Research Article
BibTex RIS Cite
Year 2016, Volume: 3 Issue: 4, 255 - 265, 31.12.2016
https://doi.org/10.17261/pressacademia.2016.342

Abstract

References

  • Allen, D. E. & Singh, A. K. (2009). Minimizing Loss at Times of Financial Crisis: Quantile Regression as a Tool for Portfolio Investment Decisions. School of Accounting, Finance and Economics & FEMARC Working Paper Series, No: 0912.
  • Allen, D. E., Gerrans, P., Singh, A. K. & Powell, P. (2009). Quantile regression: its application in investment analysis. The Finsia Journal of Applied Finance, Issue: 4.
  • Barnes, M. L. & Huges, A. W. (2002). A Quantile Regression Analysis of the Cross Section of Stock Market Returns. Federal Reserve Bank of Boston in its series Working Papers with number 02-2.
  • Breusch, T.S. & Pagan, A.R. (1980). The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics. Review of Economic Studies, 47, 239–253.
  • Chang, M. C., Hung, J-C. & Nieh, C-C. (2011). Reexamination of capital asset pricing model (CAPM): An application of quantile regression. African Journal of Business Management, Vol. 5(33), pp. 12684-12690.
  • Cohen, K.J., Pogue, J.A. (1967). An Empirical Evaluation of Alternative Portfolio Selection Models, Journal of Business, vol.40, no. 2 (April):166-193.
  • Elton, E.J. & Gruber M.J. (1973). Estimating the Dependence Structure of Share Prices, Journal of Finance, vol. 28, no. 5 (December):1203-32.
  • Fama, E. F. & French, K. R., (1996). Multi-Factor Explanations of Asset Pricing Anomalies. Journal of Finance, 51: 55-84.
  • Irmak, S. & Çetin K. (2009). Hisse Senetlerinin Korelasyon Uzaklıklarına Dayalı Olarak Kümelenmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, C.14, S.1 s.395-406.
  • Kahneman, D., & Tvertsky, A., (1979). Prospect Theory: An Analysis of Decision Under Risk. Econometrica, 47: 2, 263-291.
  • Koenker R., Bassett, G. Jr. (1978). Regression Quantiles. Econometrica, 46(1), pp.33-50.
  • Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis 91, pp.74–89.
  • Küden, M. (2014). Davranışsal Finans Açısından Bireysel Yatırım Tercihlerinin Değerlendirilmesi. Yayımlanmış Yüksek Lisans Tezi, İzmir.
  • Li, T., Sun, L. & Zou, L. (2009). State ownership and corporate performance: A quantile regression analysis of Chinese listed companies. China Economic Review, 20: 703–716.
  • Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets, Review of Economics and Statistics, vol. 47, no. 1 (February):13-37.
  • Ma, L. & Polhman, L. (2008). Return Forecasts and Optimal Portfolio Construction: A Quantile Regression Approach. The European Journal of Finance, 14:5, 409-425.
  • Markowitz, H. (1952). Portfolio Selection, Journal of Finance, 7(1), pp.77-91.
  • Mossin, J. (1966). Equilibrium in a Capital Asset Market, Econometrica, ol. 35, no. 4 (October):768-783.
  • Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. University of Cambridge, Faculty of Economics, Cambridge Working Papers in Economics No. 0435.
  • Pesaran, M. H. (2007). A Simple Panel Unit Root Test in the Presence of Cross Section Dependence. Journal of Applied Econometrics, 22(2), pp.265-312.
  • Roll, R. & Ross, S. A., (1980). An Empirical Investigation of the Arbitrage Pricing Theory. Journal of Finance, 35: 1073-1103.
  • Rosenberg, B. (1974). Extra-Market Components of Covariance in Security Returns, Journal of Financial and Quantitative Analysis, Vol. 9, No. 2 (March):263-273.
  • Ross, S. A. (1976). The Arbitrage Theory of Capital Asset Pricing. Journal of Economic Theory, 13, pp. 341-360.
  • Schoemaker, P., J., H., (1982). The Expected Utility Model: Its Variants, Purposes, Evidences and Limitations. Journal of Economic Literature, 20: 2, 529-563.
  • Sharpe, W. F. (1963). A Simplified Model for Portfolio Analysis. Management Science, Vol. 9, No. 2 (January):277-293.
  • Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. The Journal of Finance, Vol. 19, No. 3, pp. 425-442.
  • Sharpe, W. F., Alexander, G. J. & Bailey, J. V. (1999). Invesments. Prentice-Hall, USA.
  • Taylor, M. & Sarno, L. (1998). The Behaviour Of Real Exchange Rates During The Post-Bretton Woods Period. Journal of International Economics, 46, 281–312.
  • Tobin, J. (1958). Liquidity Preference as Behavior towards Risk, Review of Economic Studies, vol. 25, no. 1 (February):65-86.
  • Tolga, A. & Şahin, I. (2009). Belirsizlik Altında Karar Alma: Geleneksel ve Modern Yaklaşımlar. Türkiye Ekonomi Kurumu Tartışma Metni, No: 2009/7.
  • Uyar (2015). Finansal Raporlama Standartları’nın Piyasa Değerini Açıklama Gücü Üzerine Etkisi. Pamukkale Üniversitesi, Sosyal Bilimler Enstitüsü, Yayımlanmamış Doktora Tezi, Denizli.
  • Von Neuman, J. & Morgenstein, O. (1944). Theory of Games and Economic Behavior. Princeton Princeton University Press, USA.

