Abstract
This paper seeks to analyze the dynamical structure of the Indian stock market by considering two major Indian stock market indices, namely, BSE Sensex and CNX Nifty. The recurrence quantification analysis (RQA) is applied on the daily closing data of the two series during the period from January 2, 2002, to October 10, 2013. A Rolling Window of 100 and step size 21 are applied in order to see how both the series behave over time. The analysis based on three RQA measures, namely, % determinism (DET), laminarity (LAM), and trapping time (TT), provides conclusive evidence that the Indian equity market is chaotic in nature. Evidences for phase transition in the Indian equity market around the time of financial crisis are also found.
Highlights
An equity market could be considered as complex dynamical system, with different agents as well as institutions having different time horizons in mind, carrying out transactions that result in complex patterns that are reflected in the data
A complex dynamical/chaotic system may be defined as a type of nonlinear dynamical system which could satisfactorily explain a wide range of phenomena in many natural systems, including biological and physical systems
The objective of this paper was to analyze the dynamical behavior of the Indian capital market
Summary
An equity market could be considered as complex dynamical system, with different agents as well as institutions having different time horizons in mind, carrying out transactions that result in complex patterns that are reflected in the data. A complex dynamical/chaotic system may be defined as a type of nonlinear dynamical system which could satisfactorily explain a wide range of phenomena in many natural systems, including biological and physical systems. Such systems appear apparently random in nature but are part of a deterministic process. In a chaotic system, this nonlinear behavior is always limited by a higher deterministic structure. For this reason, there is always an underlying order in the apparent random dynamics
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