- Ph.D. in Finance, Vienna Graduate School of Finance (WU Vienna), Austria
- M.S. in Mathematics, Texas A&M University-College Station, USA
- Vordiplom in Applied Mathematics (“Wirtschaftsmathematik”), Ulm University, Germany
Matthias Buehlmaier is a principal lecturer in finance and the BBA(IBGM) program director at the University of Hong Kong (HKU).
Please visit his website www.buehlmaier.net for more comprehensive information.
He has been a visiting fellow at the University of Cambridge at Hughes Hall and Cambridge Judge Business School via the Doris Zimmern HKU-Cambridge Hughes Hall Fellowship.
His research appeared in the Review of Financial Studies (Oxford University Press) and is featured in the Harvard Law School Forum on Corporate Governance and Financial Regulation.
He is a winner of several research and teaching awards, e.g. three Faculty Outstanding Teaching Awards, the Hong Kong Asian Capital Markets Research Price from the HKSFA, and the Stephan Koren Prize, to name just a few.
The first university course worldwide (to the best of his knowledge) on the topic of text analytics and natural language processing in finance and fintech was taught by him from January to March in 2018.
He graduated with distinction from the Portfolio Management Program at the ISK Research Institute for Capital Markets, Austria, where he managed a successful stock portfolio.
In addition to his academic endeavors, he is excited about staying in contact with industry practitioners, regulators, and policy makers. Feel free to reach out if you would like to discuss topics related to his interests listed below, e.g. in relation to teaching, research, speaking engagements, consulting, applied industry projects, collaboration, or other knowledge exchange activities with business, government, or the public.
Furthermore, if you are looking for great students for internships or placements, he would be pleased to connect you with HKU Business School students.
- Investment management and investment strategies with a focus on quantitative/quantamental and data-driven approaches
- Asset pricing, market efficiency, and price discovery
- Corporate finance, in particular mergers & acquisitions (M&A)
- Financial market stability, financial "bubbles" and crises
- Data science and big data in finance
- Machine learning and artificial intelligence (AI) in finance
- Text analytics and natural language processing (NLP) in finance, e.g. textual analysis of financial media, social media, or company filings
- Fintech and wealthtech
Are Financial Constraints Priced? Evidence from Textual Analysis
Review of Financial Studies, 31 (2018): 2693-2728. (With Toni M. Whited)
Second Prize at CQAsia 2014 Academic Competition
Debt, Equity, and Information
Journal of Mathematical Economics, 50 (2014): 54-62.