株式会社極東書店トップ商品一覧Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning. 4 vols.

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Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning.

Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning. 4 vols. 金融計量経済学・数学・ 統計学・機械学習ハンドブック 全4巻

・ISBN 978-981-12-0238-4 hard set US$ 1950.00

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電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 978-981-12-0239-1

著者・編者Lee, Cheng Few / Lee, J. C. (eds.),
出版社(World Scientific, SI)
出版年月2020
ページ数4600 pp.
言語ENG
ニュース番号<652-595 652-L4174>

解説

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.