Economics: Meltdown modelling

Buchanan, Mark

doi:10.1038/460680a

Cited by 97 publications

(30 citation statements)

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“…Such properties are reminiscent of multifractal processes [Vandewalle & Ausloos, 1998;Calvet & Fisher, 2001] and have on these grounds been modeled as multiplicative cascade processes [Schmitt et al, 2000]. They are also compatible with a Levy stable distribution [Buchanan, 2009;Mandelbrot, 1963;Mantegna & Stanley, 1995]. One important characteristic of the Levy-stable distribution is that it has a power law tail with exponent less than 3, thus predicting the very large fluctuations, crashes and rallies, of the kind seen in stock markets [Mandelbrot, 1966;Blanchard, 1979;Bouchaud & Cont, 1998;Sornette & Malevergne, 2001;Sornette & Johansen, 1997].…”

Section: Introductionmentioning

confidence: 84%

A Dynamical Approach to Stock Market Fluctuations

Nicolis

Sumpter

2011

Int. J. Bifurcation Chaos

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The recent turbulence on the world's stock markets has reinvigorated the attack on classical economic models of stock market fluctuations. The key problem is determining a dynamic model, which is consistent with observed fluctuations and which reflects investor behavior. Here, we use a novel equation-free approach developed in nonlinear dynamics literature to identify the salient statistical features of fluctuations of the Dow Jones Industrial Average over the past 80 years. We then develop a minimal dynamical model in the form of a stochastic differential equation involving both additive and multiplicative system-noise couplings, which captures these features and whose parameterization on a time scale of days can be used to capture market distributions up to a time scale of months. The terms in the model can be directly linked to "herding" behavior on the part of traders. However, we show that parameters in this model have changed over a number of decades producing different market regimes. This result partially explains how, during some periods of history, "classic" economic models may work well and at other periods "econo-physics" models prove better.

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Section: Introductionmentioning

confidence: 84%

A Dynamical Approach to Stock Market Fluctuations

Nicolis

Sumpter

2011

Int. J. Bifurcation Chaos

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“…There is a substantial literature on agent-based modeling (ABM) of financial markets (Buchanan, 2009;Chen et al, 2012;Farmer and Foley, 2009;LeBaron, 2006), much of it geared to reproduce and thereby explain stylized facts from empirical studies of market behavior. For example, simulated markets have been constructed to reproduce phenomena observed in real stock markets, such as bubbles and crashes (LeBaron et al, 1999;Lee et al, 2011).…”

Section: Agent-based Financial Marketsmentioning

confidence: 99%

Latency arbitrage in fragmented markets: A strategic agent-based analysis

Wah¹,

Wellman

2017

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Abstract.We study the effect of latency arbitrage on allocative efficiency and liquidity in fragmented financial markets. We employ a simple model of latency arbitrage in which a single security is traded on two exchanges, with price quotes available to regular traders only after some delay. An infinitely fast arbitrageur reaps profits when the two markets diverge due to this latency in cross-market communication. Using an agent-based approach, we simulate interactions between high-frequency and zero-intelligence trading agents. From simulation data over a large space of strategy combinations, we estimate game models and compute strategic equilibria in a variety of market environments. We then evaluate allocative efficiency and market liquidity in equilibrium, and we find that market fragmentation and the presence of a latency arbitrageur reduces total surplus and negatively impacts liquidity. By replacing continuous-time markets with periodic call markets, we eliminate latency arbitrage opportunities and achieve further efficiency gains through the aggregation of orders over short time periods.

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“…Described by Buchanan (2009) as the social science analogue of the computational simulations now routinely used elsewhere to explore complex nonlinear processes such as the global climate, ABMs may present a viable means of projecting the impact of physical changes upon human systems. A form of social simulation, an agentbased approach represents a computational technique for the study and modelling of social interactions and communications (Li, Mao, Zeng, & Wang, 2008).…”

Section: Agent-based Modelsmentioning

confidence: 99%

Modelling migration futures: development and testing of the Rainfalls Agent-Based Migration Model – Tanzania

Smith

2014

Climate and Development

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This paper describes the conceptual and practical development and testing of the Rainfalls Agent-Based Migration ModelTanzania (RABMM-T). Drawing upon the literature on the process of developing and parameterizing a social simulation in the absence of spatio-temporal data, the paper outlines the translation of the conceptual framework into a working agent-based model. The possible impact of a change in local rainfall variability and mean upon household income, food production, and therefore the resilience and migration of members, is simulated to permit consideration of the possible impact of the artificial scenarios tested. In addition to the influence of changing rainfall, other non-rainfall scenarios are tested to explore the scale of the changes simulated. It is proposed that while a relatively clear impact of rainfall scenarios upon household resilience is simulated, the impact upon migration of household members is generally less clear. Furthermore, demographic and societal changes to the model are also seen to clearly contribute to the simulation outputs generated. The paper concludes that RABMM-T offers the first step in developing a potentially valuable resource for producing comparable migration forecasts that consider a range of contributory mechanisms. However, careful parameterization is required to ensure the quality and value of model outputs.

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Economics: Meltdown modelling

Cited by 97 publications

References 0 publications

A Dynamical Approach to Stock Market Fluctuations

A Dynamical Approach to Stock Market Fluctuations

Latency arbitrage in fragmented markets: A strategic agent-based analysis

Modelling migration futures: development and testing of the Rainfalls Agent-Based Migration Model – Tanzania

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