INVESTIGATION OF SERIAL DEPENDENCE ASYMMETRY AND TIME IRREVERSIBILITY IN STOCK MARKET RETURNS OF MIST COUNTRIES USING THE QUANTILE PERIODOGRAM

The stock market indices of the countries are indicators that provide information about the countries' economies and financial stability. The aim of the study is to determine the similarities and differences in the stock market index return behaviors for Mexico, Indonesia, South Korea and Türkiye, which constitute the MIST country group. For this purpose, the spectral density kernel estimator "Quantile Periodogram" was used. The reason why this estimator is preferred is that it allows the investigation of serial dependence at different quantiles-frequencies and it is robust to outliers frequently encountered in return series, heavy-tailed distribution and changes in the distribution at high moments. The asymmetry of the serial dependence in different quantiles-frequencies and time-irreversibility which gives information about whether the financial series behavior is predictable or not, were analyzed with the quantile periodogram. According to the findings, Türkiye is the most preferred country by financial investors among MIST countries, while Mexico is the least preferred. Secondly, it is seen that the long-term behavior predictability of the returns has increased. This means that returns are more stable in the long run. When the findings are evaluated collectively, it is concluded that MIST countries are attractive for long-term financial investment.

Keywords:

stock market, MIST Countries, Quantile Periodogram, Asymmetry, Time-Irreversibility Predictability,

PDF

___

Birr, S., S. Volgushev, T. Kley, H. Dette and M. Hallin (2017). Quantile Spectral Analysis for Locally Stationary Time Series. Journal of The Royal Statistical Society Series B-statistical Methodology, 79, 1619-1643.
Cajueiro, D.O. and B. M. Tabak (2004). Ranking efficiency for emerging equity markets. Chaos, Solitons & Fractals, Volume 23, Issue 2, 671-675.
Çolak, Ö.F. (2012). MIS(T) gibi ülkeler. https://www.dunya.com/kose-yazisi/mist-gibi-ulkeler/13960 (1 November 2021).
Dette, H., M. Hallin, T. Kley, S. Skowronek and S. Volgushev. (2015). Copula Based Spectral Analysis.
Dette, H., M. Hallin, T. Kley and S. Volgushev (2015). Of copulas, quantiles, ranks and spectra: An L1-approach to spectral analysis. Bernoulli, 21 (2) 781 – 831.
Eom, C., S. Choi, G. Oh and W.- S. Jung (2008). Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets. Physica A: Statistical Mechanics and its Applications, Volume 387, Issue 18, 4630-4636.
Flanagan, R. and L. Lacasa (2016). Irreversibility of financial time series: A graph-theoretical approach.Physics Letters A, Vol.380, Iss.20, 1689-1697.
Hinich, M., and P. Rothman (1998). Frequency-Domaın Test Of Tıme Reversıbılıty. MacroeconomicDynamics,2(1), 72-88.
Jin, L. (2021). Robust tests for time series comparison based on Laplace periodograms. Computational Statistics & Data Analysis, 160, 1-15.
Kley, T., (2016). Quantile-Based Spectral Analysis in an Object-Oriented Framework and a Reference Implementation in R: The quantspec Package. J. Stat. Soft., 70, 1-27.
Kley, T., Volgushev, S., Dette, H., & Hallin, M.(2016).Quantile Spectral Processes: Asymptotic Analysis and Inference. Bernoulli, 22, 1770-1807.
Kunsch, H. R. (1989). The Jackknife and the Bootstrap for General Stationary Observations. The Annals of Statistics, 17(3), 1217–1241.
Li, T. (2012). Quantile Periodograms. Journal of the American Statistical Association, Taylor & Francis Journals, 107(498), 765-776.
Li, T.-H. (2014), Quantile Periodogram and Time-Dependent Variance. J. Time Ser. Anal., 35, 322-340.
Li, T.-H. (2021), Quantile-frequency analysis and spectral measures for diagnostic checks of time series with nonlinear dynamics. J R Stat Soc Series C, 70: 270-290
Lim, K-P., R. D. Brooks and M. Hinich (2008). Are Stock Returns Time Reversible? International Evidence from Frequency Domain Tests. Available at SSRN: https://ssrn.com/abstract=1320165(20 October 2021).
Lim, Y. and HS. Oh (2021). Quantile spectral analysis of long-memory processes. Empirical Economics, 62, 1245-1266.
Psaradakis, Z. (2008). Assessing Time ‐Reversibility Under Minimal Assumptions. Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), 881-905.
Ramsey, J.B. and P.Rothman (1993). Time Irreversibility and Business Cycle Asymmetry. Working Papers 93-39, C.V. Starr Center for Applied Economics, New York University.
Schuster, Arthur (1898). On the investigation of hidden periodicities with application to a supposed 26 day period of meteorological phenomena. Terrestrl Magn., 3, 13 – 41.
Tukey, J.W. (1977). Exploratory data analysis. Reading, Mass: Addison-Wesley Pub. Co.
O’Neill, J. (2011). Welcome to a future built inBRICs.https://www.telegraph.co.uk/finance/financialcrisis/8900851/Jim-ONeill (5 November 2021).
Tschernig, R. (2004). Nonparametric Time Series Modeling. H. Luetkepohl and M. Kraetzig (Ed.). Applied Time Series Econometrics içinde. NY: Cambridge University Press, 243-288.
Yalvaç, F. (2016). Dünya Sisteminde Yeni Bölgesel Güçlerin Yükselişi: Türkiye, BRIC ve MIST Ülkeleri Karşılaştırması. https://hdl.handle.net/11511/59595. (1 November 2021).