VIKRAM DIXIT

As a Ph.D. candidate in Economics at Boston University, specializing in empirical macroeconomics and financial economics, I am on track to complete my degree by May 2024. My research quantifies the different types of risks faced by public firms using textual analysis of firm risk disclosures. I find that measures of shared risk factors developed from this approach can price securities in the US markets even in the presence of the Fama-French factors. 

In my research, I investigate the role of information, perceptions and sentiment in economic agents' decision-making process. I employ a variety of techniques to study these connections - including machine learning, natural language processing, and structural estimation; from a wide variety of data sources. I lean heavily on computational techniques and my background in software engineering to work with large datasets.

Teaching is sacred to me and I love interacting with curious minds. Getting people excited about ideas is one of the greatest feelings and I live for those moments. The beauty of teaching is that I get to learn too - preparing discussion materials and assignments that get across the ideas from a lesson make me learn the best ways to do so.

In my spare time, I like to bike, read or geek out on technology. I love bikes and being mechanically inclined, love maintaining both my bikes - a racing bike and my black beauty hybrid. In terms of reading, anything goes, from Calvin and Hobbes to algorithmic trading. Exploring with technology is like a trip down memory lane. I recently built my own voice-based journaling Android application, loosely based on the robot diary from the Jetsons - a classic cartoon series from my childhood. I like to use this journaling app to assess my physical and mental health using AI and machine learning in a sort-of mind hack.

My LinkedIn page is here.