Multi-scaling modelling in financial markets | Zendy

Ruipeng Liu | Zendy; Tomaso Aste | Zendy; Tiziana Di Matteo | Zendy

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Multi-scaling modelling in financial markets

Author(s) -

Ruipeng Liu,

Tomaso Aste,

Tiziana Di Matteo

Publication year - 2007

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.759585

Subject(s) - hurst exponent , multifractal system , stylized fact , finance , scaling , econometrics , computer science , financial market , volatility (finance) , statistical physics , fractal , economics , mathematics , statistics , physics , mathematical analysis , geometry , macroeconomics

Traditional image retrieval systems are content based image retrieval systems which rely on low-level features for indexing and retrieval of images. CBIR systems fail to meet user expectations because of the gap between the low level features used by such systems and the high level perception of images by humans. Semantics based methods have been used to describe images according to their high level features. In this paper, we performed experiments to identify the failure of existing semantics-based methods to retrieve images in a particular semantic category. We have proposed a new semantic category to describe the intra-region color feature. The proposed semantic category complements the existing high level descriptions. Experimental results confirm the effectiveness of the proposed method.

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