THE TREND AND DYNAMICS DISTRIBUTION OF THE JAKARTA STOCK EXCHANGE (JSX) COMPOSITE

Yıl 2012, Cilt: 4 Sayı: 1, 77 - 85, 01.06.2012

Edi Cahyono Buyung Sarita Pasrun Adam Femy Puspita Arisanti

Öz

In this paper we discuss the dynamics of the Jakarta Stock Exchange (JSX)
Composite. The dynamics indicates performance indicator of several industries in
Indonesia. The data is presented as time series. To predict the dynamics from the
data, however, is still difficult. In general, it is almost impossible to predict such
dynamics for the case of high frequency data. Hence, we do not predict the
dynamics. Rather, we seek the trend and the probability density function (pdf).
For a ‘small’ period of time, the pdf is based on the assumption that the dynamics
is normally distributed. Mathematically speaking, this is a time averaging of data,
and in some cases the data is presented in the form of candle sticks. The trend will
be approximated by a higher order polynomial function which is sought by
applying a least square methods. On the other hand, the probability density
function of the data within each candle stick is obtained by computing standard
deviation of the data with respect to the trend in the candle stick.

Anahtar Kelimeler

Jakarta Stock Exchange, JSX Composite, Dynamics, Trend Curve

Kaynakça

• Balakrishnan, K. and Ramachandran, P. A. (2000), “The method of fundamental solutions for linear reaction-diffusion equation”, Methematuics and Computer Modelling, Vol. 31, No. 2-3, pp.221-237.
• Bekiros, S. D. and Diks C. G. H. (2008), “The nonlinear relationship of exchange rates: Parametric and nonparametric causality testing”, Journal of
• Macroeconomics,Vol. 30, No. 4, pp.1641-1650.
• Belolipetskii, A. A. and Ter-Krikorov, A. M. (1984), “Fundamental solutions of the non-linear equation of heat conduction”, USSR Computational Mathematics and Mathematical Physics, Vol. 24, No. 3, pp.141-149.
• Béreau, S., Villavicencio A. L. and Mignon, V. (2010), “Nonlinear adjustment of the real exchange rate towards its equillibrium value: A panel smooth transition error correction modeling”, Economic Modelling,Vol. 27, No.1, pp.404-416.
• Cahyono, E., Juliana, J.R. and Raya, R. (2009), “Asset value dynamics and the fundamental solution of a modified heat equation”, (in the 4th International Conference on Mathemetics and Stattistics), Bandar Lampung, Indonesia, pp.312
• Cahyono, E. and Soeharyadi, Y. (2010), “On the interaction of Barenblatt’s solution to the porous medium equation”, International Journal of Mathematical
• Sciences and Engineering Applications, Vol. 4, No. 2, pp.187-198. Evans, M. D. D. and Lyons, R. K. (2008), “How is macro news tranmitted to exchange rates?”, Journal of Financial Economics,Vol. 88, No. 1, pp.26-50.
• Emekter, R., Jirasakuldech, B. and Snaith, S. M. (2009), “Nonlinear dynamics in foreign exchange excess returns: Tests of asymmetry”, Journal of Multinational
• Financial Management, Vol. 19, No. 3, pp.179-192. Gadea, M. D., Kaabia, M. B. and Sabaté, M. (2009), “Exchange rate regimes and prices: The cases of Italy, Spain and the United Kingdom (187-1998)”, Journal of
• International Financial Markets, Institutions and Money, Vol. 19, No. 3, pp.477- Guevara-Jordan, J. M. and Rojas, S. (2003), “A method of fundamental solutions for modelling porous media advective fluid flow”, Applied Numerical
• Mathematics, Vol. 47, No. 3-4, pp.449-465. Huang, Y., Neftci, S. N. and Guo, F. (2008), “Swap curve dynamics across markets: Case of US dollar versus HK dollar”, Journal of International Financial
• Markets, Institutions and Money, Vol. 18, No. 1, pp.79-93. Ito, T. and Sato, K. (2008), “Exchange rate change and inflation in post-crisis
• Asian economies: Vector autoregression analysis of exchange rate pass-through”, Journal of Money, Credit and Banking, Vol. 40, No. 7, pp.1407-1437.
• Krylova, E., Nikkinen, J. and Vähämaä, S. (2009), “Cross-dynamics of votality term structures implied by foreign exchange options”, Journal of Economics and Business, Vol. 61, No. 5, pp.355-375.
• Mainardi, F. (1996), “The fundamental solutions for the fractional diffusion-wave equation”, Applied Mathematics Letter, Vol. 9, No. 6, pp.23-28.
• Mainardi, F., Roberto, M., Gorenflo, R., and Scalas, E. (2000), “Fractional calculus and continuous time finance. II the waiting time distribution”, Physica A:
• Statistical Mechanics and its Applications, Vol. 287, pp.468-481. Meerschaert, M.M. & Scalas, E. (2006) Couple continuous random walks in finance. Physica A: Statistical Mechanics and its Applications, Vol. 370, pp.114
• Melvin, M. and Taylor, M. P. (2009), “The crisis in foreign exchange market”,
• Journal of International Money and Finance, Vol 28, No 8, pp.1317-1330.
• Muchnik, L., Bunde, A. and Havlin, S. (2009), “Long term memory in extreme returns of financial time series”, Physica A: Statistical Mechanics and its
• Applications, Vol. 388, Issue 19, pp.4145-4150.
• Neter, J., William, W. dan Micheal, H. K. (1990) Applied linear statistical models: regression, analysis of variance, and experimental design. Third edition. Irwin, Boston.
• Resende, M. and Zeidan, R. M. (2008), “Expectation and chaotic dynamics:
• Empirical evindence on exchange rates”, Economics Letters, Vol. 99, No. 1, pp.33-35. Roberto, M., Scalas, E., & Mainardi, F. (2002), “Waiting-times and returns in high-frequency financial data: an empirical study”, Physica A: Statistical
• Mechanics and its Applications, Vol. 314, pp.749-755. Rosner, D. E. (1963), “Fundamental solutions to the diffusion boundary layer equation for seperated flow over solid surfaces at very large prandtl numbers”,
• International Journal of Heat and Mass Transfer, Vol 6, No. 9, pp.793-804.