Several studies have been published in the last 55 years exploring technical analysis.
However, there is a lack of research that consolidates the available knowledge concerning …

This chapter surveys the state-of-art of heterogeneous agent models (HAMs) in finance
using a jointly theoretical and empirical analysis, combined with numerical analysis from the …

This paper uses data sampled at hourly and daily frequencies to predict Bitcoin returns. We
consider various advanced non-linear models based on a multitude of popular technical …

When people or computers need to make a decision, typically multiple conflicting criteria
need to be evaluated; for example, when we buy a car, we need to consider safety, cost and …

Using unique data from 12 lenders, we examine how equity lending fees respond to
demand shocks. We find that, when demand is moderate, fees are largely insensitive to …

Financial markets are complex systems influenced by many interrelated economic, political
and psychological factors and characterised by inherent nonlinearities. Recently, there have …

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term
memory. These empirical features are the main objectives of modeling efforts using (i) …

Guided by the Gervais and Odean (2001) overconfident trading hypothesis, we
comprehensively investigate the trading behavior of individual vs. institutional investors in …

Purpose This paper aims to review the theory and empirical evidence of institutional investor
behavioral biases in the lenses of behavioral finance paradigm. It surveys the research …

Machine learning in finance has been on the rise in the past decade. The applications of
machine learning have become a promising methodological advancement. The paper's …