Applied machine learning in finance

"Quantitative finance is a rich field in finance where advanced mathematical and statistical techniques are employed by both sell-side and buy-side institutions. Techniques like time series analysis, stochastic calculus, multivariate statistics, and numerical optimization are often used by &quo...

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Detalles Bibliográficos
Autor Corporativo: O'Reilly Artificial Intelligence Conference (-)
Otros Autores: Cherukuri, Chakri, on-screen presenter (onscreen presenter)
Formato: Vídeo online
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media 2019.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009822775006719
Descripción
Sumario:"Quantitative finance is a rich field in finance where advanced mathematical and statistical techniques are employed by both sell-side and buy-side institutions. Techniques like time series analysis, stochastic calculus, multivariate statistics, and numerical optimization are often used by "quants" for modeling asset prices, portfolio construction and optimization, and building automated trading strategies. Chakri Cherukuri (Bloomberg LP) demonstrates how to apply machine learning techniques in quantitative finance, covering use cases involving both structured and alternative datasets. The focus of the talk will be on promoting reproducible research (through Jupyter notebooks and interactive plots) and interpretable models."--Resource description page.
Notas:Title from resource description page (Safari, viewed November 12, 2019).
Descripción Física:1 online resource (1 streaming video file (45 min., 27 sec.)) : digital, sound, color