Sudito Ghosh | PhD Economics
Graduate studies at the University of Waterloo gave Sudipto Ghosh (PhD '26) the opportunity to deepen his expertise in quantitative research while jumpstarting a career at the intersection of data analytics, financial modelling and risk management.
"I chose the University of Waterloo for its distinctive emphasis on econometrics and its strong quantitative orientation," Ghosh says.
Unlike many economics programs, Waterloo offered the combination of econometrics, applied microeconomics, financial economics and time series analysis that he was looking for. Equally important was the opportunity to work alongside faculty whose research aligned with his interests and to join a program with a strong track record of preparing graduates for quantitative careers in academia and industry.
"Waterloo offered the analytical depth and mentorship environment I needed to grow as a researcher."
Understanding risk through research
Ghosh's path to doctoral research began during his undergraduate studies in Bangladesh, where an econometrics course first introduced him to the power of quantitative analysis.
"Building a simple regression model for a class project showed me how data could explain real economic behaviour, and it shaped my interest in financial modeling and analytics."
That interest eventually led him to Canada, where he completed a master's degree in economics before working at a financial research firm in Montreal. There, he gained experience in financial modeling, data visualization and empirical analysis before deciding to pursue doctoral studies.
His PhD research focused on a key challenge in financial markets: understanding how different types of volatility influence future risk.
"My thesis studies what the literature calls 'good' and 'bad' volatility - the volatility that comes from upward versus downward price movements," he explains.
Not all volatility carries the same information. Ghosh's research shows that volatility arising from positive and negative market movements can have different implications for future risk. By modelling this decomposition of volatility, his work improves the accuracy of forecasting models and allows them to better reflect the underlying dynamics of financial markets.
"Markets don't respond to all uncertainty in the same way. By recognizing where volatility comes from, we can build forecasting models that better reflect how risk actually behaves."
Applying research beyond the classroom
During the final year of his PhD, Ghosh began working as a Manager in Data Analytics and Automation at CIBC, where he now helps build data-driven solutions for the banking sector.
"The connection between academic research and industry has been incredibly valuable."
The technical and analytical skills he developed at Waterloo translated directly into his professional work.
"My doctoral training gave me strong foundations in statistical analysis, modeling, and programming."
At the same time, industry experience strengthened his research perspective by highlighting the importance of practical applications, efficiency and decision-making.
"Working in a fast paced, data driven environment sharpened my appreciation for workflow efficiency, interpretability, and practical relevance, which ultimately made my research more grounded and applicable."
A community that fosters growth
Looking back, Ghosh credits much of his success to the faculty mentorship and collaborative research environment he found at Waterloo.
"My time at Waterloo was both meaningful and formative," he says.
He worked closely with his supervisor, Professor Dinghai Xu, while also collaborating on applied economic modeling projects with Professor Anindya Sen. Teaching econometrics labs for nearly four years gave him another opportunity to develop professionally while sharing his passion for the subject that first inspired his academic journey.
"The Waterloo community fostered collaboration, curiosity, and intellectual growth, making it an ideal environment to develop as a researcher."