Xiaolu Hu is an Associate Professor in Finance in the School of Economics, Finance and Marketing at RMIT University. She joined RMIT in 2018 after completing her PhD in Finance at the University. She holds a master’s degree from the PBC School of Finance at Tsinghua University and a bachelor’s degree from the Central University of Finance and Economics. Before completing her PhD, she worked as a portfolio manager and credit rating analyst at leading organisations in China.
Her research spans empirical corporate finance, asset pricing, bond markets, machine learning and Chinese capital markets. She has published more than 30 articles in journals ranked ABDC A* or A, including the Journal of Corporate Finance, Journal of Banking & Finance, The British Accounting Review and Energy Economics. She has secured more than $910,000 in research funding from internal, external and industry sources. She also serves on the editorial board of the Journal of Accounting Literature.
Xiaolu has supervised five PhD candidates to completion and currently supervises eight PhD candidates. She leads RMIT’s Financial Technology and AI Cluster, an interdisciplinary research group that connects academic research with industry practice. Through partnerships with financial institutions, she supports research collaboration at the intersection of finance, technology and AI. She is also a CFA charterholder.
Awards:
Ad-hoc reviewer for A*/A journals: Journal of Financial Econometrics, Journal of Financial and Quantitative Analysis, Journal of Corporate Finance, Energy Economics, Pacific-Basin Finance Journal, Accounting & Finance; European Financial Management; International Review of Economics and Finance, International Review of Financial Analysis, Emerging Markets Review, Finance Research Letters, Economic Modelling, Australian Journal of Management, Journal of Clean Production, Journal of Accounting Literature.
Xiaolu started teaching in 2015, covering a wide range of undergraduate and postgraduate finance courses across Melbourne and Singapore:
Credit Rating, Fixed Income, Machine Learning, Empirical Asset Pricing, FinTech, Sustainable Finance

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