Stock market stability: Diffusion entropy analysis

2016 ◽  
Vol 450 ◽  
pp. 462-465 ◽  
Author(s):  
Shouwei Li ◽  
Yangyang Zhuang ◽  
Jianmin He
Keyword(s):  
Stock Market ◽  
Entropy Analysis ◽  
Market Stability ◽  
Diffusion Entropy

scholarly journals Diffusion Entropy Analysis: Stability of Indian Stock Market

2019 ◽  
Vol 8 (4) ◽  
pp. 9358-9362
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Stock Exchange ◽  
Significant Drop ◽  
Bear Market ◽  
Diffusion Entropy ◽  
The Usa ◽  
The Stability ◽  
Indian Stock Market

The large amount of available data of stock markets becomes very beneficial when it is transformed to valuable information. The analysis of this huge data is essential to extract out the useful information. In the present work, we employ the method of diffusion entropy to study time series of different indexes of Indian stock market. We analyze the stability of Nifty50 index of National Stock Exchange (NSE) India and SENSEX index of Bombay Stock Exchange (BSE), India in the vicinity of global financial crisis of 2008. We also apply the technique of diffusion entropy to analyze the stability of Dow Jones Industrial Average (DJIA) index of USA. We compare the results of Indian Stock market with the USA stock market (DJIA index). We conduct an empirical analysis of the stability of Nifty50, Sensex and DJIA indexes. We find significant drop in the value of diffusion entropy of Nifty50, Sensex and DJIA during the period of crisis. Both Indian and USA stock markets show bull market effects in the pre-crisis and post-crisis periods and bear market effect during the period of crisis. Our findings reveal that diffusion entropy technique can replicate the price fluctuations as well as critical events of the stock market.

Diffusion entropy analysis in billiard systems

2019 ◽  
Vol 100 (4) ◽  
Author(s):  
Gabriel I. Díaz ◽  
Matheus S. Palmero ◽  
Iberê Luiz Caldas ◽  
Edson D. Leonel
Keyword(s):  
Entropy Analysis ◽  
Diffusion Entropy

Roles of GARCH and ARCH effects on the stability in stock market crash

2021 ◽  
Author(s):  
Hai-Feng Li ◽  
Dun-Zhong Xing ◽  
Qian Huang ◽  
Jiangcheng Li
Keyword(s):  
Stock Market ◽  
Market Price ◽  
Nonequilibrium Dynamics ◽  
Escape Time ◽  
Theoretical Simulation ◽  
Market Stability ◽  
Share Data ◽  
Escape Process ◽  
The Stability ◽  
The Impact

Abstract We theoretically stochastic simulate and empirically analyze the escape process of stock market price nonequilibrium dynamics under the influence of GARCH and ARCH effects, and explore the impact of ARCH and GARCH effects on stock market stability. Based on the nonlinear GARCH model of econophysics, and combined with GARCH and ARCH effects of volatility, we propose a delay stochastic monostable potential model. We use the mean escape time, or mean hitting time, as an indicator for measuring price stability, as first introduced in Ref. [1]. Based on the comparative analysis of actual Chinese A-share data, the theoretical and empirical findings of this paper are as follows} (1) The theoretical simulation results and actual data are consistent. (2) There exist optimal GARCH and ARCH effects maximally enhancing stock market stability.

Nonextensive Diffusion Entropy Analysis and Teen Birth Phenomena

2004 ◽  
Author(s):  
N. Scafetta ◽  
P. Grigolin
Keyword(s):  
Complex System ◽  
Time Series ◽  
Entropy Analysis ◽  
Fractal Structures ◽  
Mathematical Methods ◽  
Teen Birth ◽  
Working Definition ◽  
Diffusion Entropy ◽  
Wavelet Multiresolution Analysis ◽  
Definition Of

A complex process is often a balance between nonscaling and scaling components. We show how the nonextensive Tsallis g-entropy indicator may be interpreted as a measure of the nonscaling condition in time series. This is done by applying the nonextensive entropy formalism to the diffusion entropy analysis (DEA). We apply the analysis to the study of the teen birth phenomenon. We find that the number of unmarried teen births is strongly influenced by social processes that induce an anomalous memory in the data. This memory is related to the strength of the nonscaling component of the signal and is more intense than that in the married teen birth time series. By using a wavelet multiresolution analysis, we attempt to provide a social interpretation of this effect…. One of the most exciting and rapidly developing areas of modern research is the quantitative study of "complexity." Complexity has special interdisciplinary impacts in the fields of physics, mathematics, information science, biology, sociology, and medicine. No definition of a complex system has been universally embraced, so here we adopt the working definition, "an arrangement of parts so intricate as to be hard to understand or deal with." Therefore, the main goal of the science of complexity is to develop mathematical methods in order to discriminate among the fundamental microscopic and macroscopic constituents of a complex system and to describe their interrelations in a concise way. Experiments usually yield results in the form of time series for physical observables. Typically, these time series contain both a slow regular variation, usually called a "signal," and a rapid erratic fluctuation, usually called "noise." Historically, the techniques applied to processing such time series have been based on equilibrium statistical mechanics and, therefore, they are not applicable to phenomena far from equilibrium. Among the fluctuating phenomena, a particularly important place is occupied by those phenomena characterized by some type of self-similar or scaling-fractal structures [4]. In this chapter we show that the nonextensive Tsallis g-entropy indicator may be interpreted as a measure of the strength of the nonscaling component of a time series.

Stock market stability index: An intelligent approach

2009 ◽  
Vol 13 (6) ◽  
pp. 983-993 ◽  
Author(s):  
Il Suh Son ◽  
Kyong Joo Oh ◽  
Tae Yoon Kim ◽  
Chiho Kim ◽  
Jong-Du Do
Keyword(s):  
Stock Market ◽  
Stability Index ◽  
Market Stability ◽  
Intelligent Approach
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