Evidence-based research on long-horizon asset management
How can we ensure asset owners with a focus on long-horizon investing have access to high quality research to guide best practice?
Our mission is to provide support for high quality academic research that explores this area of asset management and that facilitates decision making amongst investment practitioners.
- Research training: Through funding and supervision, promoting research excellence awards and providing research training and mentoring, we ensure early career researchers get the crucial support they need.
- Practitioner engagement: By promoting knowledge exchange between academics and practitioners, we host a variety of events to foster practitioner engagement and outreach. These take the form of live events featuring talks and presentations from global experts.
- Publications: Our published work is recognised world-wide as our associated faculty, post-doctoral staff and researchers see their work published in academic journals, books and monographs, teaching cases, reports and statements.
Our goals are to add value to the research community and to extend the research developed by this community, beyond academia into policy and practise. We aim to support our network of researchers by enhancing the resources available to them, providing forums through which to formalise and strengthen these networks and to facilitate engagement with the investment practitioners making key decisions on long-horizon investing in asset management.
Investing over the long term
This area explores traditional investment themes like asset allocation, governance, risk and return, but with a research focus on how these relate to investors with a long investment horizon.
This research explores the investment experience of long run endowments within the United States, between 1920 to present day.
A continuing study of long-run asset returns on stocks, bonds, bills, inflation, currencies and GDP since 1900.
The Centre supports the production of investment case studies designed to capture the investment experience of long-horizon investors.
Alternative assets over the long term
This area explores the long-term performance and behaviour of alternative asset classes like real estate and commodities as well as collectable assets like art, wine and coins.
Drawing on the experience of long-run real estate finance and financial history, this project makes a contribution to understanding the performance of real estate over the long-run.
Research project constructing a new dataset on exchange rates from 1919 to 1975.
Collectibles are often regarded by investors, as investments against inflation. In their Financial Analysts Journal report “Investing in emotional assets”, Professor Elroy Dimson and Dr Christopher Spaenjers review the long-term investment performance of three important categories of emotional assets.
This covers 18th century ‘structured finance’ and currency speculation in the Middle Ages, to stock market performance in the 20th and 21st centuries as well as an overview of Economist and investor John Maynard Keynes.
Since the 2008 financial crisis, there has been a resurgence of interest in economic and financial history among investment professionals.
Stock investor, currency trader and art lover – an overview of Economist and investor John Maynard Keynes, together with a video interview with Dr David Chambers, Keynes researcher, author and Reader in Finance at the Centre.
Our academic research in this area develops understanding and knowledge of how environmental, social and governmental (ESG0 factors influence investment decision-making, portfolio construction and company performance.
Materiality recognises that nonfinancial information is important in assisting investors in making sustainable investment decisions.
This empirical study builds upon the recent paper, “Active Ownership”, published as the Lead Article in the December 2015 issue of the Review of Financial Studies.
Research awards are an excellent way to identify and promote high quality research globally in areas relevant to long-horizon investors.
CEAM Research Awards
CEAM awards a research prize recognising high-quality and innovative research being undertaken by early career academic researchers globally. Priority is given to research excellence, novel insights and applicability to asset management. Five finalists are usually shortlisted to present their research and two winners are selected; the first for best research paper and the second for best presenter.
2021 Research Prize
The Best Paper Award went to Dr Lakshmi Naaraayanan and the Best Presentation Award to Dr Huan Tang at the European Investment Forum in 2021.
2019 Research Prize
The Best Paper Award went to Dr Alejandro Lopez-Lira and the Best Presentation Award to Dr Kate Suslava at the European Investment Forum in 2019.
CEAM Consortium on Asset Management Awards
In collaboration with the Financial Management Association (FMA) CEAM hosts a Consortium on Asset Management. The Consortium focuses on finance faculty who are currently working on research in asset management. Priority is given to researchers who have received their doctorates within the last five years. Five to six papers are shortlisted for presentation at the Consortium and a Best Paper Prize is awarded.
Best Paper Prize 2022
The winner of the Best Paper Prize was Π-CAPM: The Classical CAPM with Probability Weighting and Skewed Assets, presented by Joren Koëter at the 2022 Consortium on Asset Management and Fintech, co-authored with Joost Driessen and Sebastian Ebert.
Best Paper Prize 2020
The winner of the Best Paper Prize was awarded jointly to ESG Preference and Market Efficiency: Evidence from Mispricing and Institutional Trading presented by Weiming Zhang, co-authored with Jie Cao and Xintong Zhan and Sheridan Titman and Don’t Take Their Word for It: The Misclassification of Bond Mutual Funds presented by Huaizhi Chen, co-authored with Lauren Cohen and Umit Gurun. Both papers were presented at the 2020 Consortium on Asset Management.
Best Paper Award 2019
The winner of the Best Paper Prize was awarded to Bond Risk Premia with Machine Learning presented by Daniele Bianchi at the 2019 Consortium on Factor Investing, co-authored with Matthias Buechner and Andrea Tamoni.