scholarhl=en&btnG=Search&q=intitle:Risk+aversion+and+risk+premia+in+the+CDS+market1#0%5Cnhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=1645856
  • Anton, S. G. (2011). The local determinants of emerging market sovereign CDS spreads in the context of the debt crisis. An explanatory study. Analele Ştiinţifice Ale Universităţii »Alexandru Ioan Cuza« din Iaşi. Ştiinţe Economice, 58(1), 41–52.
  • Aunon-Nerin, D., Cossin, D., Hricko, T., & Huang, Z. (2005). Exploring for the Determinants of Credit Risk in Credit Default Swap Transaction Data: Is Fixed-Income Markets’ Information Sufficient to Evaluate Credit Risk? SSRN Electronic Journal, (October), 1–66. https://doi.org/10.2139/ssrn.375563
  • Avino, D., & Nneji, O. (2014). Are CDS spreads predictable? An analysis of linear and non-linear forecasting models. International Review of Financial Analysis, 34, 262–274. https://doi.org/10.1016/j.irfa.2014.04.001
  • Bayramoğlu, T., Pabuççu, H., & Çelebi Boz, F. (2017). Türkiye İçin Anfıs Modeli İle Birincil Enerji Talep Tahmini. Ege Akademik Bakis, 17(3), 431–446. https://doi.org/10.21121/eab.2017328408
  • Benkert, C. (2004). EXPLAINING CREDIT DEFAULT SWAP PREMIA. The Journal of Futures Markets, 24(1), 71–92. https://doi.org/10.1002/fut.10112
  • Boyacioglu, M. A., & Avci, D. (2010). An adaptive network-based fuzzy inference system (ANFIS) for the prediction of stock market return: The case of the Istanbul stock exchange. Expert Systems with Applications, 37(12), 7908–7912. https://doi.org/10.1016/j.eswa.2010.04.045
  • Byström, H. (2005). CREDIT DEFAULT SWAPS AND EQUITY PRICES: THE iTRAXX CDS INDEX MARKET. Chan, K. C., Fung, H. G., & Zgang, G. (2009). On the Relationship Between Asian Credit Default Swap and Equity Markets. Journal of Asia Business Studies, 3–11.
  • Di Cesare, A., & Guazzarotti, G. (2010). An analysis of the determinants of credit default swap spread changes before and during the subprime financial turmoil.
  • Doğan, O. (2016). Uyarlamalı Sinirsel Bulanık Çıkarım Sisteminin (ANFIS) Talep Tahmini İçin Kullanımı ve Bir Uygulama. Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 31(1), 257–288.
  • Dutra, T. M. (2015). Credit Default Swap (CDS) Prediction Model & Trading Strategy.
  • Ericsson, J., Jacobs, K., & Oviedo, R. (2009). The Determinants of Credit Default Swap Premia. The Journal of Financial and Quantitative Analysis, 44(1), 109–132. https://doi.org/: 1 0. 1 0 1 7/S0022 1 0900909006 1
  • Eyssell, T., Fung, H. G., & Zhang, G. (2013). Determinants and price discovery of China sovereign credit default swaps. China Economic Review, 24(1), 1–15. https://doi.org/10.1016/j.chieco.2012.09.003
  • Fonseca, J. Da, & Gottschalk, K. (2012). The Co-movement of Credit Default Swap Spreads, Stock Market Returns and Volatilities: Evidence from Asia-Pacific Markets ∗.
  • Gazel, S., & Kesebir, M. (2019). DÖVİZ KURUNUN VE KREDİ TEMERRÜT TAKASININ BANKACILIK ENDEKSİ ÜZERİNE ETKİSİ: BORSA İSTANBUL ÜZERİNE BİR UYGULAMA. In İKTİSADİ VE MALİ GÜNCEL SORUNLARIYLA ANALİZ (pp. 55–80).
  • Gökgöz, I. H., Uǧur, Ö., & Yolcu Okur, Y. (2014). On the single name CDS price under structural modeling. Journal of Computational and Applied Mathematics, 259(PART B), 406–412. https://doi.org/10.1016/j.cam.2013.07.052
  • Hassan, M. K., Ngow, T. S., Yu, J. S., & Hassan, A. (2013). Determinants of credit default swaps spreads in European and Asian markets. Journal of Derivatives and Hedge Funds, 19(4), 295–310. https://doi.org/10.1057/jdhf.2014.1
  • İldokuz, B., & Yıldırım, H. H. (2019). Korumasız Faiz Parite Kuramı ve 2005-2014 Dönemi Portföy Yatırımlarını Türkiye’ye Çeken Finansal Faktörlerin Tespiti. Ekonometri ve İstatistik E-Dergisi, 14(29), 1–22. https://doi.org/10.26650/ekoist.2018.14.29.0003
  • Jang, J. R. (1993). ANFIS : Adaptive-Network-Based Fuzzy Inference System. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, 23(3), 665–685.
  • Kargi, B. (2014). Credit Default Swap (CDS) Spreads: The Analysis of Time Series for The Integration with The Interest Rates and The Growth in Turkish Economy. Montenegrin Journal of Economics, 10(1), 59–66.
  • Kim, W. J., Jung, G., & Choi, S. (2020). Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning. Complexity, 23.
  • Koy, A., & Karaca, S. S. (2018). Daralma ve Genişleme Dönemlerinde Uluslararası Portföy Yatırımları Nasıl Etkileniyor? Marmara Üniversitesi Öneri Dergisi, 13(50), 90–105.
  • Kunt, A. S., & Taş, O. (2008). Kredi temerrüt swapları ve Türkiye’nin CDS priminin tahmin edilmesine yönelik bir uygulama. Itüdergisi/b Sosyal Bilimler, 5(1), 78–89.
  • Liu, Y., & Morley, B. (2013). Sovereign Credit Ratings, the Macroeconomy and Credit Default Swap Spreads. Brussels Economic Review, 56(3/4), 335–349.
  • Norden, L., & Weber, M. (2004). Informational efficiency of credit default swap and stock markets: The impact of credit rating announcements. Journal of Banking & Finance, 28, 2813–2843. https://doi.org/10.1016/j.jbankfin.2004.06.011
  • Oner Kaya, E., Kaya, B., & Yalciner, K. (2015). REACTION OF CREDIT DEFAULT SWAP SPREADS TO RATING ANNOUNCEMENTS: AN EVENT STUDY FOR TURKEY. Journal of Economics, Finance and Accounting, 2(4), 558–571. https://doi.org/10.17261/Pressacademia.2015414368
  • Pappa, S., & Melin, J. (2015). Evaluating Credit Default Swap spreads using the CreditGrades model. Srivastava, S., Lin, H., Premachandra, I. M., & Roberts, H. (2016). Global risk spillover and the predictability of sovereign CDS spread: International evidence. International Review of Economics and Finance, 41, 371–390. https://doi.org/10.1016/j.iref.2015.10.047
  • Tolikas, K., & Topaloglou, N. (2017). Is default risk priced equally fast in the credit default swap and the stock markets? AN empirical investigation. Journal of International Financial Markets, Institutions & Money, 51, 39–57. https://doi.org/10.1016/j.intfin.2017.09.029
  • Toolbox, F. L. (2005). Fuzzy Logic Toolbox For use with Matlab, users guide, Version 2.
  • Yücel, A. (2010). TEDARİKÇİ SEÇİMİ PROBLEMİNDE BÜTÜNLEŞİK SİNİRSEL BULANIK MANTIK YAKLAŞIMI (Doktora Tezi). Yıldız Teknik Üniversitesi, Sosyal Bilimler Enstitüsü

