Self-organized criticality and stock market dynamics: an empirical study

Bartolozzi, Maria Letizia; Leinweber, Derek B.; Thomas, A. W.

doi:10.1016/j.physa.2004.11.061

Cited by 34 publications

(35 citation statements)

References 42 publications

(59 reference statements)

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“…The time series, Fig. 11, as expected for a market near-equilibrium, displays a mean reverting behaviour, that is the imbalance tends to fluctuate all time, more or less symmetrically, around a "pseudoequilibrium" price, possibly close to criticality Bartolozzi et al (2005Bartolozzi et al ( , 2006. The same dynamics has been observed for ∆V in different futures contracts (Bartolozzi et al, 2007a).…”

Section: Lob Average Shape Spread and Imbalance Dynamicssupporting

confidence: 61%

A multi agent model for the limit order book dynamics

Bartolozzi

2010

Eur. Phys. J. B

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Abstract. In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The agents follow a noise decision making process where their actions are related to a stochastic variable, the market sentiment, which we define as a mixture of public and private information. The model, despite making just few basic assumptions over the trading strategies of the agents, is able to reproduce several empirical features of the high-frequency dynamics of the market microstructure not only related to the price movements but also to the deposition of the orders in the book.

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Section: Lob Average Shape Spread and Imbalance Dynamicssupporting

confidence: 61%

A multi agent model for the limit order book dynamics

Bartolozzi

2010

Eur. Phys. J. B

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“…Motivated by recent observations of avalanche-like dynamics in financial time series [18], we investigate a possible similar behaviour in the popular multifractal random walk (MRW) originally proposed in Ref. [24] as a paradigm for the stock market behaviour.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the theoretical interest, reliable tests to prove the presence of SOC in real systems are still in their Send offprint requests to: marco.bartolozzi@gmf.com.au a Current affiliation: Research Group, Grinham Managed Funds, Sydney NSW 2065, Australia infancy. Some attempts have been made in the contest of solar flaring [13], astrophysical [14,15] and laboratory [16,17] plasmas and the stock market [18]. These works, while leaving open the question of a SOC behaviour, clearly show that the evolution of these systems can be well described by an avalanche-like dynamics characterized by power laws in the avalanche size, duration and waiting time between them.…”

Section: Introductionmentioning

confidence: 99%

Scale-free avalanches in the multifractal random walk

Bartolozzi

2007

Eur. Phys. J. B

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Avalanches, or Avalanche-like, events are often observed in the dynamical behaviour of many complex systems which span from solar flaring to the Earth's crust dynamics and from traffic flows to financial markets. Self-organized criticality (SOC) is one of the most popular theories able to explain this intermittent charge/discharge behaviour. Despite a large amount of theoretical work, empirical tests for SOC are still in their infancy. In the present paper we address the common problem of revealing SOC from a simple time series without having much information about the underlying system. As a working example we use a modified version of the multifractal random walk originally proposed as a model for the stock market dynamics. The study reveals, despite the lack of the typical ingredients of SOC, an avalanche-like dynamics similar to that of many physical systems. While, on one hand, the results confirm the relevance of cascade models in representing turbulent-like phenomena, on the other, they also raise the question about the current state of reliability of SOC inference from time series analysis.

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“…This abrupt transition makes the system move from a state where the effect of the entities' dynamics is local to a state where the effect is global (Thiétart, 2000). Catastrophic complexity is illustrated in several models, such as the sand pile model with few large avalanches and lots of small ones (Christensen et al, 1991) and the study of stock market dynamics (Bartolozzi et al, 2005).…”

Section: The Main Complex System Theoriesmentioning

confidence: 99%

Simulating Complex Systems - Complex System Theories, Their Behavioural Characteristics and Their Simulation

Aziza

Borgi

Zgaya

et al. 2016

Proceedings of the 8th International Conference on Agents and Artificial Intelligence

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Abstract:Complexity science offers many theories such as chaos theory and coevolutionary theory. These theories illustrate a large set of real life systems and help decipher their nonlinear and unpredictable behaviours.Categorizing an observed Complex System among these theories depends on the aspect that we intend to study, and it can help better understand the phenomena that occur within the system. This article aims to give an overview on Complex Systems and their modelling. Therefore, we compare these theories based on their main behavioural characteristics, e.g. emergence, adaptability, and dynamism. Then we compare the methods used in the literature to model and simulate Complex Systems, and we propose a simple guide to select the appropriate method for modelling a Complex System.

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Self-organized criticality and stock market dynamics: an empirical study

Cited by 34 publications

References 42 publications

A multi agent model for the limit order book dynamics

A multi agent model for the limit order book dynamics

Scale-free avalanches in the multifractal random walk

Simulating Complex Systems - Complex System Theories, Their Behavioural Characteristics and Their Simulation

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