Author

Abstract

The aim of this study is to investigate the long memory properties along with structural breaks in the returns of the TEPIX. For this purpose, the properties of the long memory in the daily returns for three periods leading to September 23, 2013 were evaluated using semi- and non-parametric methods. The results show the existence of long memory properties in all periods which may be misleading due to the ignorance of possible structural breaks. Therefore, this paper considers the properties of long memory in the presence of structural breaks using the Bai and Perron test (1998, 2003). In order to examine the null hypothesis of long memory against the alternative of a structural break, we employ the Shimotsu test (2006). In contrast to past findings, we find that the long memory properties of TEPIX are sensitive to the period of analysis. The results suggest that one should be careful about the inference of long memory in the presence of structural breaks or regime changes.

Keywords

راسخی، سعید و امیر خانعلی پور (1388)، «تحلیل تجربی نوسانات و کارایی اطلاعاتی بازار سهام (مطالعه موردی: بورس اوراق بهادار تهران)»، پژوهشهای اقتصادی ایران، فصلنامه علمی- پژوهشکده علوم اقتصادی، سال سیزدهم، شماره 40، صفحات 57– 29.
شعرایی، سعید و محسن ثنایی اعلم (1389)، «بررسی وجود حافظه بلندمدت در بورس اوراق بهادار تهران و ارزیابی مدل‌هایی که حافظه بلندمدت را در نظر می‌گیرند»، مجله پژوهشهای حسابداری مالی، سال دوم، شماره چهارم، صفحات 186-173.
کاشی، منصور؛ فلاح شمس، میرفیض و محمد دنیایی (1392)، «کاربردی از مدل­های حافظه بلندمدت و شکست ساختاری با استفاده از رویکرد کمی»، مهندسی مالی و مدیریت اوراق بهادار، پاییز 1392، صفحات 50-23.
کشاورز حداد، غلامرضا؛ ابراهیمی، سید بابک واکبر جعفر عبدی (1390)، «بررسی سرایت تلاطم میان بازدهی سهام صنعت سیمان و صنایع مرتبط با آن در ایران»، پژوهشهای اقتصادی ایران، فصلنامه علمی- پژوهشکده علوم اقتصادی، سال شانزدهم، شماره 47، صفحات 162-129.
محمدی، شاپور و هستی چیت‌سازان (1390)، «بررسی حافظه­ بلندمدت بورس اوراق بهادار تهران»، مجله تحقیقات اقتصادی، دوره 46، شماره چهارم، صفحات 226-207.
Aloy, M., Boutahar, M., Gente, K., and Péguin -Feissolle, A. (2011), “Purchasing Power Parity and the Long Memory Properties of Real Exchange Rates: Does one Size Fit All?”, Economic Modelling, 28, pp.1279-1290.
Arouri, M. E. H., Hammoudeh, S., Lahiani, A., & Nguyen, D. K. (2012), “Long Memory and Structural Breaks in Modeling the Return and Volatility Dynamics of Precious Metals”, The Quarterly Review of Economics and Finance, 52(2), pp.207-218.
Badhani, K. N. (2012). “Does Nifty have a Long Memory? Semi-parametric Estimation of Fractional Integration in Returns and Volatility”. Decision 39(3),86.
Bai J, Perron P. (1998),“Estimating and Testing Linear Models with Multiple Structural Changes”, Econometrica, 66, pp.47-68.
Bai J, Perron P (2003),“Computation and Analysis of Multiple Structural Change Models”, Journal of Applied Econometrics, 18, pp.1-22.
Bai, J., and P. Perron (2006), “Multiple Structural Change Models: A Simulation Analysis”, in D. Corbae, S.N. Durlauf, and B.E. Hansen (Eds.), Econometric Theory and Practice (Cambridge: Cambridge University Press).
Bond, D., Harrison, M. J., & O'Brien, E. J. (2009), “Exploring Long Memory and Nonlinearity in Irish Real Exchange Rates Using Tests Based on Semiparametric Estimation”, Working Paper Series, UCD Centre for Economic Research,pp.1-22.
Cappelli, C. and Angela, D.: Long Memory and Structural Break Analysis of Environmental Time Series, Available at: old.sis-statistica.org/files/pdf/atti/Spontanee%202006_203-206.pdf (last access: 10 September 2014), 2006.
Chaouachi, S., Ftiti, Z., and Teulon, F. (2014), “Explaining the Tunisian Real Exchange: Long Memory Versus Structural Breaks”, Working Papers 2014-147, Department of Research, Ipag Business School.
Choi, K., Yu, W. C., & Zivot, E. (2010), “Long Memory Versus Structural Breaks in Modeling and Forecasting Realized Volatility”, Journal of International Money and Finance, 29(5),pp. 857-875.
