{"product_id":"natural-computing-in-computational-finance-volume-4-9783642233357","title":"Natural Computing in Computational Finance, Volume 4","description":"\u003cp\u003e • Author(s): Anthony Brabazon | Michael O'Neill | Dietmar Maringer\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Finance - General\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis book follows on from Natural Computing in Computational Finance Volumes I, II and III. As in the previous volumes of this series, the book consists of a series of chapters each of \u003c\/p\u003e\u003cp\u003ewhich was selected following a rigorous, peer-reviewed, selection process. The chapters illustrate the application of a range of cutting-edge natural computing and agent-based methodologies in computational finance and economics. \u003c\/p\u003e\u003cp\u003eThe applications explored 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. While describing cutting edge applications, the chapters are \u003c\/p\u003e\u003cp\u003ewritten so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. \u003c\/p\u003e\u003cp\u003ewhich was selected following a rigorous, peer-reviewed, selection process. The chapters illustrate the application of a range of cutting-edge natural computing and agent-based methodologies in computational finance and economics. \u003c\/p\u003e\u003cp\u003eThe applications explored 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. While describing cutting edge applications, the chapters are \u003c\/p\u003e\u003cp\u003ewritten so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. \u003c\/p\u003e\u003cp\u003eThe applications explored 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. While describing cutting edge applications, the chapters are \u003c\/p\u003e\u003cp\u003ewritten so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. \u003c\/p\u003e\u003cp\u003ewritten so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. \u003c\/p\u003e","brand":"Springer","offers":[{"title":"Hardcover","offer_id":47600193601687,"sku":"9783642233357","price":17322.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783642233357.webp?v=1775007405","url":"https:\/\/atlanticbooks.com\/products\/natural-computing-in-computational-finance-volume-4-9783642233357","provider":"Atlantic Books","version":"1.0","type":"link"}