Investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. This title is suitable for researchers and graduate students in computer science, finance, statistics, mathematics, and engineering.
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 engineering.
Get Machine Learning for Financial Engineering by Gyorgy Ottucsak at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Imperial College Press and it has 262 pages.
Our digital collection is currently being curated to ensure the best possible reading experience on Werezi. We'll be launching our Ebooks platform shortly.
Your privacy, your choice
Make Werezi work for you
We use essential cookies for your cart and sign-in. With your permission, optional cookies help us understand how Werezi is used and improve your book recommendations.
Essential cookies are always active. Optional analytics stay off unless you choose Allow all.