Bertram Steininger

Bertram Steininger is Associate Professor of Real Estate and Finance at the Department of Real Estate and Construction Management and affiliated with the interdisciplinary research center Digital Futures (KTH, Stockholm University, and RISE).

His research sits at the intersection of mathematics, technology, and finance. He applies financial econometrics and machine learning to problems in asset pricing, investor behavior, and risk, most recently using AI and ML to recover investors' risk perception directly from their decisions (European Journal of Finance, 2024) and building empirical frameworks for tokenized and blockchain-based assets, including real estate security tokens (Journal of Banking & Finance, 2023) and their risk-return profile as a distinct asset class (Journal of Portfolio Management, 2023). His work also covers real estate asset pricing and investment vehicles (REITs, ETNs, fund structures), corporate leverage, and natural-risk pricing in housing markets, published in theJournal of Real Estate Finance and Economics,Journal of Financial Research, andJournal of Business Ethics, among others.

Selected publications

• M. Koelbl et al., "Revealing the risk perception of investors using machine learning,"European Journal of Finance, 30(17), 2024.

• J. Kreppmeier et al., "Real estate security token offerings and the secondary market: Driven by crypto hype or fundamentals?,"Journal of Banking & Finance, 154, 2023.

• B. I. Steininger, "Return-Risk Analysis of Real Estate Tokens: An Asset Class of Its Own,"Journal of Portfolio Management, 49(10), 2023.

• W. Breuer, L. D. Nguyen and B. I. Steininger, "Decomposing industry leverage: The special cases of real estate investment trusts and technology & hardware companies,"Journal of Financial Research, 46(3), 2023.

• T. A. Kroencke, F. Schindler and B. I. Steininger, "The Anatomy of Public and Private Real Estate Return Premia,"Journal of Real Estate Finance and Economics, 56(3), 2018.

FinTech & PropTech Lab

Bertram Steininger leads the FinTech & PropTech Lab at KTH, which combines mathematical modeling, machine learning, and financial economics to study how tokenization and blockchain settlement reshape financial and real estate markets. Current research lines include:

• Pricing and market structure of digital bonds and tokenized debt securities with AI

• Trading dynamics and connectedness of tokenized real-world assets, including real estate tokens and tokenized Treasuries with AI

• Governance design and rate-setting mechanisms in DeFi lending protocols with AI

• Deep-learning and PDE-based methods for nonlinear time-series, volatility, and shock-transmission modeling in digital asset markets

Team

• Seyedeh Fatemeh Mottaghi, Postdoctoral Researcher — a mathematician by training (PDE regularity theory, extremal solutions of nonlinear elliptic problems) who now applies physics-informed neural networks and deep learning to finance, including shock transmission from Ethereum to tokenized real-world assets, entropy-based network analysis of tokenized real estate, and EGARCH/structural-break volatility modeling in DeFi.

• Shufan Ma, PhD Candidate — financial econometrics and causal identification (difference-in-differences, permutation-based inference) applied to digital bond pricing, tokenized Treasury trading dynamics, and governance reform in DeFi lending protocols.

• other team members are: Anthony Haake, Miriam Betz, Heiko Leonhard

Professional standing

• Programme Director, Master's programme in Real Estate and Construction Management (TFOBM, KTH

• Managing Editor, German Journal of Real Estate Research (GJRER)

• Editor of the Journal of Real Estate Research and Journal of Property Investment & Finance

• Board Member of the European Real Estate Society (ERES)

• Member: European Real Estate Society (ERES), Real Estate, Capital Markets Network (ReCapNet), American Real Estate Society (ARES), American Real Estate and Urban Economics Association (AREUEA)