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Physics and finance

By: Ziemann, Volker.
Series: Undergraduate Lecture Notes in Physics.Publisher: Cham : Springer, 2021Description: x, 286 p. ; ill., 25 cm.ISBN: 9783030636425.Subject(s): Mathematical physics | Probabilities | Applied mathematics | Capital market | Computer software | Engineering mathematics | Probability Theory and Stochastic Processes | Professional Computing | Finance | Theoretical, Mathematical and Computational Physics | Finance Mathematical models | Autocorrelation | Barrier option | Binary symmetric channel | Pricing Kernel | Blockchain | Co2 data analysis | Covariance matrix | Cryptography | Donkey's problem | Extreme-value theory | Green's function | Hamilton function | Koch snowflake | Lagrange multiplier | Legender transformation | Metropolis-Hastings algorithm | Robinson Crusoe model | Utility function | Wiener process | Portfolio theory | Dynamic hedgingDDC classification: 530.15 Summary: This book introduces physics students to concepts and methods of finance. Despite being perceived as quite distant from physics, finance shares a number of common methods and ideas, usually related to noise and uncertainties. Juxtaposing the key methods to applications in both physics and finance articulates both differences and common features, this gives students a deeper understanding of the underlying ideas. Moreover, they acquire a number of useful mathematical and computational tools, such as stochastic differential equations, path integrals, Monte-Carlo methods, and basic cryptology. Each chapter ends with a set of carefully designed exercises enabling readers to test their comprehension.
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Includes bibliographical references and index.

This book introduces physics students to concepts and methods of finance. Despite being perceived as quite distant from physics, finance shares a number of common methods and ideas, usually related to noise and uncertainties. Juxtaposing the key methods to applications in both physics and finance articulates both differences and common features, this gives students a deeper understanding of the underlying ideas. Moreover, they acquire a number of useful mathematical and computational tools, such as stochastic differential equations, path integrals, Monte-Carlo methods, and basic cryptology. Each chapter ends with a set of carefully designed exercises enabling readers to test their comprehension.

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