The dynamics of Boolean networks with scale-free topology are studied. The existence of a phase transition from ordered to chaotic dynamics, governed by the value of the scale-free exponent of the network, is shown analytically by analyzing the overlap between two distinct trajectories. The phase di
The scale-free topology of market investments
β Scribed by Diego Garlaschelli; Stefano Battiston; Maurizio Castri; Vito D.P. Servedio; Guido Caldarelli
- Publisher
- Elsevier Science
- Year
- 2005
- Tongue
- English
- Weight
- 581 KB
- Volume
- 350
- Category
- Article
- ISSN
- 0378-4371
No coin nor oath required. For personal study only.
β¦ Synopsis
We propose a network description of large market investments, where both stocks and shareholders are represented as vertices connected by weighted links corresponding to shareholdings. In this framework, the in-degree (k in ) and the sum of incoming link weights (v) of an investor correspond to the number of assets held (portfolio diversification) and to the invested wealth (portfolio volume), respectively. An empirical analysis of three different real markets reveals that the distributions of both k in and v display power-law tails with exponents g and a: Moreover, we find that k in scales as a power-law function of v with an exponent b: Remarkably, despite the values of a; b and g differ across the three markets, they are always governed by the scaling relation b ΒΌ Γ°1 Γ aΓ=Γ°1 Γ gΓ: We show that these empirical findings can be reproduced by a recent model relating the emergence of scale-free networks to an underlying Paretian distribution of 'hidden' vertex properties.
π SIMILAR VOLUMES
Self-organized criticality (SOC) has been claimed to play an important role in many natural and social systems. In the present work we empirically investigate the relevance of this theory to stock-market dynamics. Avalanches in stock-market indices are identified using a multi-scale wavelet-filterin