Dynamic Evolution Analysis of Stock Price Fluctuation and Its Control

Xu, Yuhua; Ke, Zhongyi; Xie, Chengrong; Zhou, Wuneng

doi:10.1155/2018/5728090

Cited by 15 publications

(17 citation statements)

References 30 publications

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“…The research also showed that most of family business stocks and market index exhibit long memory in volatility. Xu et al (2018) studied a simple dynamic system of stock price time series' fluctuation based on the rule of stock market. When the stock price time series' fluctuation has been disturbed by external excitations, the system exhibited obviously chaotic phenomena, and its basic dynamic properties have been analysed.…”

Section: Literature Reviewmentioning

confidence: 99%

Deterministic chaos and forecasting in Amazon?s share prices

Hanias

Tsakonas

Magafas

et al. 2020

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Research background: The application of non-linear analysis and chaos theory modelling on financial time series in the discipline of Econophysics. Purpose of the article: The main aim of the article is to identify the deterministic chaotic behavior of stock prices with reference to Amazon using daily data from Nasdaq-100. Methods: The paper uses nonlinear methods, in particular chaos theory modelling, in a case study exploring and forecasting the daily Amazon stock price. Findings & Value added: The results suggest that the Amazon stock price time series is a deterministic chaotic series with a lot of noise. We calculated the invariant parameters such as the maxi-mum Lyapunov exponent as well as the correlation dimension, managed a two-days-ahead forecast through phase space reconstruction and a grouped data handling method.

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Section: Literature Reviewmentioning

confidence: 99%

Deterministic chaos and forecasting in Amazon?s share prices

Hanias

Tsakonas

Magafas

et al. 2020

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“…Since Lorenz discovered the strange attractor for the first time, various chaotic systems have been discovered one after another. Although there are a large number of chaotic systems, the development of chaotic dynamic models is relatively slow in the economic field [1]. Akhmet et al investigated the generation of chaos in economic models through exogenous shocks [2].…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Impulsive Control of Financial Risk Dynamic System with Chaotic Characteristics

Tao

Qing

et al. 2021

Complexity

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The control of financial risk has always been one of the important topics in financial research. Based on the theory of finance, this paper proposes a kind of financial risk dynamic system. By analyzing some properties of the dynamic system, the system shows obvious coexisting chaotic oscillations. In order to control the financial risk dynamic system effectively, this paper proposes a finite-time impulse controller to control the financial risk dynamic system. Simulation results show that the finite-time impulse controller has faster convergence speed than the impulse controller.

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“…It is a common phenomenon in the field of financial research to study the dynamics of financial market and explore the complexity of financial system with various complex scientific methods [1][2][3][4]. In the past, there have been some different research directions through different methods to study financial problems, such as economic physics, chaos economics, and dynamic economics [5][6][7][8][9]. For many years, researchers have devoted themselves to the study of the relationship between dynamics and time data [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Chaotic Dynamics Analysis Based on Financial Time Series

2021

Complexity

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It is a common phenomenon in the field of financial research to study the dynamic of financial market and explore the complexity of financial system by using various complex scientific methods. In this paper, the chaotic dynamic properties of financial time series are analyzed. Firstly, the nonlinear characteristics of the data are discussed through the empirical analysis of agriculture index data; the daily agriculture index returns can be decomposed into the different scales based on wavelet analysis. Secondly, the dynamic system of some nonlinear characteristic data is established according to the Taylor series expansion form, and the corresponding dynamic characteristics are analyzed. Finally, the bifurcation diagram of the system shows complicated bifurcation phenomena, which provides a perspective for the analysis of chaotic phenomena of economic data.

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Dynamic Evolution Analysis of Stock Price Fluctuation and Its Control

Cited by 15 publications

References 30 publications

Deterministic chaos and forecasting in Amazon?s share prices

Deterministic chaos and forecasting in Amazon?s share prices

Finite-Time Impulsive Control of Financial Risk Dynamic System with Chaotic Characteristics

Chaotic Dynamics Analysis Based on Financial Time Series

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