Mattarocci, Gianluca
(2006):
*Market characteristics and chaos dynamics in stock markets: an international comparison.*

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## Abstract

The chaos theory assumes that the returns dynamics are not normally distributed and more complex approaches have to be used to study these time series. In fact, the Fractal Market Hypothesis assumes that the returns dynamics are not independent of the investors’ attitudes and represent the result of the interaction of traders who, frequently, adopt different investment styles. The studies proposed in literature try to identify the best approach to define the fractal dimension using, in particular, data of highly developed financial markets where a more complete set of information is available and the price determination mechanism is more efficient. A fault found with these approaches is that the results do not allow making out if there is a relationship between fractal dimension and market characteristics and, besides, it is hard to understand which aspects are more relevant in the definition of the fractal market dimension. In fact, previous studies analysed market liquidity for a limited number of countries and no other aspects related to market transactions have been considered. Using a large sample of world stock indexes, I try to identify the main market characteristics that influence returns dynamics. This study, carried out having recourse to the Rescaled Range Analysis (R/S) approach, shows that markets characteristic, like liquidity, type of admissible orders and so on, influence the R/S capability to study returns dynamics.

Item Type: | MPRA Paper |
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Institution: | University of Rome Tor Vergata - Sefemeq department |

Original Title: | Market characteristics and chaos dynamics in stock markets: an international comparison |

Language: | English |

Keywords: | Chaos; fractal dimension; R/S analysis and market characteristics |

Subjects: | D - Microeconomics > D4 - Market Structure, Pricing, and Design > D49 - Other G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing ; Trading Volume ; Bond Interest Rates C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General F - International Economics > F3 - International Finance > F37 - International Finance Forecasting and Simulation: Models and Applications |

Item ID: | 4296 |

Depositing User: | Gianluca Mattarocci |

Date Deposited: | 31 Jul 2007 |

Last Modified: | 26 Sep 2019 19:35 |

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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/4296 |