From Theory to Practice: An Academic’s Journey With Morningstar Direct

Lidia Loban, Ph.D., is an Associate Professor of Finance at the Deusto Business School in Spain who uses Morningstar Direct to bring financial concepts to life, both in the classroom and in her research.

“With Direct, I can resolve several challenges,” Loban says. “From comparing fund performance through metrics such as alpha, beta, and Sharpe ratio, to analysing portfolio composition and understanding diversification and risk.

I can also track sustainability indicators like ESG ratings and carbon intensity, which are increasingly relevant in today’s regulatory environment, such as SFDR or MiFID II, and in my academic research. The datasets in Direct enable me to evaluate risk-adjusted returns, analyse diversification, and explore sustainability dimensions.

Through Morningstar, I’ve been able to analyse European investment funds collectively, using standardised and comparable data, which is essential to maintain academic rigour. It has significantly improved the efficiency and consistency of my research and teaching, allowing me and my students to draw data-driven insights across multiple markets at once."

As a Morningstar Direct user since 2017, Loban has seen the benefits of using a streamlined investment application.

“Direct supports my teaching, research, and student projects in finance and investment analysis,” Loban says. “It has simplified my daily work by centralising reliable data and analytical tools in a single platform."

The time savings have been significant, especially when comparing funds, checking performance metrics, or accessing ESG information. Whether it’s teaching or research, I can move efficiently from data collection to analysis, which makes my work more focused and consistent.

I find the custom lists and Excel API to be especially helpful, as I can easily download and analyse portfolio compositions. These tools help me design classroom exercises built on empirical data. I also use the fund filings download feature, which offers valuable and detailed information for academic analysis.”

“The next step is to dive into the Morningstar API via Python,” Loban says. “This will enhance my professional efficiency and analytical capabilities. The integration will help me automate data extraction, expand empirical research, and offer students a more dynamic and data-driven learning experience.”

Lidia Loban has not received any cash or non-cash compensation from Morningstar, directly or indirectly, in exchange for this client success story.