An overview of machine learning for asset management
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Portfolio Management Research Logo Main navigation Topics All Topics Portfolio Management …
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 …
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
Rapid technological developments in the last decade have contributed to using machine
learning (ML) in various economic sectors. Financial institutions have embraced technology …
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 …
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 …
academics in the field of finance. However, it is commonly perceived that ML has not …
[HTML][HTML] Enhancing stock market anomalies with machine learning
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 …
learning approaches and over 250 models in a dataset with more than 500 million firm …
How can machine learning advance quantitative asset management?
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 …
pricing applications because of its ability to detect and exploit nonlinearities and interaction …
Asset Class Market Investment Portfolio Analysis and Tracking
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 …
consumers have regarding stock marketing. There is a widespread perception that trying to …
Black-box model risk in finance
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 …
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 …
Finance. Pattern-Matching methods, and the CORN-K algorithm in particular, have provided …