BibTex RIS Kaynak Göster

Estimating Probability Of Session Returns For Istanbul Stock Exchange 100 Index As Markov Chain Process

Yıl 2013, Cilt: 22 Sayı: 1, 501 - 512, 01.06.2013

Öz

In this study I modeled session returns for the Istanbul Stock Exchange 100 ISE100 index as the eight discrete state Markov chain process in order to estimate session returns of the ISE100 index The model provides valuable signals to the investors about short run selling and buying investment strategies Keywords: ISE 100 Stock Returns Markov chains Conditional probability

Kaynakça

  • Chen, C. W. S. & So, M. K. P. (2006). On a threshold heteroscedastic model International Journal of Forecasting, Volume 22, Issue 1, January–March 2006, pp 73
  • Eugene F.F (1965). Random Walks in Stock Market Prices, Financial Analysts Journal, September/October.
  • Flietz, B. D. & Bhargava, T. N. (1973). The Behavior of Stock-Price Relatives-A Markovian Analysis, Operations Research, Vol. 21, No. 6 (Nov. - Dec., 1973), pp. 1183-1199.
  • Greyserman, A., Jones, D. H. & Strawderman, W. E. (2006). Portfolio selection using hierarchical Bayesian analysis and MCMC methods, Journal of Banking & Finance, Volume 30, Issue 2, February 2006, pp 669-678.
  • Griffin, J. E. & Steel, M. F. J. (2006). Inference with non-Gaussian Ornstein–Uhlenbeck processes for stochastic volatility, Journal of Econometrics, Volume 134, Issue 2, October 2006, pp 605-644.
  • Guidolin, M. & Timmermann, A. (2007). Properties of equilibrium asset prices under alternative learning schemes, Journal of Economic Dynamics and Control, Volume 31, Issue 1, January 2007, pp 161-217.
  • Hamilton, J. D. & Susmel, R. (1994). Autoregressive conditional heteroskedasticity and changes in regime, Journal of Econometrics, Volume 64, Issues 1–2, September– October 1994, pp 307-333.
  • Kanas, A. (2003). Non-linear Forecasts of Stock Returns , Journal of Forecasting, Vol. 22 Issue 4, p 299.
  • Kılıç, S. B. (2005). Test of the weak form efficient market hypothesis for the Istanbul Stock Exchange by Markov Chains methodology, University of Social Sciences Of Cukurova, Vol:14, No:1, pp 333-342.
  • Lin, S. K., Wang, S. Y. & Tsai, P. L. (2009). Application of hidden Markov switching moving average model in the stock markets: Theory and empirical evidence International Review of Economics & Finance, Volume 18, Issue 2, March 2009, pp 306-3
  • Liu, H. (2011). Dynamic portfolio choice under ambiguity and regime switching mean returns , Journal of Economic Dynamics and Control, Volume 35, Issue 4, April 2011, pp 623-640.
  • McQueen, G. & Thorley, S. (1991). Are Stock Returns Predictable? A Test Using Markov Chains, Journal of Finance, Vol. 46 Issue 1, p239.
  • Mills, T.C. & Jordanov, J. V. (2003). The size effect and the random walk hypothesis: evidence from the London Stock Exchange using Markov Chains, Applied Financial Economics, Vol. 13.
  • Ryan, T. M. (1973). Security Prices As Markov Processes. Journal of Financial & Quantitative Analysis, Vol. 8 Issue 1, pp 17-36.
  • Tsionas, E. G. (2000). Bayesian model comparison by Markov chain simulation: Illustration using stock market data, Research in Economics, Volume 54, Issue 4, December 2000, pp 403-416.
  • Turner, C. M., Startz, R., & Nelson, C. R. (1989). A Markov Model of Heteroscedastisity Risk and Learning in the Stock market, Journal of Financial Economics, 25 (1989) pp 3-22.
  • Zhang, X. & King, M. L. (2008). Box-Cox stochastic volatility models with heavy-tails and correlated errors, Journal of Empirical Finance, Volume 15, Issue3, June2008, pp 549-5

Estimating Probability Of Session Returns For Istanbul Stock Exchange 100 Index As Markov Chain Process

