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Network theory and agent-based modeling in economics and finance

Contributor(s): Chakrabarti, Anindya S [Editor] | Pichl, Lukas [Editor] | Kaizoji, Taisei [Editor].
Material type: materialTypeLabelBookPublisher: Singapore Springer Nature 2019Description: vi, 458 p.: ill. Includes references.ISBN: 9789811383182.Subject(s): Economics - Data processing | System analysis | Network gamesDDC classification: FP 330.0285 Summary: This book presents the latest findings on network theory and agent-based modeling of economic and financial phenomena. In this context, the economy is depicted as a complex system consisting of heterogeneous agents that interact through evolving networks; the aggregate behavior of the economy arises out of billions of small-scale interactions that take place via countless economic agents. The book focuses on analytical modeling, and on the econometric and statistical analysis of the properties emerging from microscopic interactions. In particular, it highlights the latest empirical and theoretical advances, helping readers understand economic and financial networks, as well as new work on modeling behavior using rich, agent-based frameworks. Innovatively, the book combines observational and theoretical insights in the form of networks and agent-based models, both of which have proved to be extremely valuable in understanding non-linear and evolving complex systems. Given its scope, the book will capture the interest of graduate students and researchers from various disciplines (e.g. economics, computer science, physics, and applied mathematics) whose work involves the domain of complexity theory. https://www.springer.com/gp/book/9789811383182
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Books Vikram Sarabhai Library
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Books Vikram Sarabhai Library
Faculty Publication
Slot 1431 (2 Floor West Wing) Non-fiction FP 330.0285 N3-2 (Browse shelf) 2 Available 200896
Books Vikram Sarabhai Library
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Table of contents

Complexity and Emergence: A New Paradigm for Economic Modeling
Information Selection Efficiency in Networks: A Neurocognitive-Founded Agent-Based Model
Diversification by Self-reinforcement of Preferences and Change of Interaction Type
Price Distortions and Public Information: Theory, Experiments, and Simulations
Order Book on Financial Networks
Detection of Factors Influencing Market Liquidity Using an Agent-Based Simulation
Macroscopic Properties in Economic System and Their Relations
How Much Income Inequality is Fair? Nash Bargaining Solution and Its Connection to Entropy
A Limit Cycle View of Inequality
Simulated Maximum Likelihood Estimation of Agent-Based Models in Economics and Finance
Emergent Urban Morphologies in an Agent-Based Model of Housing
The Transferability of Human Capital, the Brain Drain and the Brain Gain
Is Life (or at Least Socioeconomic Aspects of It) Just Spin and Games?
An Agent-Based Model of BCVA and Systemic Risk
Additional Default Probability in Consideration of Firm’s Network
Systemic Risk: Fire-Walling Financial Systems Using Network-Based Approaches
Spectral and Network Method in Financial Time Series Analysis: A Study on Stock and Currency Market
Research on Loss Absorption of Financial Group
Knowledge-Driven Approaches for Financial News Analytics
Network-Based Policies Versus Tax Evasion
Network Games: The Cooperative Approach

This book presents the latest findings on network theory and agent-based modeling of economic and financial phenomena. In this context, the economy is depicted as a complex system consisting of heterogeneous agents that interact through evolving networks; the aggregate behavior of the economy arises out of billions of small-scale interactions that take place via countless economic agents. The book focuses on analytical modeling, and on the econometric and statistical analysis of the properties emerging from microscopic interactions. In particular, it highlights the latest empirical and theoretical advances, helping readers understand economic and financial networks, as well as new work on modeling behavior using rich, agent-based frameworks.
Innovatively, the book combines observational and theoretical insights in the form of networks and agent-based models, both of which have proved to be extremely valuable in understanding non-linear and evolving complex systems. Given its scope, the book will capture the interest of graduate students and researchers from various disciplines (e.g. economics, computer science, physics, and applied mathematics) whose work involves the domain of complexity theory.

https://www.springer.com/gp/book/9789811383182

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