Ryan Chacon
Each week, Daniels is featuring a researcher who conducts meaningful research that impacts their field and the wider community. Learn more about their work in Q&As with the Daniels Research team and email them to nominate yourself or a colleague for a future Q&A.
Ryan Chacon is an assistant professor in the Franklin L. Burns School of Real Estate and Construction Management. He earned his undergraduate degree in finance from Florida State University and his doctorate in financial economics from the University of Missouri. Before joining the faculty at Daniels, Chacon served as an assistant professor at the University of Colorado, Colorado Springs. His research, focused on the interplay between real estate and financial markets, has been published in top-tier academic journals, such as the Journal of Financial and Quantitative Analysis, the Journal of Real Estate Finance and Economics and the Journal of Real Estate Research. As an educator, Chacon is passionate about teaching a wide range of real estate and finance courses at both the undergraduate and graduate levels.
What do you study, and how did you become interested in that area of research?
Broadly speaking, my research is at the intersection of real estate and finance. My background is in finance, but during my doctoral studies at the University of Missouri I had a mentor who focused on real estate. I really enjoyed working with him and learning about the fascinating questions that shape the built environment. My dissertation ended up being on a real estate topic, and since then I’ve slowly migrated from finance toward real estate.
Within real estate, I focus on two main areas. The first is institutional investment—how organizations like pension funds decide how much real estate to hold in their portfolios and whether to invest through private funds or public stocks, debt or equity. The second is the intersection of artificial intelligence and commercial real estate, where I’m exploring how tools like large language models can analyze everything from news sentiment to automated property appraisals.
What inspired you to pursue an academic career?
When I was earning my master’s degree in finance, most of my peers were headed to Wall Street. I wasn’t interested in that lifestyle, and I began wondering how I could use my skills and curiosity in a way that was productive but still offered some balance and freedom.
My favorite thing about this profession is exactly that freedom—the ability to work on what interests me and keep things fresh and exciting. During my master’s program I built a strong relationship with one of my faculty mentors, learned more about academia and realized that this path fit me perfectly. I’m very happy that I chose it.
Can you share a project you’re especially excited about?
Right now, I’m working with several faculty across the U.S. and one of our master’s students here at Daniels on a project that uses large language models to read and analyze news articles from the past 40 years. We’re developing predictions about what’s going to happen in the commercial real estate markets.
Our work focuses on publicly traded companies that invest in real estate, and we’ve built a trading strategy based on those predictions. It actually performs well—and it’s pretty fun to see the models work in real time.
How does your research influence your teaching?
The AI-related research I’m doing has completely reshaped my classroom. I start every class by talking about what’s happening in the market, and about half the time I also introduce new AI tools—ways students can use them to complete assignments or explore topics more deeply. Students often ask if we can have a class just on AI, but I tell them the field changes every few weeks. What really matters is learning how to stay curious, how to ask good questions and how to investigate things independently.
I also bring a lot of real-world experience to class through my role as a board member of the El Paso County Pension Fund. That perspective helps students understand how large institutional investors make real estate decisions and how theory connects with practice.
Why is your research important for society?
The part of my research that probably has the most direct societal impact is my work on pension fund investment in real estate. Pension funds are made up of everyday individuals—people working in city, state and federal government—and their financial security depends on how efficiently those funds allocate capital.
Many pension funds are critically underfunded, which is a real concern for their members. My research helps those funds think about allocation strategies that can improve their long-term financial health. It’s rewarding to know that the work I’m doing can ultimately support people’s retirements and financial well-being.
What’s next for your research?
I’m leaning further into AI-driven projects because the possibilities are expanding so quickly. This year I’ll be presenting my paper on AI and commercial real estate at MIT, and my co-author will present it at Concordia University. There’s a lot of excitement around this area, and it’s inspiring to collaborate with other researchers who are pushing the boundaries of what technology can do for real estate and finance.