Prediction Revisited - The Importance of Observation

Informationen zum Autor 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. Klappentext 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. Zusammenfassung 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. Inhaltsverzeichnis Timeline of Innovations ix Essential Concepts xi Preface xv 1 Introduction 1 Relevance 2 Informativeness 3 Similarity 4 Roadmap 4 2 Observing Information 7 Observing Information Conceptually 7 Central Tendency 8 Spread 9 Information Theory 10 The Strong Pull of Normality 14 A Constant of Convenience 17 Key Takeaways 18 Observing...

List of contents

Timeline of Innovations ix
 
Essential Concepts xi
 
Preface xv
 
1 Introduction 1
 
Relevance 2
 
Informativeness 3
 
Similarity 4
 
Roadmap 4
 
2 Observing Information 7
 
Observing Information Conceptually 7
 
Central Tendency 8
 
Spread 9
 
Information Theory 10
 
The Strong Pull of Normality 14
 
A Constant of Convenience 17
 
Key Takeaways 18
 
Observing Information Mathematically 20
 
Average 20
 
Spread 21
 
Information Distance 24
 
Observing Information Applied 26
 
Appendix 2.1: On the Inflection Point of the Normal Distribution 32
 
References 39
 
3 Co-occurrence 41
 
Co-occurrence Conceptually 41
 
Correlation as an Information-Weighted Average of Co-occurrence 46
 
Pairs of Pairs 49
 
Across Many Attributes 50
 
Key Takeaways 52
 
Co-occurrence Mathematically 54
 
The Covariance Matrix 58
 
Co-occurrence Applied 59
 
References 66
 
4 Relevance 67
 
Relevance Conceptually 67
 
Informativeness 68
 
Similarity 72
 
Relevance and Prediction 73
 
How Much Have You Regressed? 74
 
Partial Sample Regression 76
 
Asymmetry 80
 
Sensitivity 86
 
Memory and Bias 87
 
Key Takeaways 88
 
Relevance Mathematically 90
 
Prediction 95
 
Equivalence to Linear Regression 97
 
Partial Sample Regression 100
 
Asymmetry 102
 
Relevance Applied 107
 
Appendix 4.1: Predicting Binary Outcomes 114
 
Predicting Binary Outcomes Conceptually 114
 
Predicting Binary Outcomes Mathematically 116
 
References 121
 
5 Fit 123
 
Fit Conceptually 123
 
Failing Gracefully 125
 
Why Fit Varies 126
 
Avoiding Bias 129
 
Precision 130
 
Focus 133
 
Key Takeaways 134
 
Fit Mathematically 136
 
Components of Fit 138
 
Precision 139
 
Fit Applied 143
 
6 Reliability 149
 
Reliability Conceptually 149
 
Key Takeaways 153
 
Reliability Mathematically 155
 
Reliability Applied 163
 
References 168
 
7 Toward Complexity 169
 
Toward Complexity Conceptually 169
 
Learning by Example 170
 
Expanding on Relevance 171
 
Key Takeaways 175
 
Toward Complexity Mathematically 177
 
Complexity Applied 183
 
References 183
 
8 Foundations of Relevance 185
 
Observations and Relevance: A Brief Review of the Main Insights 186
 
Spread 187
 
Co-occurrence 187
 
Relevance 188
 
Asymmetry 188
 
Fit and Reliability 189
 
Partial Sample Regression and Machine Learning Algorithms 189
 
Abraham de Moivre (1667-1754) 190
 
Pierre-Simon Laplace (1749-1827) 192
 
Carl Friedrich Gauss (1777-1853) 193
 
Francis Galton (1822-1911) 195
 
Karl Pearson (1857-1936) 197
 
Ronald Fisher (1890-1962) 199
 
Prasanta Chandra Mahalanobis (1893-1972) 200
 
Claude Shannon (1916-2001) 202
 
References 206
 
Concluding Thoughts 209
 
Perspective 209
 
Insights 210
 
Prescriptions 210
 
Index 211

Product details

• Authors: Megan Czasonis, Mark P Kritzman, Mark P. Kritzman, Mark P. (Windham Capital Management Bost Kritzman, Kritzman Mark P., David Turkington
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 14.07.2022
• EAN: 9781119895589
• ISBN: 978-1-119-89558-9
• No. of pages: 240
• Subjects: Social sciences, law, business > Business > Management; Prognose, Entscheidungsfindung, Business & management, Wirtschaft u. Management, Theorie der Entscheidungsfindung, Decision Sciences