Bộ sách luyện thi ETS 2023 LC&RC
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Year:2023
Publisher:Cambridge University Press
Language:english
Pages:741
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.
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