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What’s new in the 2nd Edition     Optional Stochastic Analysis on non-“usual” filtrations: the first textbook presentation of optional processes on stochastic bases beyond the standard right-continuous, complete setting, with an accompanying optional stochastic calculus. Optional SDEs and stochastic exponentials\/logarithms: existence-uniqueness theory and product\/inverse rules, with financial modeling worked out in this optional-semimartingale framework. New applications: Stochastic Regression Analysis and Risk Theory, showing how optional tools yield estimation results and ruin-probability bounds in general settings. Expanded exercises with solutions: a substantially enlarged Supplement (Ch. 15) featuring problems that reinforce both core theory and applications.   Designed for senior undergraduates, graduate students, and instructors, the book also serves researchers and practitioners who need a concise, example-driven route from measure-theoretic probability to the techniques used in finance, statistics, and risk modeling. Abundant worked examples and a comprehensive set of problems—with hints and solutions—make it ideal for self study or course adoption.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":53483909415185,"sku":"NGR9783032204813","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783032204813.jpg?v=1777615005"},{"product_id":"numerical-analysis-a-graduate-course-book-david-e-stewart-9783031081231","title":"Numerical Analysis: A Graduate Course","description":"This book aims to introduce graduate students to the many applications of numerical computation, explaining in detail both how and why the included methods work in practice. The text addresses numerical analysis as a middle ground between practice and theory, addressing both the abstract mathematical analysis and applied computation and programming models instrumental to the field. While the text uses pseudocode, Matlab and Julia codes are available online for students to use, and to demonstrate implementation techniques. The textbook also emphasizes multivariate problems alongside single-variable problems and deals with topics in randomness, including stochastic differential equations and randomized algorithms, and topics in optimization and approximation relevant to machine learning. Ultimately, it seeks to clarify issues in numerical analysis in the context of applications, and presenting accessible methods to students in mathematics and data science.","brand":"WoB","offers":[{"title":"- \/ - \/ INTERNAL","offer_id":53649429496081,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":53649429528849,"sku":"NIN9783031081231","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783031081231.jpg?v=1781153431"}],"url":"https:\/\/www.worldofbooks.com\/en-gb\/collections\/cms-caims-books-in-mathematics-book-series.oembed","provider":"World of Books ","version":"1.0","type":"link"}