Student Profile: Laura Leal, graduate student, studies the ups and downs of financial markets

Wednesday, Aug 29, 2018
by Sharon Adarlo

Laura Leal, 28, doctoral candidate:

Studies: Laura Leal earned her undergraduate degree in economics at Escola Brasileira de Economia e Finanças da FGV (EBEF) in 2011 and then her master’s degree in economics at Escola de Pós-Graduação em Economia (EPGE-FGV) in 2016. Both schools are in Rio de Janeiro, Brazil, Leal’s hometown. Before starting her master’s, she worked as a macroeconomics analyst for Banco BBM in Rio de Janeiro. In 2016, she began studying for her doctoral degree in finance engineering at Princeton’s Operations Research and Financial Engineering (ORFE) department. She is also enrolled in CSML’s Graduate Certificate Program in Statistics and Machine Learning, and in the Graduate Certificate Program in Computational & Information Science at the Princeton Institute for Computational Science and Engineering.

Research: Leal is interested in how markets move and discerning patterns in the massive amount of finance data generated all over the world. That’s why she decided to enroll in CSML’s certificate program.

"I think the courses are interesting, and I am excited to deepen my knowledge on data science and machine learning for my research,” she said.

Under her advisor, Rene Carmona, the Paul Wythes ’55 Professor of Engineering and Finance, Leal delves into high frequency trading for her research. She creates statistical models that include a variety of agents, such as investors and companies, and she examines finance data in a given time period, like a day of stock trading or a month.

"When you look at markets, you can have many objectives in mind,” she said about her research. “You can simulate how agents may react to an event or predict what might happen in the future. If you want to make predictions, you obtain data from the past, study patterns within that data, and then extrapolate what may happen in the markets.” As part of her research, Leal employs the programming languages R, C++, and Python.

Leal is also interested in the growing fintech sector, where banks and other financial institutions have started applying machine learning techniques to build new products or service their clients better.

For fun: Leal likes to work out at the gym and read books on programming, history, biographies, and fiction. Leal also speaks four languages: Portuguese, English, French, and Spanish.