Democracy versus dictatorship in self-organized models of financial markets

D’hulst, Reinhilde; Rodgers, G. J.

doi:10.1016/s0378-4371(00)00089-3

Cited by 11 publications

(2 citation statements)

References 10 publications

(16 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The models may be extended or manipulated to explore quantitatively the emergence of empirical scaling laws. Alternatively, the approach to 'critical' self-organized, or stable states may be examined [13]. These are just a few of the uses which could be categorized as 'theoretical' study.…”

Section: Introductionmentioning

confidence: 99%

From market games to real-world markets

et al. 2001

View full text Add to dashboard Cite

This paper uses the development of multi-agent market models to present a unified approach to the joint questions of how financial market movements may be simulated, predicted, and hedged against. We examine the effect of different market clearing mechanisms and show that an out-of-equilibrium clearing process leads to dynamics that closely resemble real financial movements. We then show that replacing the `synthetic' price history used by these simulations with data taken from real financial time-series leads to the remarkable result that the agents can collectively learn to identify moments in the market where profit is attainable. We then employ the formalism of Bouchaud and Sornette in conjunction with agent based models to show that in general risk cannot be eliminated from trading with these models. We also show that, in the presence of transaction costs, the risk of option writing is greatly increased. This risk, and the costs, can however be reduced through the use of a delta-hedging strategy with modified, time-dependent volatility structure.Comment: Presented at APFA2 (Liege) July 2000. Proceedings: Eur. Phys. J. B Latex file + 10 .ps figs. n.johnson@physics.ox.ac.u

show abstract

Section: Introductionmentioning

confidence: 99%

From market games to real-world markets

et al. 2001

View full text Add to dashboard Cite

show abstract

“…Therefore it seems relevant that the number of actors on the market be increased at crash time, together with the decrease in exchanged volume. Furthermore the connectivity is a key ingredient in the spreading of information on a market [39] and also leads to consider the effect of interacting agents and herding models [40,41]. Notice that this effect is entirely contained in the oscillations which therefore smoothen the rate of divergence.…”

Section: Predictability and Remedies For A Conclusionmentioning

confidence: 99%

Crashes : symptoms, diagnoses and remedies

Ausloos

Vandewalle

2002

Empirical Science of Financial Fluctuations

View full text Add to dashboard Cite

A brief historical perspective is first given concerning financial crashes, -from the 17th till the 20th century. In modern times, it seems that log periodic oscillations are found before crashes in several financial indices. The same is found in sand pile avalanches on Sierpinski gaskets. A discussion pertains to the after shock period with illustrations from the DAX index. The factual financial observations and the laboratory ones allow us some conjecture on symptoms and remedies for discussing financial crashes along econophysics lines.

show abstract

Herd behaviors in the stock and foreign exchange markets

Kim

Yoon

Kim

2004

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

The herd behaviors of returns for the won-dollar exchange rate and the KOSPI are analyzed in Korean financial markets. It is shown that the probability distribution P (R) of price returns R for three values of the herding parameter tends to a power-law behavior P (R) ≃ R −β with the exponents β = 2.2(the won-dollar exchange rate) and 2.4(the KOSPI). The financial crashes are found to occur at h > 2.33 when the relative increase in the probability distribution of exteremely high price returns is observed. Especially, the distribution of normalized returns shows a crossover to a Gaussian distribution for the time step ∆t = 252. Our results will be also compared to the other well-known analyses.

show abstract

Democracy versus dictatorship in self-organized models of financial markets

Cited by 11 publications

References 10 publications

From market games to real-world markets

From market games to real-world markets

Crashes : symptoms, diagnoses and remedies

Herd behaviors in the stock and foreign exchange markets

Contact Info

Product

Resources

About