An overview of machine learning for asset management

Y Lee, JRJ Thompson, JH Kim, WC Kim… - The Journal of …, 2023 - pm-research.com
The Journal of Portfolio Management | Portfolio Management Research Skip to main content
Portfolio Management Research Logo Main navigation Topics All Topics Portfolio Management …

[PDF][PDF] PyPortfolioOpt: portfolio optimization in Python

RA Martin - Journal of Open Source Software, 2021 - joss.theoj.org
Portfolio construction is a critically important aspect of investment management. Even after
an investor selects a set of assets or return streams to invest in, it is a nontrivial task to …

Ethically responsible machine learning in fintech

M Rizinski, H Peshov, K Mishev, LT Chitkushev… - IEEE …, 2022 - ieeexplore.ieee.org
Rapid technological developments in the last decade have contributed to using machine
learning (ML) in various economic sectors. Financial institutions have embraced technology …

[BOOK][B] Machine learning for factor investing: R version

G Coqueret, T Guida - 2020 - taylorfrancis.com
Machine learning (ML) is progressively reshaping the fields of quantitative finance and
algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers …

[PDF][PDF] Machine learning for active portfolio management

SM Bartram, J Branke, G De Rossi… - The Journal of …, 2021 - wrap.warwick.ac.uk
Abstract Machine learning (ML) methods are attracting considerable attention among
academics in the field of finance. However, it is commonly perceived that ML has not …

[HTML][HTML] Enhancing stock market anomalies with machine learning

V Azevedo, C Hoegner - Review of Quantitative Finance and Accounting, 2023 - Springer
We examine the predictability of 299 capital market anomalies enhanced by 30 machine
learning approaches and over 250 models in a dataset with more than 500 million firm …

How can machine learning advance quantitative asset management?

D Blitz, T Hoogteijling, H Lohre… - Available at SSRN …, 2023 - papers.ssrn.com
The emerging literature suggests that machine learning (ML) is beneficial in many asset
pricing applications because of its ability to detect and exploit nonlinearities and interaction …

Asset Class Market Investment Portfolio Analysis and Tracking

PA Jadhav, C Vinotha, SK Gupta… - … and Informatics (IC3I …, 2022 - ieeexplore.ieee.org
Researchers and analysts have, for a long time, taken an interest in the expectations that
consumers have regarding stock marketing. There is a widespread perception that trying to …

Black-box model risk in finance

SN Cohen, D Snow, L Szpruch - arXiv preprint arXiv:2102.04757, 2021 - cambridge.org
Abstract Machine learning models are increasingly used in a wide variety of financial
settings. The difficulty of understanding the inner workings of these systems, combined with …

Dricorn-k: A dynamic risk correlation-driven non-parametric algorithm for online portfolio selection

S Sooklal, TL van Zyl, A Paskaramoorthy - Southern African Conference for …, 2020 - Springer
Abstract Online Portfolio Selection is regarded as a fundamental problem in Computational
Finance. Pattern-Matching methods, and the CORN-K algorithm in particular, have provided …