Guglielmo D’Amico is a professor at the University of Chieti-Pescara in Italy, with research interests in econophysics, quantitative finance and statistical models. He has published multiple papers on using quantitative methods to study topics like market returns, waiting times, inequality measurement in finance, and stock price prediction. His recent works develop software tools and statistical models aiming to quantify inequality and unpredictability in complex random systems like financial markets. The research provides insights into market behaviors and also has practical applications in areas like portfolio optimization and risk management.
Developed software Randentropy to measure inequality
In the paper “Randentropy: a software to measure inequality in random systems”, D’Amico and coauthors present the software Randentropy they developed to measure inequality and unpredictability in random sequences. It uses statistical methods like the Gini index and Shannon entropy to quantify the distribution characteristics. The software has been applied to study phenomena like order flow and price change distributions in financial markets. By measuring the inequality over time, it can reveal changes in market conditions and risk levels. The research provides a useful tool for studying complex systems and has practical applications in finance.
Proposed predictive models for stock prices using analyst ratings
In another paper titled “Feature Learning for Stock Price Prediction Shows a Significant Role of Analyst Rating”, D’Amico collaborates with Khushi to demonstrate predictive models for short-term stock price movements using machine learning methods. Their main finding is that incorporating analyst rating data significantly improves the accuracy of stock price prediction compared to just using historical prices. They test long short-term memory (LSTM) models and find analyst ratings contain useful signals on future price changes. The research shows integrating both numerical market data and human judgements can lead to better predictive analytics in finance.
Guglielmo D’Amico’s research introduces useful software tools and statistical models to measure and predict inequality, unpredictability and price changes in random systems like financial markets. His works have both scientific values in understanding market behaviors, and also practical applications in investment strategy, portfolio optimization and risk management.