Robert Weant

Robert Weant is a Quantitative Analyst at Hubbard Decision Research (HDR) who has quickly become a skilled practitioner of Applied Information Economics (AIE). With expertise in developing specific algorithms and unique regression models, he has enhanced methods used by AIE and increased the effectiveness of Monte Carlo simulations we build for our clients.

Prior to joining HDR, Robert graduated with an M.S. in Economics from the University of North Carolina Charlotte and an M.S.B.A. in Applied Finance from Copenhagen Business School located in Denmark. While pursuing higher education he worked in Business Intelligence and focused his academic efforts on quantitatively testing financial portfolios to optimize risk-adjusted returns. In addition to this, he also led a team of Economics students to successfully compete in a monetary policy competition hosted by the Federal Reserve to become one of the top 5 finalists in the country. Through both his work in academia and his career, he has developed a strong passion for handling data sets and applying statistical methods to them to enhance one’s comprehension of the world we live in.

Robert’s technical skills in Excel, Power BI, and Python have led him to skillfully streamline model deployment for our clients and automate workload. Having gained significant international experience from living in three countries (USA, Denmark, and China), he has developed the ability to effectively communicate with people regardless of their background and help them understand how quantitative methods can improve their decision-making.