Applicability of genetic algorithms for stock market prediction: A systematic survey of the last decade
Stock market is one of the attractive domains for researchers as well as academicians. It
represents highly complex non-linear fluctuating market behaviours where traders …
represents highly complex non-linear fluctuating market behaviours where traders …
A portfolio construction model based on sector analysis using Dempster-Shafer evidence theory and Granger causal network: An application to National stock …
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 …
Real-time portfolio management system utilizing machine learning techniques
There are 1641 companies listed on the National Stock Exchange of India. It is undoubtedly
infeasible for a retail investor to invest in all the stocks. It is a well-known fact that the …
infeasible for a retail investor to invest in all the stocks. It is a well-known fact that the …
Stacked deep learning structure with bidirectional long-short term memory for stock market prediction
The rapid growth of deep learning research has introduced numerous methods to solve real-
world applications. In the financial market, the stock price prediction is one of the most …
world applications. In the financial market, the stock price prediction is one of the most …
Between nonlinearities, complexity, and noises: an application on portfolio selection using kernel principal component analysis
This paper discusses the effects of introducing nonlinear interactions and noise-filtering to
the covariance matrix used in Markowitz's portfolio allocation model, evaluating the …
the covariance matrix used in Markowitz's portfolio allocation model, evaluating the …
Tactical asset allocation through random walk on stock network
Tactical asset allocation is an essential method for defining a profitable portfolio for a given
period. An analyst usually creates a tactical asset portfolio through technical analysis, a …
period. An analyst usually creates a tactical asset portfolio through technical analysis, a …
Interpolative Boolean approach for fuzzy portfolio selection
In this chapter, we present a fuzzy approach to portfolio selection based on interpolative
Boolean algebra. Interpolative Boolean algebra is a real-valued generalization of Boolean …
Boolean algebra. Interpolative Boolean algebra is a real-valued generalization of Boolean …
Stock Portfolio Health Monitoring System
S Shinde, A Ware, S Yadav, A Paul… - … System, Computing and …, 2023 - ieeexplore.ieee.org
For many years, stock market portfolio management has been successful in attracting the
interest of several academics from the domains of computer science, finance, and …
interest of several academics from the domains of computer science, finance, and …
Reinforcement Learning Driven Trading Algorithm with Optimized Stock Portfolio Management Scheme to Control Financial Risk
D Ramya - SN Computer Science, 2025 - Springer
In recent years, the application of deep learning techniques in financial markets has
achieved significant attention for develo** effective investment strategies. Traditional …
achieved significant attention for develo** effective investment strategies. Traditional …
Portfolio Optimization for Indian Mutual Funds: A Comparative Study
This paper studies the various types of Portfolio optimization techniques. It explains the
models and how they differ from each other. The main focus is creating an optimum portfolio …
models and how they differ from each other. The main focus is creating an optimum portfolio …