ANFIS METODU İLE CDS PRİMİ TAHMİNLEMESİ: TÜRKİYE ÖRNEĞİ

Yıl 2021, Cilt 17, Sayı 4, 1175 - 1197, 31.12.2021
https://doi.org/10.17130/ijmeb.816813

Öz

CDS primi ülkelerin risk derecelerini ve yatırım yapılabilirliklerini ifade etmektedir. CDS primini doğru tahmin edebilen yatırımcılar fonlarını güvenilir ülkelere ve doğru kaynaklara aktarabilmektedirler. Bu çalışmada Türkiye’nin CDS primi ANFIS metodu ile tahmin edilmiştir. Çalışmanın girdi değişkenleri olarak döviz kuru, kredi notu, faiz oranı, hisse senedi fiyatı, hisse senedi volatilitesi ve hisse senedi getirisi seçilmiştir. Çalışma için 2015-2020 dönemini kapsayan günlük bir veri seti kullanılmıştır. ANFIS metodu ile girdi seçimi neticesinde CDS priminin tahmin edilmesinde en etkili girdi değişkenlerin; döviz kuru, hisse senedi fiyatı ve faiz oranı oldukları tespit edilmiştir. Model eğitildikten sonra, ANFIS modelinin tutarlılığının sınanması için modele ilk defa gösterilen test veri seti ile CDS tahminlemesi yapılmış ve ANFIS modeli CDS tahmin değerlerinin gerçek CDS değerlerine oldukça yakın olduğu görülmüştür. Son olarak, ANFIS modelinin tahmin performansının değerlendirilmesi için ANFIS tahmin modeli ve çoklu doğrusal regresyon analizi sonuçları karşılaştırılmıştır. ANFIS tahmin modelinin daha iyi bir tahmin performansına sahip olduğu sonucunda ulaşılmıştır.

