Heterogeneity, spontaneous coordination and extreme events within large-scale and small-scale agent-based financial market models

Predictive analysis of epidemics often depends on the initial conditions of the outbreak, the structure of the afflicted population, and population size. However, disease outbreaks are subjected to fluctuations that may shape the spreading process. Agent-based epidemic models mitigate the issue by using a transition matrix which replicates stochastic effects observed in real epidemics. They have met considerable numerical success to simulate small scale epidemics. The problem grows exponentially with population size, reducing the usability of agent-based models for large scale epidemics. Here, we present an algorithm that explores permutation symmetries to enhance the computational performance of agent-based epidemic models. Our findings bound the stochastic process to a single eigenvalue sector, scaling down the dimension of the transition matrix to o ( N 2 ) .

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Optimal Lockdown Strategies: All about Time

10.21203/rs.3.rs-194973/v1 ◽

2021 ◽

Author(s):

Anagh Pathak ◽

Varun Madan Mohan ◽

Arpan Banerjee

Keyword(s):

Large Scale ◽

Economic Cost ◽

Mitigation Strategies ◽

Disease Spread ◽

Small Scale ◽

Mass Model ◽

Agent Based ◽

Effective Reduction ◽

Limiting Case ◽

Infection Spread

Abstract Lockdowns are disease mitigation strategies that aim to contain the spread of an infection by restricting the interactions of its carriers. Lockdowns can thus have a considerable economic cost, which makes the identification of optimal lockdown windows that minimize both infection spread and economic disruption imperative. A well-known feature of complex dynamical systems is their sensitivity to the timing of external inputs. Hence, we hypothesized that the timing and duration of lockdowns should dictate lockdown outcomes. We demonstrate this concept computationally from two perspectives - Firstly, a stochastic "small-scale" Agent Based Model (ABM) of a Susceptible-Infected-Recovered (SIR) disease spread and secondly, a deterministic "large-scale" perspective using a multi-group SIR mass model with parameters determined from the SARS-CoV2 data in India. Lockdowns were implemented as an effective reduction of interaction probabilities in both models. This allowed us to evaluate the parametric variations of lockdown intensity and duration onto the dynamical properties of the infection spread over different connection topologies. We definitively show that the lockdown outcomes in both the stochastic small-scale and deterministic large-scale perspectives depend sensitively on the timing of its imposition and that it is possible to minimize lockdown duration while limiting case loads to numbers below hospitalization thresholds.

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The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies

Agent Based Models for Economic Policy Advice ◽

10.1515/9783110508840-004 ◽

2008 ◽

Cited By ~ 9

Author(s):

Frank H. Westerhoff

Keyword(s):

Financial Market ◽

Market Models ◽

Agent Based ◽

Regulatory Policies

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How essential of the balance between large and small scale features to reproduce precipitation during a sudden sharp turn from drought to flood

10.5194/egusphere-egu2020-12558 ◽

2020 ◽

Author(s):

Yuanyuan Ma

Keyword(s):

Extreme Events ◽

Large Scale ◽

Climate Model ◽

Regional Climate ◽

Small Scale ◽

Model Errors ◽

Continuous Simulation ◽

Spectral Nudging ◽

Sharp Turn ◽

The Difference

<p>Sudden turn from drought to flood (STDF) is a unique representation of intra-seasonal extreme events and occurs frequently. However, it is notoriously difficult to represent in climate simulations due to the accumulation of model errors. This study uses a regional climate model (RCM) with different initialization and nudging schemes to explore effective approaches for capturing a STDF event. Results show that the conventional continuous integration with single initialization cannot reproduce the STDF event, while nudging or re-initialization can. Furthermore, spectral nudging and re-initialization outperform the conventional continuous simulation in reproducing precipitation features, but grid nudging induces the largest biases for precipitation though it has the smallest biases for other meteorological elements. Scale separation analysis shows that the large-scale features of the conventional continuous simulation drift far from the actual fields and force erroneous small-scale features, whereas the nudging and re-initialization successfully prevent the model from drifting away from the forcing fields at large-scales. The different performance for simulating precipitation among spectral nudging, re-initialization and grid nudging can be attributed to that the former two methods generate their own small-scale information via the RCM, while grid nudging over-suppresses the small-scale information while retaining the large-scale features. The difference in small-scale features affects the simulation of different moisture fluxes and convergences, as well as clouds, and then results in diverse precipitation. These results illustrate that both the consistency with large-scale features and the local variability from small-scale features are both robust factors for reproducing precipitation features during extreme events using RCMs.</p>

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Discovering the opposite shore: How did hominins cross sea straits?

PLoS ONE ◽

10.1371/journal.pone.0252885 ◽

2021 ◽

Vol 16 (6) ◽

pp. e0252885

Author(s):

Ericson Hölzchen ◽

Christine Hertler ◽

Ana Mateos ◽

Jesús Rodríguez ◽

Jan Ole Berndt ◽

...