THE ANALYSIS OF FINANCIAL BETA BEHAVIOUR VIA PANEL QUANTILE REGRESSION APPROACH

Year 2016, Volume: 3 Issue: 4, 255 - 265, 31.12.2016
https://doi.org/10.17261/pressacademia.2016.342

Abstract

In finance theory, Market model has been a major issue for decades. Especially, it is used by most of the researchers to estimate financial beta coefficient. It is obvious that there are some weaknesses to use Ordinary Least Squares (OLS) for estimation of the market model. The coefficients estimated by OLS explain only for mid-point of distribution and the OLS estimator does not consider extreme values. Therefore, Quantile Regression technique provides considering outliers and a detailed report while estimating the market model. The aim of the study is investigating the differences of financial beta coefficients on different quantiles via panel quantile regression technique. For this purpose, daily stock returns which traded in Borsa Istanbul and New York Stock Exchange are used for 2011-2015 period. Findings show that financial beta coefficients change for different points of stock returns for both markets.  It is clear that investors which regard differences of the financial beta coefficient on different quantiles prevent the possible strategic mistakes and losses. Besides, findings contain some important evidences about investor behaviors.

References

  • Allen, D. E. & Singh, A. K. (2009). Minimizing Loss at Times of Financial Crisis: Quantile Regression as a Tool for Portfolio Investment Decisions. School of Accounting, Finance and Economics & FEMARC Working Paper Series, No: 0912.
  • Allen, D. E., Gerrans, P., Singh, A. K. & Powell, P. (2009). Quantile regression: its application in investment analysis. The Finsia Journal of Applied Finance, Issue: 4.
  • Barnes, M. L. & Huges, A. W. (2002). A Quantile Regression Analysis of the Cross Section of Stock Market Returns. Federal Reserve Bank of Boston in its series Working Papers with number 02-2.
  • Breusch, T.S. & Pagan, A.R. (1980). The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics. Review of Economic Studies, 47, 239–253.
  • Chang, M. C., Hung, J-C. & Nieh, C-C. (2011). Reexamination of capital asset pricing model (CAPM): An application of quantile regression. African Journal of Business Management, Vol. 5(33), pp. 12684-12690.
  • Cohen, K.J., Pogue, J.A. (1967). An Empirical Evaluation of Alternative Portfolio Selection Models, Journal of Business, vol.40, no. 2 (April):166-193.
  • Elton, E.J. & Gruber M.J. (1973). Estimating the Dependence Structure of Share Prices, Journal of Finance, vol. 28, no. 5 (December):1203-32.
  • Fama, E. F. & French, K. R., (1996). Multi-Factor Explanations of Asset Pricing Anomalies. Journal of Finance, 51: 55-84.
  • Irmak, S. & Çetin K. (2009). Hisse Senetlerinin Korelasyon Uzaklıklarına Dayalı Olarak Kümelenmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, C.14, S.1 s.395-406.
  • Kahneman, D., & Tvertsky, A., (1979). Prospect Theory: An Analysis of Decision Under Risk. Econometrica, 47: 2, 263-291.
  • Koenker R., Bassett, G. Jr. (1978). Regression Quantiles. Econometrica, 46(1), pp.33-50.
  • Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis 91, pp.74–89.
  • Küden, M. (2014). Davranışsal Finans Açısından Bireysel Yatırım Tercihlerinin Değerlendirilmesi. Yayımlanmış Yüksek Lisans Tezi, İzmir.
  • Li, T., Sun, L. & Zou, L. (2009). State ownership and corporate performance: A quantile regression analysis of Chinese listed companies. China Economic Review, 20: 703–716.
  • Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets, Review of Economics and Statistics, vol. 47, no. 1 (February):13-37.
  • Ma, L. & Polhman, L. (2008). Return Forecasts and Optimal Portfolio Construction: A Quantile Regression Approach. The European Journal of Finance, 14:5, 409-425.
  • Markowitz, H. (1952). Portfolio Selection, Journal of Finance, 7(1), pp.77-91.
  • Mossin, J. (1966). Equilibrium in a Capital Asset Market, Econometrica, ol. 35, no. 4 (October):768-783.
  • Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. University of Cambridge, Faculty of Economics, Cambridge Working Papers in Economics No. 0435.