Kaynakça

  • Abid, F., & Naifar, N. (2006). The determinants of credit default swap rates: An explanatory study. International Journal of Theoretical and Applied Finance, 9(1), 23–42. https://doi.org/10.1142/S0219024906003445
  • Afonso, A., Furceri, D., & Gomes, P. (2012). Sovereign credit ratings and financial markets linkages: Application to European data. Journal of International Money and Finance, 31(3), 606–638. https://doi.org/10.1016/j.jimonfin.2012.01.016
  • Alexander, C., & Kaeck, A. (2008). Regime dependent determinants of credit default swap spreads. Journal of Banking & Finance, 32, 1008–1021. https://doi.org/10.1016/j.jbankfin.2007.08.002
  • Amato, J. (2005). Risk Aversion and Risk Premia in the CDS Market. BIS Quarterly Review, 55–68. Retrieved from http://scholar.google.com/scholarhl=en&btnG=Search&q=intitle:Risk+aversion+and+risk+premia+in+the+CDS+market1#0%5Cnhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=1645856
  • Anton, S. G. (2011). The local determinants of emerging market sovereign CDS spreads in the context of the debt crisis. An explanatory study. Analele Ştiinţifice Ale Universităţii »Alexandru Ioan Cuza« din Iaşi. Ştiinţe Economice, 58(1), 41–52.
  • Aunon-Nerin, D., Cossin, D., Hricko, T., & Huang, Z. (2005). Exploring for the Determinants of Credit Risk in Credit Default Swap Transaction Data: Is Fixed-Income Markets’ Information Sufficient to Evaluate Credit Risk? SSRN Electronic Journal, (October), 1–66. https://doi.org/10.2139/ssrn.375563
  • Avino, D., & Nneji, O. (2014). Are CDS spreads predictable? An analysis of linear and non-linear forecasting models. International Review of Financial Analysis, 34, 262–274. https://doi.org/10.1016/j.irfa.2014.04.001
  • Bayramoğlu, T., Pabuççu, H., & Çelebi Boz, F. (2017). Türkiye İçin Anfıs Modeli İle Birincil Enerji Talep Tahmini. Ege Akademik Bakis, 17(3), 431–446. https://doi.org/10.21121/eab.2017328408
  • Benkert, C. (2004). EXPLAINING CREDIT DEFAULT SWAP PREMIA. The Journal of Futures Markets, 24(1), 71–92. https://doi.org/10.1002/fut.10112
  • Boyacioglu, M. A., & Avci, D. (2010). An adaptive network-based fuzzy inference system (ANFIS) for the prediction of stock market return: The case of the Istanbul stock exchange. Expert Systems with Applications, 37(12), 7908–7912. https://doi.org/10.1016/j.eswa.2010.04.045
  • Byström, H. (2005). CREDIT DEFAULT SWAPS AND EQUITY PRICES: THE iTRAXX CDS INDEX MARKET. Chan, K. C., Fung, H. G., & Zgang, G. (2009). On the Relationship Between Asian Credit Default Swap and Equity Markets. Journal of Asia Business Studies, 3–11.
  • Di Cesare, A., & Guazzarotti, G. (2010). An analysis of the determinants of credit default swap spread changes before and during the subprime financial turmoil.
  • Doğan, O. (2016). Uyarlamalı Sinirsel Bulanık Çıkarım Sisteminin (ANFIS) Talep Tahmini İçin Kullanımı ve Bir Uygulama. Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 31(1), 257–288.
  • Dutra, T. M. (2015). Credit Default Swap (CDS) Prediction Model & Trading Strategy.
  • Ericsson, J., Jacobs, K., & Oviedo, R. (2009). The Determinants of Credit Default Swap Premia. The Journal of Financial and Quantitative Analysis, 44(1), 109–132. https://doi.org/: 1 0. 1 0 1 7/S0022 1 0900909006 1
  • Eyssell, T., Fung, H. G., & Zhang, G. (2013). Determinants and price discovery of China sovereign credit default swaps. China Economic Review, 24(1), 1–15. https://doi.org/10.1016/j.chieco.2012.09.003
  • Fonseca, J. Da, & Gottschalk, K. (2012). The Co-movement of Credit Default Swap Spreads, Stock Market Returns and Volatilities: Evidence from Asia-Pacific Markets ∗.
