Complexity analysis of the stock market

Joongwoo Brian Park; Jeong Won Lee; Jae Suk Yang; Hang Hyun Jo; Hie Tae Moon

doi:10.1016/j.physa.2006.12.042

Complexity analysis of the stock market

Joongwoo Brian Park
, Jeong Won Lee
, Jae Suk Yang
, Hang Hyun Jo
, Hie Tae Moon

Physics

Korea Advanced Institute of Science and Technology
Korea University

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

We study the complexity of the stock market by constructing ε{lunate}-machines of Standard and Poor's 500 index from February 1983 to April 2006 and by measuring the statistical complexities. It is found that both the statistical complexity and the number of causal states of constructed ε{lunate}-machines have decreased for last 20 years and that the average memory length needed to predict the future optimally has become shorter. These results support that the information is delivered to the economic agents and applied to the market prices more rapidly in year 2006 than in year 1983.

Original language	English
Pages (from-to)	179-187
Number of pages	9
Journal	Physica A: Statistical Mechanics and its Applications
Volume	379
Issue number	1
DOIs	https://doi.org/10.1016/j.physa.2006.12.042
State	Published - 1 Jun 2007

Bibliographical note

Funding Information:
The initial development of the PCATS Triaxial apparatus was supported through the Technology Strategy Board (TSB) Knowledge Transfer Partnership grant ( KTP007047 ). This study was also financially supported by the Research Consortium for Methane Hydrate Resources in Japan (MH21 Research Consortium) to carry out Japan's Methane Hydrate R&D Program conducted by the Ministry of Economy, Trade and Industry (METI).

Keywords

Computational mechanics
Econophysics
Statistical complexity

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10.1016/j.physa.2006.12.042

Cite this

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title = "Complexity analysis of the stock market",

abstract = "We study the complexity of the stock market by constructing ε\{lunate\}-machines of Standard and Poor's 500 index from February 1983 to April 2006 and by measuring the statistical complexities. It is found that both the statistical complexity and the number of causal states of constructed ε\{lunate\}-machines have decreased for last 20 years and that the average memory length needed to predict the future optimally has become shorter. These results support that the information is delivered to the economic agents and applied to the market prices more rapidly in year 2006 than in year 1983.",

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note = "Funding Information: The initial development of the PCATS Triaxial apparatus was supported through the Technology Strategy Board (TSB) Knowledge Transfer Partnership grant ( KTP007047 ). This study was also financially supported by the Research Consortium for Methane Hydrate Resources in Japan (MH21 Research Consortium) to carry out Japan's Methane Hydrate R\&D Program conducted by the Ministry of Economy, Trade and Industry (METI).",

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AU - Won Lee, Jeong

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N1 - Funding Information: The initial development of the PCATS Triaxial apparatus was supported through the Technology Strategy Board (TSB) Knowledge Transfer Partnership grant ( KTP007047 ). This study was also financially supported by the Research Consortium for Methane Hydrate Resources in Japan (MH21 Research Consortium) to carry out Japan's Methane Hydrate R&D Program conducted by the Ministry of Economy, Trade and Industry (METI).

PY - 2007/6/1

Y1 - 2007/6/1

N2 - We study the complexity of the stock market by constructing ε{lunate}-machines of Standard and Poor's 500 index from February 1983 to April 2006 and by measuring the statistical complexities. It is found that both the statistical complexity and the number of causal states of constructed ε{lunate}-machines have decreased for last 20 years and that the average memory length needed to predict the future optimally has become shorter. These results support that the information is delivered to the economic agents and applied to the market prices more rapidly in year 2006 than in year 1983.

AB - We study the complexity of the stock market by constructing ε{lunate}-machines of Standard and Poor's 500 index from February 1983 to April 2006 and by measuring the statistical complexities. It is found that both the statistical complexity and the number of causal states of constructed ε{lunate}-machines have decreased for last 20 years and that the average memory length needed to predict the future optimally has become shorter. These results support that the information is delivered to the economic agents and applied to the market prices more rapidly in year 2006 than in year 1983.

KW - Computational mechanics

KW - Econophysics

KW - Statistical complexity

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JO - Physica A: Statistical Mechanics and its Applications

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IS - 1

ER -

Complexity analysis of the stock market

Abstract

Bibliographical note

Keywords

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