Reducing financial avalanches by random investments
METADATA ONLY
Loading...
Author / Producer
Date
2013-12
Publication Type
Journal Article
ETH Bibliography
yes
Citations
Altmetric
METADATA ONLY
Data
Rights / License
Abstract
Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanche dynamics in financial markets. We consider a community of interacting investors, distributed in a small-world network, who bet on the bullish (increasing) or bearish (decreasing) behavior of the market which has been specified according to the S&P 500 historical time series. Remarkably, we find that the size of herding-related avalanches in the community can be strongly reduced by the presence of a relatively small percentage of traders, randomly distributed inside the network, who adopt a random investment strategy. Our findings suggest a promising strategy to limit the size of financial bubbles and crashes. We also obtain that the resulting wealth distribution of all traders corresponds to the well-known Pareto power law, while that of random traders is exponential. In other words, for technical traders, the risk of losses is much greater than the probability of gains compared to those of random traders. © 2013 American Physical Society.
Permanent link
Publication status
published
External links
Editor
Book title
Journal / series
Volume
88 (6)
Pages / Article No.
62814
Publisher
American Physical Society
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Organisational unit
03784 - Helbing, Dirk / Helbing, Dirk