In this study, the hourly directions of eight banking stocks in Borsa Istanbul were predicted
using linear-based, deep-learning (LSTM) and ensemble learning (LightGBM) models …

Numerous machine learning models have been developed to achieve the 'real-life'financial
objective of optimising the risk/return profile of investment strategies. In the current article:(a) …

With the advances in financial technology (FinTech) in recent years, the finance industry has
attempted to enhance the efficiency of their services through technology. The financial …

Trading strategies play a vital role in Algorithmic trading, a computer program that takes and
executes automated trading decisions in the stock market. The conventional wisdom is that …

This paper provides a review on machine learning methods applied to the asset
management discipline. Firstly, we describe the theoretical background of both machine …

Selecting the most suitable activation function is a critical factor in the effectiveness of deep
learning models, as it influences their learning capacity, stability, and computational …

Owing to the recent explosive expansion of deep learning, several challenging problems in
a variety of fields have been handled by deep learning, yet deep learning methods have …

In financial engineering, portfolio optimization has been of consistent interest. Portfolio
optimization is a process of modulating asset distributions to maximize expected returns and …

Purpose Machine learning (ML), and deep learning in particular, is gaining traction across a
myriad of real-life applications. Portfolio management is no exception. This paper provides a …

Selecting the most suitable activation function is a critical factor in the effectiveness of deep
learning models, as it influences their learning capacity, stability, and computational …