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Journals / İ M K B Dergisi / 2007 / Cilt: 9 - Sayı: 36

Asymmetric Responses in Volatility Between Positive and Negative Shocks: New Evidence from Turkish Data by Using TAR-GARCH Model

Volatilitenin Negatif ve Pozitif Şoklara Asimetrik Tepkisi: TAR-GARCH Modeli Kullanılarak Türkiye Verilerinden Yeni Bir Kanıt

Cüneyt AKAR
Pages
75–82
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results show that stock return volatility reacts asymmetrically to past information at a lag of one time period in the Turkish stock market.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this study is to investigate the asymmetric responses in volatility between positive and negative shocks in Turkish stock market.
📊
Key Findings & Data:The daily closing values of Istanbul Stock Exchange 100 Index (ISE-100), cover the . period from January 02, 1990 to December 29, 2004, are analyzed by using threshold autoregressive GARCH (TAR-GARCH) model.
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Conclusion & Impact:Results show that stock return volatility reacts asymmetrically to past information at a lag of one time period in the Turkish stock market.
🔬Design:Modeling & Simulation
📍Scope:2004 Verileri
⚙️Variables:Domain Parameters

Abstract

The aim of this study is to investigate the asymmetric responses in volatility between positive and negative shocks in Turkish stock market. The daily closing values of Istanbul Stock Exchange 100 Index (ISE-100), cover the . period from January 02, 1990 to December 29, 2004, are analyzed by using threshold autoregressive GARCH (TAR-GARCH) model. This study is the first one which examines the asymmetric volatility of stock index return in Turkish stock market by using TAR-GARCH model with daily data for a period of fifteen years. Results show that stock return volatility reacts asymmetrically to past information at a lag of one time period in the Turkish stock market.

Özet

Bu çalışmanın amacı Türkiye hisse senedi piyasasında volatilitenin negatif ve pozitif şoklara asimetrik tepki verip vermediğini incelemektir. Çalışmada kullanılan İstanbul Menkul Kıymetler Borsası 100 Endeksi (IMKB-100) günlük kapanış değerleri 2 Ocak 1990 ve 29 Aralık 2004 tarihleri arasındaki periyodu kapsamaktadır. Bu veriler eşikli otoregresif GÂRCH (TAR-GARCH) modeli kullanılarak analiz edilmiştir. Çalışma 15 yıl gibi uzun bir periyotta TAR-GARCH metoduyla Türkiye hisse senedi piyasasında asimetrik volatiliteyi inceleyen ilk çalışmadır. Sonuçlar hisse senedi getiri volatilitesinin Türkiye hisse senedi piyasasında geçmiş bilgilere bir gecikmede asimetrik tepki verdiğin göstermektedir.

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Cite This Article

AKAR, C. (2022). Asymmetric Responses in Volatility Between Positive and Negative Shocks: New Evidence from Turkish Data by Using TAR-GARCH Model. İ M K B Dergisi, Cilt: 9 - Sayı: 36, 75–82. https://ajindex.com/articles/546397

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References (11)

  1. Balaban, E, Bayar, A., Kan, B., "Stock Return Seasonality and Asymmetric Conditional Volatility in World Equity Markets", Applied Economics Letters, 8, 2001, s. 263-268.
  2. Bekaert, G., Wu, G., "Asymmetric Volatility and Risk in Equity Markets", The Review of Financial Studies, 13, 2000, s. 1-42.
  3. Blair, B., Poon S. H., Taylor, S. "Asymmetric and Crach Effects in Stock Volatility for S&P Index and its Constituents", Applied Financial Economics, Vol. 12, No. 5, 2002, s. 319-329.
  4. Chen C. W. S, Chiang T. C, So M. K. P., "Asymmetrical Reaction to US Stock-Return News: Evidence from Major Stock Markets Based on a Double-Threshold Model" Journal of Economics and Business, 55, 2003, s. 487-502.
  5. Chen C. W. S, So M. K. P., Gerlach, H. R. "Asymmetric Response and Interaction of U.S. and Local News in Financial Markets", Applied Stochastic Models in Business and Industry, 21, 2005, s. 273- 288. " Chiang, T. C, Doong, S. C, "Empirical Analysis of Stock Returns and Volatilities: Evidence from Seven Asian Stock Markets Based on TAR-GARCH Model" Review of Quantitative Finance and Accounting, 17,2001, s. 301-318.
  6. Christie, A., "The Stochastic Behaviour of Common Stock Variances: Value, Leverage and Interest Rate Effects", Journal of Financial Economics, 10, 1982, s. 407-432.
  7. Engle, R., Ng, V., "Measuring and Testing the Impact of News on Volatility", Journal of Finance, 48, 1993, s. 1749-1778. Henry O., "Modelling the Asymmetry of Stock Market Volatility", Applied Financial Economics, 8, 1998, s. 145-153.
  8. French, K. R:, Schwert, W., Stambaugh, R. F., "Expected Stock Returns and Volatility", Journal of Financial Economics, 19, 1987, s. p. 3-30. McMillan G. D,, Speight, E. A., "Asymmetric Volatility Dynamics in High Frequency FTSE-100 Stock Index Futures'", Applied Financial Economics, 13, 2003, s. 599-607.
  9. Nelson, D., "Conditional Heieroscedascity in Asset Returns: A New Approach", Econometrica, 59, 1991, p. 347-370.
  10. Schwert, G. W., "Stock Volatility and the Crash of '87", The Review of Financial Studies, V.3, n.l, 1990, s. 77-102 Shields K. K., "Threshold Modelling of Stock Return Volatility on Eastern European Markets'" Economics of Planning, 30, 1997, s. 107-125.
  11. Tsay, R. S., "Testing and Modeling Threshold Autoregressive Processes," Journal of the American Statistical Association, 84, (1989), s. 231 -240 Wu, G. "The Determinants of Asymmetric Volatility", The Review of Financial Studies, Vol.14, No. 3,2001, s. 837-859.