Information versus imitation in a real-time agent-based model of financial markets

This chapter develops an agent-based model to analyze microscopic and macroscopic links between investor behaviors and price fluctuations in a financial market. This analysis focuses on the effects of Passive Investment Strategy in a financial market. From the extensive analyses, we have found that (1) Passive Investment Strategy is valid in a realistic efficient market, however, it could have bad influences such as instability of market and inadequate asset pricing deviations, and (2) under certain assumptions, Passive Investment Strategy and Active Investment Strategy could coexist in a Financial Market.

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An Agent-Based Model to Study the Impact of Convex Incentives on Financial Markets

Advances in Intelligent Systems and Computing - Trends in Practical Applications of Scalable Multi-Agent Systems, the PAAMS Collection ◽

10.1007/978-3-319-40159-1_1 ◽

2016 ◽

pp. 3-13 ◽

Cited By ~ 1

Author(s):

Annalisa Fabretti ◽

Tommy Gärling ◽

Stefano Herzel ◽

Martin Holmen

Keyword(s):

Financial Markets ◽

Agent Based Model ◽

Agent Based ◽

The Impact

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Tax optimization in an agent-based model of real-time spectrum secondary market

Telecommunication Systems ◽

10.1007/s11235-016-0180-4 ◽

2016 ◽

Vol 64 (3) ◽

pp. 543-558 ◽

Cited By ~ 6

Author(s):

Juraj Gazda ◽

Viliam Kováč ◽

Peter Tóth ◽

Peter Drotár ◽

Vladimír Gazda

Keyword(s):

Real Time ◽

Time Spectrum ◽

Secondary Market ◽

Agent Based Model ◽

Agent Based

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Real-time Analysis of City Scale Transportation Networks in New Orleans Metropolitan Area using an Agent Based Model Approach

MATEC Web of Conferences ◽

10.1051/matecconf/201927106007 ◽

2019 ◽

Vol 271 ◽

pp. 06007

Author(s):

Millard McElwee ◽

Bingyu Zhao ◽

Kenichi Soga

Keyword(s):

New Orleans ◽

Real Time ◽

High Performance ◽

Large Scale ◽

Transportation Networks ◽

Transportation Network ◽

Regional Scale ◽

Agent Based Model ◽

Agent Based ◽

Real Time Analysis

The primary focus of this research is to develop and implement an agent-based model (ABM) to analyze the New Orleans Metropolitan transportation network near real-time. ABMs have grown in popularity because of their ability to analyze multifaceted community scale resilience with hundreds of thousands of links and millions of agents. Road closures and reduction in capacities are examples of influences on the weights or removal of edges which can affect the travel time, speed, and route of agents in the transportation model. Recent advances in high-performance computing (HPC) have made modeling networks on the city scale much less computationally intensive. We introduce an open-source ABM which utilizes parallel distributed computing to enable faster convergence to large scale problems. We simulate 50,000 agents on the entire southeastern Louisiana road network and part of Mississippi as well. This demonstrates the capability to simulate both city and regional scale transportation networks near real time.

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