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by Mark P. Kritzman (Author), David Turkington (Author), Megan Czasonis (Author)
A thought-provoking and startlingly insightful reworking of the science of prediction
In Prediction Revisited: The Importance of Observation, a team of renowned experts in the field of data-driven investing delivers a ground-breaking reassessment of the delicate science of prediction for anyone who relies on data to contemplate the future. The book reveals why standard approaches to prediction based on classical statistics fail to address the complexities of social dynamics, and it provides an alternative method based on the intuitive notion of relevance.
The authors describe, both conceptually and with mathematical precision, how relevance plays a central role in forming predictions from observed experience. Moreover, they propose a new and more nuanced measure of a prediction's reliability. Prediction Revisited also offers:
- Clarifications of commonly accepted but less commonly understood notions of statistics
- Insight into the efficacy of traditional prediction models in a variety of fields
- Colorful biographical sketches of some of the key prediction scientists throughout history
- Mutually supporting conceptual and mathematical descriptions of the key insights and methods discussed within
With its strikingly fresh perspective grounded in scientific rigor, Prediction Revisited is sure to earn its place as an indispensable resource for data scientists, researchers, investors, and anyone else who aspires to predict the future from the data-driven lessons of the past.
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A thought-provoking and startlingly insightful reimagination of the science of prediction
In Prediction Revisited: The Importance of Observation, a team of renowned finance and risk experts at the top of their game describes a ground-breaking realignment of the connection between past experiences and future outcomes. The book reveals why standard approaches to prediction based on classical statistics fail to address the complexities of social dynamics, and it maps out an elegant prediction system based on a novel measure of statistical relevance.
Drawing upon information theory and an obscure yet profound mathematical equivalence, the authors describe, both conceptually and with mathematical precision, how relevance plays a central role in forming predictions. Additionally, they introduce a new and more nuanced measure of a prediction's reliability, enabling researchers to fine tune their responses to specific predictions.
Prediction Revisited also:
- Illuminates many commonly accepted but less commonly understood notions of statistics
- Reveals several valuable yet previously unrecognized mathematical equivalences
- Includes colorful biographical sketches of some of the key scientists whose contributions paved the path to relevance-based prediction
- Enables access to the mathematically minded reader as well as those who prefer an intuitive and conceptual discussion of the book's key ideas
With its strikingly fresh perspective grounded in scientific rigor, Prediction Revisited is a must-read for anyone who aspires to reach a new level of understanding and mastery of data-driven prediction.
Author Biography
MEGAN CZASONIS is Managing Director and Head of Portfolio Management Research at State Street Associates.
MARK KRITZMAN is a Founding Partner and CEO of Windham Capital Management. He is also a Founding Partner of State Street Associates and teaches a graduate course at the Massachusetts Institute of Technology.
DAVID TURKINGTON is Senior Managing Director and Head of State Street Associates.
