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Stochastic modelling of big data in finance

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Stochastic modelling of big data in finance/ Anatoliy Swishchuk.
作者:	Swishchuk, Anatoliy.
出版者:	Boca Raton, FL :Chapman & Hall/CRC Press, : 2023.,
面頁冊數:	1 online resource.
標題:	Finance - Mathematical models. -
電子資源:	https://www.taylorfrancis.com/books/9781003265986
ISBN:	9781003265986

Stochastic modelling of big data in finance
Swishchuk, Anatoliy.

Stochastic modelling of big data in finance[electronic resource] /Anatoliy Swishchuk. - 1st ed. - Boca Raton, FL :Chapman & Hall/CRC Press,2023. - 1 online resource. - Chapman and Hall/CRC financial mathematics series. - Chapman and Hall/CRC financial mathematics series..

Includes bibliographical references and index.

"Stochastic Modelling of Big Data in Finance provides a rigorous overview and exploration of stochastic modelling of big data in finance (BDF). The book describes various stochastic models, including multivariate models, to deal with big data in finance. This includes data in high-frequency and algorithmic trading, specifically in limit order books (LOB), and shows how those models can be applied to different datasets to describe the dynamics of LOB, and to figure out which model is the best with respect to a specific data set. The results of the book may be used to also solve acquisition, liquidation and market making problems, and other optimization problems in finance. Features Self-contained book suitable for graduate students and post-doctoral fellows in financial mathematics and data science, as well as for practitioners working in the financial industry who deal with big data All results are presented visually to aid in understanding of concepts"--

ISBN: 9781003265986Subjects--Topical Terms:

557653
Finance
--Mathematical models.

LC Class. No.: HG106

Dewey Class. No.: 332.01/5195

Stochastic modelling of big data in finance
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245 1 0 $a Stochastic modelling of big data in finance $h [electronic resource] / $c Anatoliy Swishchuk.
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504 $a Includes bibliographical references and index.
520 $a "Stochastic Modelling of Big Data in Finance provides a rigorous overview and exploration of stochastic modelling of big data in finance (BDF). The book describes various stochastic models, including multivariate models, to deal with big data in finance. This includes data in high-frequency and algorithmic trading, specifically in limit order books (LOB), and shows how those models can be applied to different datasets to describe the dynamics of LOB, and to figure out which model is the best with respect to a specific data set. The results of the book may be used to also solve acquisition, liquidation and market making problems, and other optimization problems in finance. Features Self-contained book suitable for graduate students and post-doctoral fellows in financial mathematics and data science, as well as for practitioners working in the financial industry who deal with big data All results are presented visually to aid in understanding of concepts"-- $c Provided by publisher.
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