000			02347nam a22002297a 4500
005			20241108130457.0
008			241108b |||||||| |||| 00| 0 eng d
020			_a9780367639723
082			_a332.6420285 _bCOQ
100			_aCoqueret, Guillaume
245			_aMachine learning for factor investing: _bpython version
260			_bCRC Press _aBoca Raton _c2023
300			_axvii, 339 p.
365			_aGBP _b68.99
490			_aChapman and Hall/CRC Financial Mathematics Series
520			_aMachine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers, notably for alpha signal generation and stocks selection. The technicality of the subject can make it hard for non-specialists to join the bandwagon, as the jargon and coding requirements may seem out-of-reach. Machine learning for factor investing: Python version bridges this gap. It provides a comprehensive tour of modern ML-based investment strategies that rely on firm characteristics. The book covers a wide array of subjects which range from economic rationales to rigorous portfolio back-testing and encompass both data processing and model interpretability. Common supervised learning algorithms such as tree models and neural networks are explained in the context of style investing and the reader can also dig into more complex techniques like autoencoder asset returns, Bayesian additive trees and causal models. All topics are illustrated with self-contained Python code samples and snippets that are applied to a large public dataset that contains over 90 predictors. The material is available online so that readers can reproduce and enhance the examples at their convenience. If you have even a basic knowledge of quantitative finance, this combination of theoretical concepts and practical illustrations will help you learn quickly and deepen your financial and technical expertise. (https://www.routledge.com/Machine-Learning-for-Factor-Investing-Python-Version/Coqueret-Guida/p/book/9780367639723?srsltid=AfmBOooIOBp6ih8X6ME3blopu09hDWDV554uI0wqDB1anEalyaBRwCZ6)
650			_aInvestments -- Data processing
650			_aMachine learning
650			_aPython (Computer program language)
700			_aGuida, Tony _911369
942			_cBK _2ddc
999			_c7510 _d7510