BibTex RIS Kaynak Göster

TÜRKİYE HİSSE SENEDİ PİYASASI OYNAKLIĞINDAKİ ASİMETRİK UZUN HAFIZA ÖZELLİĞİ

Yıl 2014, Cilt: 1 Sayı: 1, 1 - 10, 03.01.2014

Öz

Bu çalışmada, Türkiye hisse senedi piyasası oynaklığındaki asimetrik uzun hafıza özelliği incelenmektedir. Bu amaçla,
finans literatüründe FIEGARCH modeli ile asimetri özelliğini de değerlendiren uzun hafıza oynaklık modeli
uygulamalarına katkıda bulunmaktadır. İlk olarak, Türkiye hisse senedi piyasası oynaklığındaki simetrik uzun hafıza
dinamiklerini tanımlamak için FIGARCH modeli tahmin edilmektedir. İkinci olarak oynaklığın iyi-kötü haberlere
asimetrik cevabı EGARCH modeli ile incelenmektedir. Son olarak, uzun hafıza süreçli asimetrik oynaklığın varlığı
FIEGARCH modeli ile değerlendirilmektedir. Çalışma yatırımcılar ve piyasa katılımcıları için önemli bulgular
sağlamaktadır. Sonuçlar Türkiye hisse senedi piyasa oynaklığında şokların asimetrik etkisinin varlığını ve uzun dönem
kalıcılığını göstermektedir.

Kaynakça

  • (1) Engle, R.F. 1982. Autoregressive Conditional Heteroscedasticity with Estimates of Variance of United Kingdom Inflation, Econometrica. (50):987-1008.
  • (2) Bollerslev, T. 1986. Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics. (31):307-327.
  • (3) Nelson, D.B. 1991. Conditional Heteroskedas- ticity in asset returns: A new approach, Econometrica (59): 347-370.
  • (4) Engle, R.F. and Ng, V.K., 1993. Measuring and testing the impact of news on volatility. Journal of Finance. (48):1749-1777.
  • (5) Glosten, L.R., R. Jagannathan and Runkle D. 1993. On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks, Journal of Finance. (48):1779-1801.
  • (6) Zakoian, J.M. 1994. Threshold Heteroskedastic Models, Journal of Economic Dynamics and Control. (18):931-955.
  • (7) Granger, C.W.J. and R. Joyeux. 1980. An introduction to long-memory time series models and fractional differencing, Journal of Time Series Analysis. (1):15-39.
  • (8) Bollerslev, T. and Mikkelsen H.O. 1996. Modeling and Pricing Long-Memory in Stock
  • Market Volatility, Journal of Econometrics. (73), 1:151-184.
  • (9) Tse, Y. 1998. The Conditional Heteroskedasticity of the Yen-dollar Exchange Rate, Journal of Applied Econometrics. (193):49-55.
  • (10) Wright, J. 2002. Log-Periodogram Estimation Of Long Memory Volatility Dependencies With Conditionally Heavy Tailed Returns, Econometric Reviews, Taylor and Francis Journals. 21(4):397-417.
  • (11) Degiannakis, S. 2004. Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model, Appl. Financ. Econ. (14):1333–1342.
  • (12) Kilic, R. 2004. On the long memory properties of emerging capital markets: evidence from Istanbul stock exchange, Applied Financial Economics. (14): 915-922.
  • (13) Akgün, I. ve Sayyan, H. 2005. Forecasting Volatility in ISE-30 Stock Returns with Asymmetric Conditional Heteroscedasticity Models, Symposium of Traditional Finance, Marmara Üniversitesi, Bankacılık ve Sigortacılık Yüksekokulu, İstanbul, Türkiye, 127-141.
  • (14) Cavalcante, J. and Assaf, A. 2005. Long range dependence in the returns and volatility of the Brazilian stock market, European Review of Economics and Finance. (5):5–20.
  • (15) Bellalah, M., Aloui, C., and Abaoub, E. 2005. Long-range Dependence in Daily Volatility on Tunisian stock market. International Journal of Business. 10(3):191-216.
  • (16) Assaf, A. 2007. Dependence and mean reversion in stock prices: The case of the MENA region, Research in International Business and Finance. (20): 286–304.
  • (17) Kang, H.S. and Yoon, SM. 2007. Long memory properties in return and volatility: Evidence from the Korean stock market, Physica A. (385):591-600.
  • (18) Banerjee, A., and Sarkar, S. (2006). Modeling daily volatility of the Indian stock market using intra-day data. Working paper WPSNO.588. Indian Institute of Management.
  • (19) Goudarzi, H. 2010. Modeling Long term memory in the Indian Stock Market using Fractionally Integrated EGARCH model. International Journal of Trade, Economics and Finance, 1(3), 231-237.
  • (20) Demireli, E. 2010. Value at Risk (VAR) analysis and Long Memory: Evidence from FIAPARCH in Istanbul Stock Exchange, Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 24, (4):217-228.
  • (21) Laurent, S., and J.P. Peters, 2001. G@RCH 2.0 :An Ox Package for Estimating and Forecasting Various ARCH Models, Proceedings 8th Forecasting Financial Markets. London, May 2001.
  • (22) Baillie, R.T., T.Bollerslev, and H.O. Mikkelsen. 1996. Fractionally integrated generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 74, (3):3–30.
  • (23) Bollerslev, T. and H.O.A. Mikkelsen. 1996. Modeling and Pricing Long-Memory in Stock Market Volatility. Journal of Econometrics 73:151-184.
Yıl 2014, Cilt: 1 Sayı: 1, 1 - 10, 03.01.2014

