[HTML][HTML] A survey of the application of graph-based approaches in stock market analysis and prediction
Graph-based approaches are revolutionizing the analysis of different real-life systems, and
the stock market is no exception. Individual stocks and stock market indices are connected …
the stock market is no exception. Individual stocks and stock market indices are connected …
Random walk through a stock network and predictive analysis for portfolio optimization
WB Freitas, JRB Junior - Expert Systems with Applications, 2023 - Elsevier
Portfolio optimization is the process that aims to make a profitable asset distribution and
minimize the risk of loss. Usually, portfolio optimization is performed by a human analyst …
minimize the risk of loss. Usually, portfolio optimization is performed by a human analyst …
[BOOK][B] Machine learning for asset managers
MML de Prado - 2020 - cambridge.org
Successful investment strategies are specific implementations of general theories. An
investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset …
investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset …
[HTML][HTML] Data analytics on graphs part III: Machine learning on graphs, from graph topology to applications
Modern data analytics applications on graphs often operate on domains where graph
topology is not known a priori, and hence its determination becomes part of the problem …
topology is not known a priori, and hence its determination becomes part of the problem …
Trends and applications of machine learning in quantitative finance
S Emerson, R Kennedy, L O'Shea… - … conference on economics …, 2019 - papers.ssrn.com
Recent advances in machine learning are finding commercial applications across many
industries, not least the finance industry. This paper focuses on applications in one of the …
industries, not least the finance industry. This paper focuses on applications in one of the …
A portfolio construction model based on sector analysis using Dempster-Shafer evidence theory and Granger causal network: An application to National stock …
K Bisht, A Kumar - Expert Systems with Applications, 2023 - Elsevier
With the emerging areas of economy, the diverse sector-based investment portfolios are
considered more significant. This paper presents an integrated approach of portfolio …
considered more significant. This paper presents an integrated approach of portfolio …
[BOOK][B] Artificial intelligence in asset management
Artificial intelligence (AI) has grown in presence in asset management and has
revolutionized the sector in many ways. It has improved portfolio management, trading, and …
revolutionized the sector in many ways. It has improved portfolio management, trading, and …
Hierarchical clustering-based asset allocation
T Raffinot - The Journal of Portfolio Management, 2017 - pm-research.com
This article proposes a hierarchical clustering-based asset allocation method, which uses
graph theory and machine learning techniques. Hierarchical clustering refers to the …
graph theory and machine learning techniques. Hierarchical clustering refers to the …
AlphaPortfolio: Direct construction through deep reinforcement learning and interpretable AI
We directly optimize the objectives of portfolio management via deep reinforcement learning-
--an alternative to conventional supervised-learning paradigms that routinely entail first-step …
--an alternative to conventional supervised-learning paradigms that routinely entail first-step …
[HTML][HTML] A generic hierarchical clustering approach for detecting bottlenecks in manufacturing
The advancements in machine learning (ML) techniques open new opportunities for
analysing production system dynamics and augmenting the domain expert's decision …
analysing production system dynamics and augmenting the domain expert's decision …