Data science has applications across the whole real estate investment stack. It certainly has application in the financial side of things, such as finding alpha and being able to more efficiently understand where there is investment opportunity. Please join Erkan Yonder, Laurentian Bank Professor of Real Estate and Finance at Concordia University - John Molson School of Business as he discusses his paper, Neighbourhood Effects, Immigration and Real Estate Valuation: A Machine Learning Approach.
- This project uses a machine learning model (LASSO) to determine the best neighborhood predictors.
- Among 105 neighborhood variables, the LASSO machine learning model detects six local immigration variables, which is important for the Canadian real estate markets.
- A higher share of external immigrants, non-permanent residents, and Arab and South Asian population in a neighborhood are shown to increase house prices.
- The model also reflects other important neighborhood effects such as local income or unemployment.
- This project also develops a benchmark score, which can help investors better assess their assets and investments using neighborhood factors. Controlling for the benchmark score increases in-sample Adjusted R-Squared from 49% to 70%, that is only one variable instead of hundreds of zip code fixed effects.
- The machine learning model framework improves prediction accuracy up to 30% compared to relative models.
The figure above reflects the net contribution of the best neighborhood predictors to house prices and compares it with the heat map of actual prices. The heat map created based on the neighborhood predictors matches the heat map of actual prices.
We hope you are able to attend this interesting discussion.
Download and read the full report that will be discussed >>> Neighborhood Effects, Immigration and Real Estate Valuation: A Machine Learning Approach
Laurentian Bank Professor of Real Estate and Finance at Concordia University - John Molson School of Business
BIO: Dr. Erkan Yonder is an assistant professor of Finance and Real Estate at the John Molson School of Business (JMSB) at Concordia University in Canada. Before joining JMSB, Erkan has worked at Ozyegin University as an assistant professor for 5 years. Erkan has received his PhD degree in Finance and Real Estate at Maastricht University in 2013. Erkan has visited the Center for Real Estate, the Massachusetts Institute of Technology (MIT), as a visiting PhD student in 2012. He also hold a second PhD degree in Economics from Middle East Technical University.
Erkan mainly work on real estate finance covering subfields such as Real Estate Investment Trusts (REITs), green buildings, commercial real estate, commercial mortgages, behavioral real estate, and sustainability. His research projects in these fields have been published in leading academic journals including Real Estate Economics, the Journal of Real Estate Finance and Economics, the Journal of Banking and Finance, the Journal of Economic Geography, and the Journal of International Money and Finance.
Dr. Andrea Chegut
Director of the MIT Real Estate Innovation Lab
BIO: Dr. Andrea Chegut, Director of the MIT Real Estate Innovation Lab, which investigates innovative products and technologies, financial value, and economic growth impacts in the built environment.
The lab is an interdisciplinary group of computational designers, urban planners, economists and statisticians that work to understand change in cities. Dr. Chegut also heads entrepreneurial research for DesignX, a venture accelerator for student and faculty firms from MIT’s School of Architecture and Planning that focuses on design, cities and the built environment. She holds the position of Research Scientist at MIT based on her academic research in asset pricing of innovative commercial and residential real estate products, entrepreneurial firm performance, and technological progress in the built environment.
Additionally, Dr. Chegut has a PhD in financial economics with a concentration in real estate and has worked at the intersection of innovation, urban economics and real estate for over a decade.
In addition to research, Dr. Chegut teaches classes on technology and innovation, finance, data science and machine learning at MIT. Prior to her work at MIT, Andrea had a career in securities asset pricing, mortgage back securitization and worked across Europe on developing asset pricing models for commercial real estate, green buildings and digital infrastructure.
Head of Real Assets at LSEG (London Stock Exchange Group)
BIO: Ali joined FTSE Russell as Head of Real Assets to head the research and index design for the real assets suite including FTSE EPRA Nareit, FTSE Nareit and FTSE Russell Infrstaucture indices. Ali also covers private equity real assets data projects within the organization.
Ali joins FTSE Russell after heading the Index & Research department at EPRA, a partner on the FTSE EPRA Nareit Index series. In his previous role Ali has worked closely with European REITs and dedicated global investors by collaborating on benchmarking requirements, research initiatives and allocation strategy. During his time at EPRA, time Ali collaborated with FTSE Russell’s Review, Governance, Product, ETP and Marketing teams.
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