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İSTANBUL MENKUL KIYMETLER BORSASI 100 ENDEKSİNİN DOĞRUSALLIK TESTİ

Journal Name:

  • İstanbul Üniversitesi Ekonometri ve İstatistik Dergisi

Publication Year:

  • 2006

Key Words:

Keywords (Original Language):

Author NameUniversity of Author
Abstract (2. Language): 
The aim of the study is nonlinearity test of ISE – 100 returns. The most usedly nonlinearity test of BDS test is applied. Data is obtained from the Central Bank of Turkey. Return data is calculated by the difference of natural logarthim of daily closing value. The data has 4352 observations, between the data of 02.01.1989 and 04.07.2006. BDS test is done on the four different error term. Before the ARMA process to make the BDS test days are used as a dummies and error term is obtained by regression. Second data set is ARMA process is done and error term is obtained and then BDS test is applied. Third data set is logarithm of the squared standardized residuals of GARCH (1,1) process. Fourth data set is logarithm of the squared standardized residuals of AR (1) - GARCH (1,1) process. First, second and fourth data sets reject the null hypothesis that means there exist a nonlinear relation. Third data set fail to reject the null hypothesis of iid, for some embedding dimension, that means GARCH (1,1) process removes most of the nonlinearity.
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Abstract (Original Language): 
Bu çalışmanın amacı İMKB-100 endeksi getirisinin doğrusal bir yapıya sahip olup olmadığını göstermektir. Çalışmada doğrusallık testlerinden en fazla kullanılan BDS testinden faydalanılacaktır. Kullanılan veri seti Merkez Bankasından elde edilmiştir. Getiri serisi endeksin günlük kapanış değerlerinin logaritmik farkı alınarak hesaplanmıştır. Çalışmada kullanılan veri seti 02.01.1989 – 04.07.2006 yılları arasında olup 4352 gözlemden oluşmaktadır. Çalışmada veri seti dört şekilde değerlendirilmiştir: ilk değerlendirme veri setine günler kukla değişken olarak kullanıldıktan sonra ARMA süreci uygulanmıştır hata terimlerine BDS testi uygulanmıştır. İkinci veri seti ise getiri serisine ARMA süreci uygulanarak hata terimleri elde edildikten sonra BDS testi uygulanmıştır. Üçüncü veri setinde GARCH(1,1) süreci ve dördüncü veri setinde ise AR(1) – GARCH(1,1) ile standartlaştırılmış hata karelerinin logaritmalarına BDS testi uygulanmıştır. Birinci, ikinci ve dördüncü veri setinde BDS testi sonuçlarına göre getirilerin doğrusal olmayan bir yapıya sahip olduğu bulunmuştur. Üçüncü veri seti incelendiğinde ise BDS testi bazı boyutlarda hata terimlerinin bağımsız benzer dağılıma sahip olduğunu göstermiştir.
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  • 3
23-31
  • Turkish

REFERENCES

References: 

Abhyankar A.,Copeland L.S, Wong W. (1995) “Nonlinear dynamics in real time equity market indeces:
evidence from the United Kingdom”, Royal Economic Society, 105 (July), 864-880
Abhyankar A., Copeland L.S, Wong W. (1997) “Uncovering nonlinear structure in real time stock market
indexes: The S&P 500, the DAX, the Nikkei 225, and the FTSE-100”, Journal of business and Econnomic
Statistic, January1997, vol15 no:1, 1-14
Barnett W.A., Gallant R., Hinich M.J., Jungeilges J.A., Kaplan D., Jensen M. (1997) “A single blind
controlled competition among tests for nonlinearity and chaos”, Journal of Econometrics 82, 157-192
Bollerslev T. (1986) “Generalised Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics, 31,
307-327.
Brock W.A., Hsieh D. A., LeBaron B. (1993) “Nonlinear Dynamics, Chaos, and Instability: Statistical Theory
and Economic Evidence” MIT Press, London.