Choi, K., & Zivot, E. (2007), “Long Memory and Structural Changes in the Forward Discount: An Empirical Investigation”, Journal of International Money and Finance, 26(3), pp.342-363.
Diebold,F. X. and Inoue, A. (2001), “Long Memory and Regime Switching”, Journal of Econometrics, 105, pp.131–159.
Diebolt, C. & Guiraud, V. (2005), “A Note on Long Memory Time Series”, Quality and Quantity,39(6),pp.827-836.
Ezzat, Hassan (2013), “Long Memory Processes and Structural Breaks in Stock Returns and Volatility: Evidence from the Egyptian Exchange”, International Research Journal of Finance and Economics, 113: pp. 136-146.
Fernandez, V. (2011), “Alternative Estimators of Long-Range Dependence”, Studies in Nonlinear Dynamics & Econometrics, 15, 2,pp.1-33.
Granger, C.W.J., Hyung, N. (2004), “Occasional Structural Breaks and Long Memory with an Application to the S&P 500 Absolute Stock Returns”, Journal of Empirical Finance,11, pp.399–421.
Granger C. W. J & R. Joyeux. (1980), “An Introduction to Long-Memory Time Series Models and Fractional Differencing- J”. Time Series Anal,15-29.
Haldrup, N., & Kruse, R. (2014), “Discriminating between Fractional Integration and Spurious Long Memory”, (No. 2014-19), School of Economics and Management, University of Aarhus.
Kellard, N., & Sarantis, N. (2008), “Can Exchange Rate Volatility Explain Persistence in the Forward Premium?”, Journal of Empirical Finance, 15(4), pp.714-728
Kim, J. W., Seo, B., & Leatham, D. J. (2010), “Structural Change in Stock Price Volatility of Asian Financial Markets”, Journal of Economic Research, 15,pp. 1-27.
Kumar, D. (2014). “Long Memory in the Volatility of Indian Financial Market: An Empirical Analysis Based on Indian Data”. Anchor Academic Publishing.
Lahiani, A., & Scaillet, O. (2009), “Testing for Threshold Effect in ARFIMA Models: Application to US Unemployment Rate data”, International Journal of Forecasting, 25, 418-428.
Lildholdt, P. (2000). “Long memory and ARFIMA Modeling”, Aarhus.: University of Aarhus and Center for Dinamic Modelling in Economics.
Mynhardt, H. R., Plastun, A., & Makarenko, I. (2014). “Behavior of Financial Markets Efficiency During the Financial Market Crisis: 2007-2009” (No. 58942).University Library of Munich, Germany.
Ohanissian, A., Russell, J. R., & Tsay, R. S. (2008), “True or Spurious Long Memory? A New Test”, Journal of Business & Economic Statistics, 26(2), pp. 161-175.
Olbermann, B. P., Lopes, S. R., & Reisen, V. A. (2006), “Invariance of the first difference in ARFIMA models”, Computational Statistics, 21(3-4),pp. 445-461.
Perron, P., & Qu, Z. (2007), “An Analytical Evaluation of the Log-periodogram Estimate in the Presence of Level Shifts and its Implications for Stock Returns Volatility”, Working Paper: Boston University.
Perron, P., & Qu, Z. (2010),“Long-memory and Level Shifts in the Volatility of Stock Market Return Indices”, Journal of Business & Economic Statistics, 28(2), pp.275-290.
Shimotsu, K. (2006),“Simple (but Effective) Tests of Long Memory Versus Structural Breaks”, Working Paper, Department of Economics, Queen’s University.
Smith A., (2005), “Level Shifts and the Illusion of Long Memory in Economic Time Series”, Journal of Business and Economic Statistics 23, 3, pp.321-335.
Weron, R.(2002), “Estimating Long-range Dependence: Finite Sample Properties and Confidence Intervals”, Physica A: Statistical Mechanics and its Applications, 312(1), 285-299.
Xiu,J. Jin,Y.(2007), “Empirical Study of ARFIMA Model Based on Fractional Differencing”, Physica A, 377, pp.138 – 154.
Yalama, A., & Celik, S. (2013), “Real or Spurious Long Memory Characteristics of Volatility: Empirical Evidence from an Emerging Market”, Economic Modelling, 30, pp.67-72.
Yusof, F., Kane, I. L., & Yusop, Z. (2013), “Structural Break or Long Memory: an Empirical Survey on Daily Rainfall Data Sets Across Malaysia. Hydrology and Earth System Sciences, 17(4), 1311-1318.