Machine learning for financial engineering

Machine learning for financial engineering/ László Györfi, György Ottucsák, Harro Walk. -- London: Imperial College Press, 2012. ix, 250 pages; 24 cm
Call no. : 006.31 G997
This volume investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. Such sequential investment strategies use information collected from the market's past and determine, at the beginning of a trading period, a portfolio; that is, a way to invest the currently available capital among the assets that are available for purchase or investment. The aim is to produce a self-contained text intended for a wide audience, including researchers and graduate students in computer science, finance, statistics, mathematics, and english.
Sách có tại phòng đọc Thư viện Sư phạm Kỹ thuật Tp. Hồ Chí Minh.
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