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Confidence Revisited: The Distribution of Information

November 12, 2025
By: Megan Czasonis, Mark Kritzman, Fangzhong Liu, David Turkington

By Megan Czasonis, Mark Kritzman, Fangzhong Liu, and David Turkington

 

Relevance-Based Prediction can assess a prediction’s reliability from the consistency of the information that forms it, providing a novel perspective that complements conventional measures of confidence.

 

Prediction is like a voting process. Each datapoint casts a “vote” for the unknown outcome, and the final forecast averages these diverse views. But to know how confident we should be in the average, we need transparency into the votes that went into it. Linear regression and machine learning models can’t offer this visibility because they estimate parameters and then discard the data. However, as we show in a recent paper, Relevance-Based Prediction, a model-free technique, can assess the reliability of a prediction from the distribution of information that is used to form it.

 

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Author Bios
Megan Czasonis
Megan Czasonis is a Managing Director and Head of Portfolio Management Research at State Street Associates. The Portfolio Management Research team collaborates with academic partners to develop new research on asset allocation, risk management, and investment strategy. The team delivers this research to institutional investors through indicators, advisory projects, and thought leadership pieces. Megan has co-authored various journal articles and works closely with institutional investors to develop customized solutions based on this research. Megan graduated Summa Cum Laude from Bentley University with a B.S. in Economics / Finance.
Mark Kritzman
Mark is a founding partner of State Street Associates and senior lecturer at the MIT Sloan School of Management. As the author of seven books and more than 100 research articles, Mark has pioneered new approaches to asset allocation, investment strategy, and predictive analytics. He received the James R. Vertin award from the CFA Institute recognizing the relevance and value of his research to the investment profession. Mark’s contributions provide State Street clients with novel practical methods to improve the effectiveness of predictions and investment processes.
Fangzhong Liu
Fangzhong Liu is a Quantitative Researcher on the Portfolio Management Research team at State Street Associates. His research spans a broad range of topics, including portfolio construction, asset allocation, currency management, and advanced predictive methods. He holds a Bachelor of Science in Mathematics and Economics from the University of Southern California and a Master of Finance from the Massachusetts Institute of Technology.
David Turkington
David Turkington is Senior Managing Director and Head of State Street Associates, State Street Markets’ decades-long partnership with renowned academics that produces innovative research on markets and investment strategy. David is a frequent presenter at industry conferences, has published more than 40 research articles in a range of journals, and serves on the editorial board of the Journal of Alternative Investments. He is the co-author of three books including “Asset Allocation: From Theory to Practice and Beyond” and “Prediction Revisited: The Importance of Observation.” His published research has received the 2010 Graham and Dodd Scroll Award, five Bernstein-Fabozzi/Jacobs-Levy Outstanding Article Awards, the 2013 Peter L. Bernstein Award for best paper in an Institutional Investor journal, the 2021 and 2023 Roger F. Murray First Prize for outstanding research presented at the Q Group seminars, and the 2022 and 2023 Harry Markowitz awards for best paper in the Journal of Investment Management.
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1. Peter L. Bernstein Award for Best Article in an Institutional Investor Journal in 2013; Bernstein-Fabozzi/Jacobs-Levy Award for Outstanding Article in the Journal of Portfolio Management in 2006, 2009, 2011, 2013 (2), 2014, 2015, 2016, 2021; Graham & Dodd Scroll Award for article in the Financial Analysts Journal in 2002 and 2010. Roger F. Murray First Prize for Research Presented at the Q Group Conference in 2012, 2021, 2023. Harry M. Markowitz Award for Best Paper in the Journal of Investment Management in 2022, 2023. Doriot Award for Best Private Equity Research Paper in 2022.