Brock W.A., Dechert D, Lebaron B., and Scheinkman J. (1996) “A test for independence based on a correlation
dimension”, Econometric Review 15, 197-235
Brooks C., (1997) “Linear and non-linear (Non-) Forecastability of High-frequency Exchange Rates” Journal of
Forecasting, 16, 125-145.
Brooks C., Heravi S.M. (1999) “The Effect of (Mis-Specified) GARCH Filters on the Finite Sample Distribution
of the BDS Test”, Computational Economics, 13, 147-162.
Brooks C. (1999) “Portmanteau Model Diagnostics and Tests for Nonlinearity: A Comparative Monte Carlo
Stıdy of Two Alternative Methods”, Computational Economics, 13, 3, 249-263.
Brooks C., Henry O.T., (2000) “Can Portmanteau Nonlinearity Test Serve as General Mis-Specification Test?
Evidence From Symmetric and Asymmetric GARCH Models”, Economics Letters, 67, 245-251.
Campbell Y.J., Lo A.W., MacKinlay A.C. (1997) The Econometric of Financial Markets, Princeton University
Press
Caporale G.M., Ntantamis C., Pantelidis T., Pittis N., (2005) “The BDS Test as a Test for the Adequacy of a
GARCH (1,1) Specification: A Monte Carlo Study”, Journal of Financial Econometrics, 3, 2, 282-309
Dickey D.A. and Fuller W.A. (1979) “Distribution of the Estimators for Autoregressive Time Series with a Unit
Root,” Journal of the American Statistical Association, 74, 427–431
Fama E. (1970) “Efficient capital markets: A review of theory and empirical works”, Journal of Finance 25, 34-105
Fernandes M. (1998) “Non-Linearity and Exchange Rates”, Journal of Forecasting, 17, 497-514.
Frank M., Stengos T. (1989) “Measuring the stangeness of gold and silver rates of return”, Rewiev of Economic
Studies, 56, 553-567
Grasberger P., Proccia I. (1983) “Measuring the strangeness of strange attractors”, Physica 9D 189
Hsieh D.A. (1989) “Testing for nonlinear dependence in daily foreign exchange rates”, Journal of Business vol
62 no:3 339-369
Hsieh D.A. (1993) “Implication of nonlinear dynamics for financial risk management”, Journal of Financial and
Quantitative Analysis, vol 28 no:1, 41-64
Jarque C. and Bera A. (1980) “Efficient Tests for Normality, Homoskedasticity, and Serial Independence of
Regression Residuals”, Economics Letters, 6, 255–259.
Kaplan D. (1994) “Exceptional events as evidence for determinism”, Physica D, 73,38-48
Kondak N. E. (1997) “The Efficiency Market Hypothesis Revisited: Some Evidence From The Istanbul Stock
Exchange”, Sermaye Piyasası Yayınları, Ankara.
Kosfeld R., Robe S., (2001) “Testing the Nonlinearities in German Bank Stock Returns”, Empirical Economics,
26, 581-597.
Lima P. J.F (1997) “On the Robustness of Nonlinearity tests to Moment Condition Failure”, Journal of
Ecnometrics, 76, 251-280.
Özer H. (2001) “The Distributional Properties and Weak Efficiency In Istanbul Stock Exchange: A Sectoral
Analysis”, Basılmamış İktisat Tezi, Bilkent Üniversitesi.
Phillips P.C.B. and Perron P. (1988) “Testing for a Unit Root in Time Series Regression,” Biometrika, 75, 335–
346
Scheinkman J.A, LeBaron B. (1989) “Nonlinear dynamics and stock returns”, Journal of Business vol 62, no:3,
311-337
Taylor S.J., (1986) “Forecasting Volatility of Currency Exchange Rates”, International Journal of Forecasting, 3,
159-170.
Urruia J.L., Vu J., Gronewoller P., Hoque M. (2002) “Nonlinearity and Low Deterministic Chaotic Behavior in
Insurance Portfolio Stock Returns”, The Journal of Risk and Insurance, 69,4, 537-554.

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