Statistical properties of the Indonesian Stock Exchange Index

Herd behavior in weight-driven information spreading models for financial market

“…On the other hand, if the information dispersion is much faster than the trading activity then the relative increase in the distribution of extremely high return is observed. This relative increase of return distribution is known to be related to the financial crashes [9,13,14]. As shall be seen in Section 2 we indeed find that the relative increase in the return distribution is observed during the 9.11 crash.…”

“…Among those empirical studies, the most remarkable finding is that many different markets share universal properties. For example, the fat-tailed distribution of returns [2,3,5], long-term volatility correlation [2,6,7] and herding behavior [8,9] have been observed in many different markets [3][4][5][10][11][12][13][14]. The existence of such universal nature in many different markets is striking and suggests that those markets should be governed by the similar underlying mechanisms.…”

Changes in The Statistical Properties of The Indonesian Stock Exchange Index Trough Five Different Time Periods Since 1998 Until 2016

“…In Indonesia, there has been an effort of using statistical physics to study the variations in stock price index [6,7]. In those studies, the authors analyze the distributions of the Indonesian stock exchange index (IHSG), in the time span that includes before, during, and after the 1997 monetary crisis.…”

“…Many empirical studies shows that the distribution of the price return index behave like a heavy tailed bell-shaped curve [8][9][10], and that it can be fitted to a Levy-stable distribution [6,7], this was first proposed by Mandelbrot [5]. Nevertheless, other types of distributions have also been used to describe the price return index, including the Gaussian function [6,7,11]. As a nice bookkeeping of different fitting approach to the price return index, as well as an effort to provide a standard, one can refer to Ref.…”

“…Naturally, one can make the relations between the change of the financial situations, with any major events that took place around the changing point dates. In the earlier work ( [6,7]) the changing points are determined a priori as the dates when the Indonesian Rupiah currency rates fall very steeply. It is the aim of our study, to find the changing points without any assumptions based on any socio-economic situations.…”