Описание: Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners,' which covers robo-advisors and price formation; 'Risk intermediation,' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy,' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theory.
Описание: -Up-to-date with cutting edge topics -Suitable for professional quants and as library reference for students of finance and financial mathematics
Описание: This book contains high-quality papers presented at the First International Forum on Financial Mathematics and Financial Technology.
Автор: Lamberton, Damien Название: Introduction to stochastic calculus applied to finance ISBN: 1584886269 ISBN-13(EAN): 9781584886266 Издательство: Taylor&Francis Рейтинг: Цена: 14545.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Maintaining the lucid style of its popular predecessor, this concise and accessible introduction covers the probabilistic techniques required to understand the most widely used financial models. Along with additional exercises, this edition presents fully updated material on stochastic volatility models and option pricing.
An innovative textbook for use in advanced undergraduate and graduate courses; accessible to students in financial mathematics, financial engineering and economics.
Introduction to the Economics and Mathematics of Financial Markets fills the longstanding need for an accessible yet serious textbook treatment of financial economics. The book provides a rigorous overview of the subject, while its flexible presentation makes it suitable for use with different levels of undergraduate and graduate students. Each chapter presents mathematical models of financial problems at three different degrees of sophistication: single-period, multi-period, and continuous-time. The single-period and multi-period models require only basic calculus and an introductory probability/statistics course, while an advanced undergraduate course in probability is helpful in understanding the continuous-time models. In this way, the material is given complete coverage at different levels; the less advanced student can stop before the more sophisticated mathematics and still be able to grasp the general principles of financial economics.
The book is divided into three parts. The first part provides an introduction to basic securities and financial market organization, the concept of interest rates, the main mathematical models, and quantitative ways to measure risks and rewards. The second part treats option pricing and hedging; here and throughout the book, the authors emphasize the Martingale or probabilistic approach. Finally, the third part examines equilibrium models -- a subject often neglected by other texts in financial mathematics, but included here because of the qualitative insight it offers into the behavior of market participants and pricing.
Автор: Ruey Tsay Название: Analysis of Financial Time Series ISBN: 0470414359 ISBN-13(EAN): 9780470414354 Издательство: Wiley Рейтинг: Цена: 19792.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Analysis of Financial Time Series, Third Edition provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described.
Автор: Capinski Название: Mathematics for Finance, 2 ed. ISBN: 0857290819 ISBN-13(EAN): 9780857290816 Издательство: Springer Рейтинг: Цена: 2620.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Mathematics for Finance: An Introduction to Financial Engineering combines financial motivation with mathematical style.
Автор: Viens Название: Handbook of Modeling High-Frequency Data in Finance ISBN: 0470876883 ISBN-13(EAN): 9780470876886 Издательство: Wiley Рейтинг: Цена: 23594.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: * Emphasis throughout the book is placed on models for high-frequency data and applications of statistics and statistical methods to tackle modeling problems within a complex system and systems of systems framework * The book is written and edited by well-known, international experts in the field.
Автор: Tsay Название: An Introduction to Analysis of Financial Data with R ISBN: 0470890819 ISBN-13(EAN): 9780470890813 Издательство: Wiley Рейтинг: Цена: 18683.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A complete set of statistical tools for beginning financial analysts from a leading authority Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data.
Описание: *Provides an introduction to the basics of financial statistics and mathematical finance.
Автор: Campolieti Название: Financial Mathematics ISBN: 1439892423 ISBN-13(EAN): 9781439892428 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Нет в наличии.
Описание: Versatile for Several Interrelated Courses at the Undergraduate and Graduate Levels Financial Mathematics: A Comprehensive Treatment provides a unified, self-contained account of the main theory and application of methods behind modern-day financial mathematics. Tested and refined through years of the authors’ teaching experiences, the book encompasses a breadth of topics, from introductory to more advanced ones. Accessible to undergraduate students in mathematics, finance, actuarial science, economics, and related quantitative areas, much of the text covers essential material for core curriculum courses on financial mathematics. Some of the more advanced topics, such as formal derivative pricing theory, stochastic calculus, Monte Carlo simulation, and numerical methods, can be used in courses at the graduate level. Researchers and practitioners in quantitative finance will also benefit from the combination of analytical and numerical methods for solving various derivative pricing problems. With an abundance of examples, problems, and fully worked out solutions, the text introduces the financial theory and relevant mathematical methods in a mathematically rigorous yet engaging way. Unlike similar texts in the field, this one presents multiple problem-solving approaches, linking related comprehensive techniques for pricing different types of financial derivatives. The book provides complete coverage of both discrete- and continuous-time financial models that form the cornerstones of financial derivative pricing theory. It also presents a self-contained introduction to stochastic calculus and martingale theory, which are key fundamental elements in quantitative finance.
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