Keyword(s):

Large Scale ◽

Scale Effects ◽

Small Scale ◽

Behavioral Models ◽

Comprehensive Understanding ◽

Agent Based ◽

Continental Scale ◽

Water Barrier ◽

Sea Straits ◽

Scale Models

Understanding hominin expansions requires the comprehension of movement processes at different scales. In many models of hominin expansion these processes are viewed as being determined by large-scale effects, such as changes in climate and vegetation spanning continents and thousands or even millions of years. However, these large-scale patterns of expansions also need to be considered as possibly resulting from the accumulation of small-scale decisions of individual hominins. Moving on a continental scale may for instance involve crossing a water barrier. We present a generalized agent-based model for simulating the crossing of a water barrier where the agents represent the hominin individuals. The model can be configured to represent a variety of movement modes across water. Here, we compare four different behavioral scenarios in conjunction with a set of water barrier configurations, in which agents move in water by either paddling, drifting, swimming or rafting. We introduce the crossing-success-rate (CSR) to quantify the performance in water crossing. Our study suggests that more focus should be directed towards the exploration of behavioral models for hominins, as directionality may be a more powerful factor for crossing a barrier than environmental opportunities alone. A prerequisite for this is to perceive the opposite shore. Furthermore, to provide a comprehensive understanding of hominin expansions, the CSR allows for the integration of results obtained from small-scale simulations into large-scale models for hominin expansion.

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Come Together: The Role of Cognitively Biased Imitators in a Small Scale Agent-Based Financial Market

Games and Dynamics in Economics ◽

10.1007/978-981-15-3623-6_4 ◽

2020 ◽

pp. 69-88

Author(s):

Giovanni Campisi ◽

Fabio Tramontana

Keyword(s):

Financial Market ◽

Small Scale ◽

Agent Based

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AN AGENT-BASED MODEL OF HUMAN DISPERSALS AT A GLOBAL SCALE

Advances in Complex Systems ◽

10.1142/s0219525913500239 ◽

2013 ◽

Vol 16 (04n05) ◽

pp. 1350023 ◽

Cited By ~ 10

Author(s):

SIMONE CALLEGARI ◽

JOHN DAVID WEISSMANN ◽

NATALIE TKACHENKO ◽

WESLEY P. PETERSEN ◽

GEORGE LAKE ◽

...

Keyword(s):

Population Dynamics ◽

High Performance ◽

Large Scale ◽

Global Scale ◽

Small Scale ◽

Emergent Properties ◽

Agent Based ◽

Human Dispersal ◽

Model Hierarchy ◽

Empirical Context

In this paper, we report on the theoretical foundations, empirical context and technical implementation of an agent-based modeling (ABM) framework, that uses a high-performance computing (HPC) approach to investigate human population dynamics on a global scale, and on evolutionary time scales. The ABM-HPC framework provides an in silico testbed to explore how short-term/small-scale patterns of individual human behavior and long-term/large-scale patterns of environmental change act together to influence human dispersal, survival and extinction scenarios. These topics are currently at the center of the Neanderthal debate, i.e., the question why Neanderthals died out during the Late Pleistocene, while modern humans dispersed over the entire globe. To tackle this and similar questions, simulations typically adopt one of two opposing approaches, top-down (equation-based) and bottom-up (agent-based) models of population dynamics. We propose HPC technology as an essential computational tool to bridge the gap between these approaches. Using the numerical simulation of worldwide human dispersals as an example, we show that integrating different levels of model hierarchy into an ABM-HPC simulation framework provides new insights into emergent properties of the model, and into the potential and limitations of agent-based versus continuum models.

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MARKET DIMENSIONALITY AND THE PROLIFERATION OF SMALL-SCALE FIRMS

Advances in Complex Systems ◽

10.1142/s0219525908001593 ◽

2008 ◽

Vol 11 (02) ◽

pp. 231-247 ◽

Cited By ~ 4

Author(s):

CÉSAR GARCÍA-DÍAZ ◽

ARJEN VAN WITTELOOSTUIJN ◽

GÁBOR PÉLI

Keyword(s):

Product Differentiation ◽

Price Discrimination ◽

Product Space ◽

Large Scale ◽

Small Degree ◽

High Dimensionality ◽

Small Scale ◽

Two Dimensional ◽

Agent Based ◽

Alternative Approach

We build an agent-based computational model to study how the changing number of active product variants in a two-dimensional product space affects the performance of different firm types (i.e. large-scale and small-scale enterprises). We use an alternative approach to measure product space dimensionality, considering that dimensions may be a fraction of the Euclidean measure. The results confirm that high dimensionality gives advantage to small-scale firms. Additionally, we find that large-scale firms may also benefit from initial increasing dimensionality, since it allows a small degree of product differentiation and price discrimination.

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