Investor sentiment indicates how far an asset value deviates from its economic
fundamentals. In this article, we review various measures of investor sentiment based on …

Academic research relies extensively on macroeconomic variables to forecast the US equity
risk premium, with relatively little attention paid to the technical indicators widely employed …

Purpose The purpose of this paper is to comprehensively review a large and heterogeneous
body of academic literature on investors' feedback trading, one of the most popular trading …

Due to the characteristics of financial time series, such as being non-linear, non-stationary
and noisy, with uncertain and hidden relationships, it is difficult to capture its non-stationary …

Technological advances in telecommunications, securities exchanges, and algorithmic
trading have facilitated a host of new investment products that resemble theme-based …

Technical analysis is the use of past price behavior and/or other market data, such as
volume, to guide trading decisions in asset markets. These decisions are often generated by …

In recent years, machine learning algorithms have been successfully employed to leverage
the potential of identifying hidden patterns of financial market behavior and, consequently …

Alternative datasets (alt-datasets) appear to be entering the financial mainstream.
Alternative data (altdata) have always occupied a crucial role in financial markets, but, until …

Grid algorithmic trading has become quite popular among traders because it shows several
advantages with respect to similar approaches. Basically, a grid trading strategy is a method …

This paper describes a new paradigm for stock trading involving the use of classical
feedback controllers which are “model free” in that they use neither parameterization nor …