  • Pesaran, M. H. (2007). A Simple Panel Unit Root Test in the Presence of Cross Section Dependence. Journal of Applied Econometrics, 22(2), pp.265-312.
  • Roll, R. & Ross, S. A., (1980). An Empirical Investigation of the Arbitrage Pricing Theory. Journal of Finance, 35: 1073-1103.
  • Rosenberg, B. (1974). Extra-Market Components of Covariance in Security Returns, Journal of Financial and Quantitative Analysis, Vol. 9, No. 2 (March):263-273.
  • Ross, S. A. (1976). The Arbitrage Theory of Capital Asset Pricing. Journal of Economic Theory, 13, pp. 341-360.
  • Schoemaker, P., J., H., (1982). The Expected Utility Model: Its Variants, Purposes, Evidences and Limitations. Journal of Economic Literature, 20: 2, 529-563.
  • Sharpe, W. F. (1963). A Simplified Model for Portfolio Analysis. Management Science, Vol. 9, No. 2 (January):277-293.
  • Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. The Journal of Finance, Vol. 19, No. 3, pp. 425-442.
  • Sharpe, W. F., Alexander, G. J. & Bailey, J. V. (1999). Invesments. Prentice-Hall, USA.
  • Taylor, M. & Sarno, L. (1998). The Behaviour Of Real Exchange Rates During The Post-Bretton Woods Period. Journal of International Economics, 46, 281–312.
  • Tobin, J. (1958). Liquidity Preference as Behavior towards Risk, Review of Economic Studies, vol. 25, no. 1 (February):65-86.
  • Tolga, A. & Şahin, I. (2009). Belirsizlik Altında Karar Alma: Geleneksel ve Modern Yaklaşımlar. Türkiye Ekonomi Kurumu Tartışma Metni, No: 2009/7.
  • Uyar (2015). Finansal Raporlama Standartları’nın Piyasa Değerini Açıklama Gücü Üzerine Etkisi. Pamukkale Üniversitesi, Sosyal Bilimler Enstitüsü, Yayımlanmamış Doktora Tezi, Denizli.
  • Von Neuman, J. & Morgenstein, O. (1944). Theory of Games and Economic Behavior. Princeton Princeton University Press, USA.
There are 32 citations in total.

Details

Journal Section Articles
Authors

Hakan Aygoren

Umut Uyar

Publication Date December 31, 2016
Published in Issue Year 2016 Volume: 3 Issue: 4

Cite

APA Aygoren, H., & Uyar, U. (2016). THE ANALYSIS OF FINANCIAL BETA BEHAVIOUR VIA PANEL QUANTILE REGRESSION APPROACH. Journal of Economics Finance and Accounting, 3(4), 255-265. https://doi.org/10.17261/pressacademia.2016.342

Journal of Economics, Finance and Accounting (JEFA) is a scientific, academic, double blind peer-reviewed, quarterly and open-access online journal. The journal publishes four issues a year. The issuing months are March, June, September and December. The publication languages of the Journal are English and Turkish. JEFA aims to provide a research source for all practitioners, policy makers, professionals and researchers working in the area of economics, finance, accounting and auditing. The editor in chief of JEFA invites all manuscripts that cover theoretical and/or applied researches on topics related to the interest areas of the Journal. JEFA publishes academic research studies only. JEFA charges no submission or publication fee.

Ethics Policy - JEFA applies the standards of Committee on Publication Ethics (COPE). JEFA is committed to the academic community ensuring ethics and quality of manuscripts in publications. Plagiarism is strictly forbidden and the manuscripts found to be plagiarized will not be accepted or if published will be removed from the publication. Authors must certify that their manuscripts are their original work. Plagiarism, duplicate, data fabrication and redundant publications are forbidden. The manuscripts are subject to plagiarism check by iThenticate or similar. All manuscript submissions must provide a similarity report (up to 15% excluding quotes, bibliography, abstract and method).

Open Access - All research articles published in PressAcademia Journals are fully open access; immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Open access is a property of individual works, not necessarily journals or publishers. Community standards, rather than copyright law, will continue to provide the mechanism for enforcement of proper attribution and responsible use of the published work, as they do now.