Natural computing in computational finance

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This book continues the exploration of natural computing in computational finance, following its previous volumes. It features a collection of chapters selected through a rigorous peer-review process, showcasing advanced natural computing and agent-based methodologies applied to finance and economics. Topics covered include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination, and agent-based modeling of liquidity costs and trade strategy adaptation. The chapters present these cutting-edge applications in a manner that is accessible to a broad audience, making them relevant for academics, students, and practitioners in computational finance and economics. The diverse applications illustrate the innovative approaches being utilized in the field, ensuring that readers can engage with the material regardless of their level of expertise. This volume aims to bridge the gap between complex methodologies and practical applications, fostering a deeper understanding of how natural computing can enhance financial decision-making and economic analysis.