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A thought-provoking and startlingly insightful reworking of the science of predictionIn 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 withinWith 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.
Financial professionals are faced with increasingly technical topics that are theoretically complicated but practically necessary in determining the trade-off between risk and return. This title presents a collection of essays that shows how to make decisions in the face of unknown forces and how to assert some control over the outcome.
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