Öz

Kaynakça

  • (1) Engle, R.F. 1982. Autoregressive Conditional Heteroscedasticity with Estimates of Variance of United Kingdom Inflation, Econometrica. (50):987-1008.
  • (2) Bollerslev, T. 1986. Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics. (31):307-327.
  • (3) Nelson, D.B. 1991. Conditional Heteroskedas- ticity in asset returns: A new approach, Econometrica (59): 347-370.
  • (4) Engle, R.F. and Ng, V.K., 1993. Measuring and testing the impact of news on volatility. Journal of Finance. (48):1749-1777.
  • (5) Glosten, L.R., R. Jagannathan and Runkle D. 1993. On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks, Journal of Finance. (48):1779-1801.
  • (6) Zakoian, J.M. 1994. Threshold Heteroskedastic Models, Journal of Economic Dynamics and Control. (18):931-955.
  • (7) Granger, C.W.J. and R. Joyeux. 1980. An introduction to long-memory time series models and fractional differencing, Journal of Time Series Analysis. (1):15-39.
  • (8) Bollerslev, T. and Mikkelsen H.O. 1996. Modeling and Pricing Long-Memory in Stock
  • Market Volatility, Journal of Econometrics. (73), 1:151-184.
  • (9) Tse, Y. 1998. The Conditional Heteroskedasticity of the Yen-dollar Exchange Rate, Journal of Applied Econometrics. (193):49-55.
  • (10) Wright, J. 2002. Log-Periodogram Estimation Of Long Memory Volatility Dependencies With Conditionally Heavy Tailed Returns, Econometric Reviews, Taylor and Francis Journals. 21(4):397-417.
  • (11) Degiannakis, S. 2004. Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model, Appl. Financ. Econ. (14):1333–1342.
  • (12) Kilic, R. 2004. On the long memory properties of emerging capital markets: evidence from Istanbul stock exchange, Applied Financial Economics. (14): 915-922.
  • (13) Akgün, I. ve Sayyan, H. 2005. Forecasting Volatility in ISE-30 Stock Returns with Asymmetric Conditional Heteroscedasticity Models, Symposium of Traditional Finance, Marmara Üniversitesi, Bankacılık ve Sigortacılık Yüksekokulu, İstanbul, Türkiye, 127-141.
  • (14) Cavalcante, J. and Assaf, A. 2005. Long range dependence in the returns and volatility of the Brazilian stock market, European Review of Economics and Finance. (5):5–20.
  • (15) Bellalah, M., Aloui, C., and Abaoub, E. 2005. Long-range Dependence in Daily Volatility on Tunisian stock market. International Journal of Business. 10(3):191-216.
  • (16) Assaf, A. 2007. Dependence and mean reversion in stock prices: The case of the MENA region, Research in International Business and Finance. (20): 286–304.
  • (17) Kang, H.S. and Yoon, SM. 2007. Long memory properties in return and volatility: Evidence from the Korean stock market, Physica A. (385):591-600.
  • (18) Banerjee, A., and Sarkar, S. (2006). Modeling daily volatility of the Indian stock market using intra-day data. Working paper WPSNO.588. Indian Institute of Management.
  • (19) Goudarzi, H. 2010. Modeling Long term memory in the Indian Stock Market using Fractionally Integrated EGARCH model. International Journal of Trade, Economics and Finance, 1(3), 231-237.
  • (20) Demireli, E. 2010. Value at Risk (VAR) analysis and Long Memory: Evidence from FIAPARCH in Istanbul Stock Exchange, Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 24, (4):217-228.
  • (21) Laurent, S., and J.P. Peters, 2001. G@RCH 2.0 :An Ox Package for Estimating and Forecasting Various ARCH Models, Proceedings 8th Forecasting Financial Markets. London, May 2001.
  • (22) Baillie, R.T., T.Bollerslev, and H.O. Mikkelsen. 1996. Fractionally integrated generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 74, (3):3–30.
  • (23) Bollerslev, T. and H.O.A. Mikkelsen. 1996. Modeling and Pricing Long-Memory in Stock Market Volatility. Journal of Econometrics 73:151-184.
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Serpil Türkyılmaz

Mesut Balıbey Bu kişi benim

Yayımlanma Tarihi 3 Ocak 2014
Yayımlandığı Sayı Yıl 2014 Cilt: 1 Sayı: 1

Kaynak Göster

APA Türkyılmaz, S., & Balıbey, M. (2014). TÜRKİYE HİSSE SENEDİ PİYASASI OYNAKLIĞINDAKİ ASİMETRİK UZUN HAFIZA ÖZELLİĞİ. Journal of Banking and Financial Research, 1(1), 1-10.