Bonsoo Koo

Assoc Professor


Research output per year

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Personal profile


Bonsoo Koo is an Associate Professor at the Department of Econometrics and Business Statistics at Monash University. Associate Professor Koo received his PhD from the London School of Economics and Political Science. His research interests lie in a variety of economic modelling, estimation, inference and forecasting, particularly in the areas of Finance and macroeconometrics. He has a number of publications in the areas of Financial Econometrics, Finance, Econometric Theory and Superannuation. 

He has been awarded three Australian Research Council grants through its National Competitive Grants Programme and is currently working on "Forecasting under uncertainty", "Superannuation fit for the future", and "Modelling, estimation and forecasting of the yield curve dynamics". 

Research interests

Financial Econometrics, Econometric Theory, Finance, Macroeconometrics, Superannuation

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Research Output

  • 9 Article
  • 1 Conference Paper

Estimation of a nonparametric model for bond prices from cross-section and time series information

Koo, B., La Vecchia, D. & Linton, O. B., 2020, (Accepted/In press) In : Journal of Econometrics. 27 p.

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

High-dimensional predictive regression in the presence of cointegration

Koo, B., Anderson, H. M., Seo, M. H. & Yao, W., 2020, (Accepted/In press) In : Journal of Econometrics. 22 p.

Research output: Contribution to journalArticleResearchpeer-review

Personalised drawdown strategies and partial annuitisation to mitigate longevity risk

Chen, W., Minney, A., Toscas, P., Koo, B., Zhu, Z. & Pantelous, A. A., 2020, (Accepted/In press) In : Finance Research Letters. 10 p., 101644.

Research output: Contribution to journalArticleResearchpeer-review

Regularized regression for hierarchical forecasting without unbiasedness conditions

Ben Taieb, S. & Koo, B., 2019, KDD 2019: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Li, Y., Rosales, R., Terzi, E. & Karypis, G. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 1337-1347 11 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

A note on the validity of cross-validation for evaluating autoregressive time series prediction

Bergmeir, C., Hyndman, R. J. & Koo, B., 1 Apr 2018, In : Computational Statistics and Data Analysis. 120, p. 70-83 14 p.

Research output: Contribution to journalArticleResearchpeer-review

68 Citations (Scopus)