  • Gazel, S., & Kesebir, M. (2019). DÖVİZ KURUNUN VE KREDİ TEMERRÜT TAKASININ BANKACILIK ENDEKSİ ÜZERİNE ETKİSİ: BORSA İSTANBUL ÜZERİNE BİR UYGULAMA. In İKTİSADİ VE MALİ GÜNCEL SORUNLARIYLA ANALİZ (pp. 55–80).
  • Gökgöz, I. H., Uǧur, Ö., & Yolcu Okur, Y. (2014). On the single name CDS price under structural modeling. Journal of Computational and Applied Mathematics, 259(PART B), 406–412. https://doi.org/10.1016/j.cam.2013.07.052
  • Hassan, M. K., Ngow, T. S., Yu, J. S., & Hassan, A. (2013). Determinants of credit default swaps spreads in European and Asian markets. Journal of Derivatives and Hedge Funds, 19(4), 295–310. https://doi.org/10.1057/jdhf.2014.1
  • İldokuz, B., & Yıldırım, H. H. (2019). Korumasız Faiz Parite Kuramı ve 2005-2014 Dönemi Portföy Yatırımlarını Türkiye’ye Çeken Finansal Faktörlerin Tespiti. Ekonometri ve İstatistik E-Dergisi, 14(29), 1–22. https://doi.org/10.26650/ekoist.2018.14.29.0003
  • Jang, J. R. (1993). ANFIS : Adaptive-Network-Based Fuzzy Inference System. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, 23(3), 665–685.
  • Kargi, B. (2014). Credit Default Swap (CDS) Spreads: The Analysis of Time Series for The Integration with The Interest Rates and The Growth in Turkish Economy. Montenegrin Journal of Economics, 10(1), 59–66.
  • Kim, W. J., Jung, G., & Choi, S. (2020). Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning. Complexity, 23.
  • Koy, A., & Karaca, S. S. (2018). Daralma ve Genişleme Dönemlerinde Uluslararası Portföy Yatırımları Nasıl Etkileniyor? Marmara Üniversitesi Öneri Dergisi, 13(50), 90–105.
  • Kunt, A. S., & Taş, O. (2008). Kredi temerrüt swapları ve Türkiye’nin CDS priminin tahmin edilmesine yönelik bir uygulama. Itüdergisi/b Sosyal Bilimler, 5(1), 78–89.
  • Liu, Y., & Morley, B. (2013). Sovereign Credit Ratings, the Macroeconomy and Credit Default Swap Spreads. Brussels Economic Review, 56(3/4), 335–349.
  • Norden, L., & Weber, M. (2004). Informational efficiency of credit default swap and stock markets: The impact of credit rating announcements. Journal of Banking & Finance, 28, 2813–2843. https://doi.org/10.1016/j.jbankfin.2004.06.011
  • Oner Kaya, E., Kaya, B., & Yalciner, K. (2015). REACTION OF CREDIT DEFAULT SWAP SPREADS TO RATING ANNOUNCEMENTS: AN EVENT STUDY FOR TURKEY. Journal of Economics, Finance and Accounting, 2(4), 558–571. https://doi.org/10.17261/Pressacademia.2015414368
  • Pappa, S., & Melin, J. (2015). Evaluating Credit Default Swap spreads using the CreditGrades model. Srivastava, S., Lin, H., Premachandra, I. M., & Roberts, H. (2016). Global risk spillover and the predictability of sovereign CDS spread: International evidence. International Review of Economics and Finance, 41, 371–390. https://doi.org/10.1016/j.iref.2015.10.047
  • Tolikas, K., & Topaloglou, N. (2017). Is default risk priced equally fast in the credit default swap and the stock markets? AN empirical investigation. Journal of International Financial Markets, Institutions & Money, 51, 39–57. https://doi.org/10.1016/j.intfin.2017.09.029
  • Toolbox, F. L. (2005). Fuzzy Logic Toolbox For use with Matlab, users guide, Version 2.
  • Yücel, A. (2010). TEDARİKÇİ SEÇİMİ PROBLEMİNDE BÜTÜNLEŞİK SİNİRSEL BULANIK MANTIK YAKLAŞIMI (Doktora Tezi). Yıldız Teknik Üniversitesi, Sosyal Bilimler Enstitüsü

Ayrıntılar

Birincil Dil Türkçe
Konular İşletme Finans
Bölüm Araştırma Makaleleri
Yazarlar

Busra KUTLU KARABIYIK (Sorumlu Yazar)
AYDIN ADNAN MENDERES ÜNİVERSİTESİ
0000-0002-6691-2921
Türkiye

Yayımlanma Tarihi 31 Aralık 2021
Başvuru Tarihi 27 Ekim 2020
Kabul Tarihi 27 Mayıs 2021
Yayınlandığı Sayı Yıl 2021, Cilt 17, Sayı 4

Kaynak Göster

APA Kutlu Karabıyık, B. (2021). ANFIS METODU İLE CDS PRİMİ TAHMİNLEMESİ: TÜRKİYE ÖRNEĞİ . Uluslararası Yönetim İktisat ve İşletme Dergisi , 17 (4) , 1175-1197 . DOI: 10.17130/ijmeb.816813