Portfolio optimization is one of the most important investment strategies in financial markets.
It is practically desirable for investors, especially high-frequency traders, to consider …

Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior
results in many sequence modeling tasks. The ability of Transformer to capture long-range …

A financial plan is crucial due to inflation, retirement, insurance, etc., and many people
choose stock trading as one part of their overall investment portfolio. Recently, the COVID …

In recent years, portfolio optimization is the most attracted topic among researchers. More
advanced techniques in portfolio optimization help the investors to gain more profits. The …

In recent years, online portfolio selection (OLPS) has received more and more attention from
quantitative investment and artificial intelligence communities. This paper first improves a …

Abstract Machine learning algorithms have been widely used to establish online portfolio
selection strategies. Meta-algorithm, one of the machine learning algorithms, has the …

While machine learning's role in financial trading has advanced considerably, algorithmic
transparency and explainability challenges still exist. This research enriches prior studies …

We propose a system based on the peak price involving randomness (PPR) for the portfolio
selection. In the light of the relative price forecast in the paper entitled “reweighted price …

Based on the momentum principle and adaptive learning mechanism, we design online
portfolio selection strategies, which are suitable for nonstationary financial market. Firstly, we …

Online portfolio selection is a practical problem in financial engineering and quantitative
trading. Many empirical studies show that stock performance in the market is likely to follow …