Optimising the value of institutional real estate portfolios with machine learning

27 / 04 / 22 - 0 minute read

Traditional linear models indicate that contract rents are only 5% below estimated rents, while machine learning models identify potential for rental increases that is two to three times higher.

Author

Dr. Marcelo Cajias

Artificial intelligence (AI) and especially machine learning (ML) methods increasingly offer valuable alternatives to answer questions in real estate research and practice.

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Optimising the value of institutional real estate portfolios with machine learning

Dr. Marcelo Cajias

Head of Data Intelligence

Marcelo Cajias heads the Data Intelligence section, which is part of the Investment Strategy and Research team at PATRIZIA. In his role he is responsible for the global portfolio of analytical solutions and dashboards that support strategic investment decisions by means of observed and unobserved machine learning forecast models for various asset classes. Marcelo studied business administration at the University of Regensburg in Germany, majoring in statistics, econometrics and real estate economics. He received his doctorate for his thesis on the economic impact of sustainability on listed real estate companies.

His research has been published in various international journals and he has received the RICS Best Paper Award and the German Real Estate Research Prize.