The level of modeling sophistication in financial services has increased considerably over
the years. Nowadays, the complexity of financial problems and the vast amount of data …

For many real-world applications, predicting a price range is more practical and desirable
than predicting a concrete value. In this case, price prediction can be regarded as a …

In this paper, we propose an effective online portfolio selection strategy by integrating expert
opinions, which are obtained based on mean reversion and trading volume. Existing studies …

How to carry out an investment portfolio efficiently and reasonably has become a hot issue.
This study mainly addresses the problem of the instability of forecasting stock price …

Predicting the future price trends of stocks is a challenging yet intriguing problem given its
critical role to help investors make profitable decisions. In this paper, we present a …

Trend representation has been attracting more and more attention recently in portfolio
optimization (PO) via machine learning methods. It adopts concepts and phenomena from …

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

Online portfolio selection (OPS) has received increasing attention from machine learning
and quantitative finance communities. Despite their effectiveness, the pioneering OPS …

Quantitative trading takes advantage of mathematical functions for automatically making
stock or futures trading decisions. Specifically, various trading strategies that proposed by …

This article proposes a neoclassical stock market portfolio based on the principles of
dynamic response and constant adaptation to the market. The construction of a neoclassical …