Risk and uncertainty are vital for making economic decision. An individual's propensity to make riskier decisions depends on various circumstances. Most studies on general and financial risk preference focus on analyzing the correlation between the sociodemographic and economic factors, using...

How to contemplate several types of data and generate an efficient analysis? It was possible to notice an opportunity to use Machine Learning (ML) with artificial intelligence. This study uses ML techniques and automated data extraction to focus on forecast price trends in assets of the...

This book is an experiment: How much knowledge about "using machine learning in quantitative trading" is stored and easily retrieved from the weights of ChatGPT-4? It follows a previous and similar experiment illustrated in "From Data to Trade: A Machine Learning Approach to Quantitative...

In recent years, machine learning (ML) techniques have become very popular as, in many cases, they outperform other classic methods such as regressions. However, ML techniques usually have two main drawbacks as the marginal effects of the variables of the model may a) be counterintuitive, and b)...

This work focuses on forecasting emerging technology trends in the insurance industry with the use of artificial intelligence (AI). In comparison to similar industries, the digital transformation of the insurance industry is progressing slowly. Traditional insurance organizations are struggling...

This study examines the profitability of short-selling strategies of different portfolios with varying combinations of bull and bear Leveraged Exchange-Traded Funds (LETFs). We find that while short-selling the combination of both bull and bear LETFs does not yield significant positive returns...

This paper proposes machine learning-based option pricing models that incorporate firm characteristics. We employ two semi-parametric models, one that uses machine learning to predict the implied volatility and the other to correct the pricing error of the Black-Scholes model and use 114 firm...

In a novel take on the gradual information diffusion hypothesis of Hong et al. (2007), we examine the predictive role of industries over aggregate stock market volatility. Using high frequency data for U.S. industry indexes and various heterogeneous autoregressive (HAR) type and machine learning...

Presentation of a mathematics of letters and a language of letters that will allow an artificial intelligence to learn endlessly and be able to think as we think. With the numbered letters, the information that an artificial intelligence obtains with its artificial senses will not lose its...