Yıl 2013, Cilt: 22 Sayı: 1, 501 - 512, 01.06.2013

Öz

-

Kaynakça

  • Chen, C. W. S. & So, M. K. P. (2006). On a threshold heteroscedastic model International Journal of Forecasting, Volume 22, Issue 1, January–March 2006, pp 73
  • Eugene F.F (1965). Random Walks in Stock Market Prices, Financial Analysts Journal, September/October.
  • Flietz, B. D. & Bhargava, T. N. (1973). The Behavior of Stock-Price Relatives-A Markovian Analysis, Operations Research, Vol. 21, No. 6 (Nov. - Dec., 1973), pp. 1183-1199.
  • Greyserman, A., Jones, D. H. & Strawderman, W. E. (2006). Portfolio selection using hierarchical Bayesian analysis and MCMC methods, Journal of Banking & Finance, Volume 30, Issue 2, February 2006, pp 669-678.
  • Griffin, J. E. & Steel, M. F. J. (2006). Inference with non-Gaussian Ornstein–Uhlenbeck processes for stochastic volatility, Journal of Econometrics, Volume 134, Issue 2, October 2006, pp 605-644.
  • Guidolin, M. & Timmermann, A. (2007). Properties of equilibrium asset prices under alternative learning schemes, Journal of Economic Dynamics and Control, Volume 31, Issue 1, January 2007, pp 161-217.
  • Hamilton, J. D. & Susmel, R. (1994). Autoregressive conditional heteroskedasticity and changes in regime, Journal of Econometrics, Volume 64, Issues 1–2, September– October 1994, pp 307-333.
  • Kanas, A. (2003). Non-linear Forecasts of Stock Returns , Journal of Forecasting, Vol. 22 Issue 4, p 299.
  • Kılıç, S. B. (2005). Test of the weak form efficient market hypothesis for the Istanbul Stock Exchange by Markov Chains methodology, University of Social Sciences Of Cukurova, Vol:14, No:1, pp 333-342.
  • Lin, S. K., Wang, S. Y. & Tsai, P. L. (2009). Application of hidden Markov switching moving average model in the stock markets: Theory and empirical evidence International Review of Economics & Finance, Volume 18, Issue 2, March 2009, pp 306-3
  • Liu, H. (2011). Dynamic portfolio choice under ambiguity and regime switching mean returns , Journal of Economic Dynamics and Control, Volume 35, Issue 4, April 2011, pp 623-640.
  • McQueen, G. & Thorley, S. (1991). Are Stock Returns Predictable? A Test Using Markov Chains, Journal of Finance, Vol. 46 Issue 1, p239.
  • Mills, T.C. & Jordanov, J. V. (2003). The size effect and the random walk hypothesis: evidence from the London Stock Exchange using Markov Chains, Applied Financial Economics, Vol. 13.
  • Ryan, T. M. (1973). Security Prices As Markov Processes. Journal of Financial & Quantitative Analysis, Vol. 8 Issue 1, pp 17-36.
  • Tsionas, E. G. (2000). Bayesian model comparison by Markov chain simulation: Illustration using stock market data, Research in Economics, Volume 54, Issue 4, December 2000, pp 403-416.
  • Turner, C. M., Startz, R., & Nelson, C. R. (1989). A Markov Model of Heteroscedastisity Risk and Learning in the Stock market, Journal of Financial Economics, 25 (1989) pp 3-22.
  • Zhang, X. & King, M. L. (2008). Box-Cox stochastic volatility models with heavy-tails and correlated errors, Journal of Empirical Finance, Volume 15, Issue3, June2008, pp 549-5
Toplam 17 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Doç.dr.süleyman Bilgin Kılıç Bu kişi benim

Yayımlanma Tarihi 1 Haziran 2013
Gönderilme Tarihi 29 Aralık 2013
Yayımlandığı Sayı Yıl 2013 Cilt: 22 Sayı: 1

Kaynak Göster

APA Kılıç, D. B. (2013). Estimating Probability Of Session Returns For Istanbul Stock Exchange 100 Index As Markov Chain Process. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 22(1), 501-512.