The financial world has witnessed a skyrocketing volume of algorithmic (algo or robot)
trading since the beginning of the 2000s. Today most transactions in financial markets are …

This paper reviews the recent development and new findings of the literature on learning-to-
forecast experiments (LtFEs). In general, the stylized finding in the typical LtFEs, namely the …

The objective of our paper is to explore the impact of managers' emotional intelligence (EQ)
and cognitive ability (IQ) on firm performance. In this regard, an experimental survey on …

Do more intelligent investors take better economic decisions than less intelligent ones? Is
risk attitude, in particular risk/loss aversion, linked to cognitive ability? Does an investor's …

Using double auction market experiments with both human and agent traders, we
demonstrate that agent traders prioritising low latency often generate, sometimes perversely …

The resolution of complex problems is widely seen as the next challenge for hybrid human–
artificial intelligence (AI) teams. This paper uses experiments to assess whether there is a …

Purpose It is imperative for policymakers, financial institutions, and individual investors to
comprehend the factors that impact stock market participation, given the growing …

This paper investigates whether experiences of living in a communist regime relate to low
market earnings. We recruit North Korean refugees and measure their implicit bias against …

Agent-based computational economics (ACE) has been long considered a computational
companion to evolutionary economics (EE) or simply computational EE; its main connection …

Investor attention refers to the limited attention that investors can devote to the information
which might affect their investment decisions. Given attention is a scarce cognitive resource …