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The Book of Alternative Data

Release Date: 2020/07/01
ISBN: 9781119601791
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The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management

Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject.

This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book:

  • Provides an integrated modeling approach to extract value from multiple types of datasets
  • Treats the processes needed to make alternative data signals operational
  • Helps investors and risk managers rethink how they engage with alternative datasets
  • Features practical use case studies in many different financial markets and real-world techniques
  • Describes how to avoid potential pitfalls and missteps in starting the alternative data journey
  • Explains how to integrate information from different datasets to maximize informational value

The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.

Table of Contents

  1. Cover
  2. Preface
  3. Acknowledgments
  4. PART 1: Introduction and Theory
    1. CHAPTER 1: Alternative Data: The Lay of the Land
    2. 1.1 INTRODUCTION
    3. 1.2 WHAT IS “ALTERNATIVE DATA”?
    4. 1.3 SEGMENTATION OF ALTERNATIVE DATA
    5. 1.4 THE MANY VS OF BIG DATA
    6. 1.5 WHY ALTERNATIVE DATA?
    7. 1.6 WHO IS USING ALTERNATIVE DATA?
    8. 1.7 CAPACITY OF A STRATEGY AND ALTERNATIVE DATA
    9. 1.8 ALTERNATIVE DATA DIMENSIONS
    10. 1.9 WHO ARE THE ALTERNATIVE DATA VENDORS?
    11. 1.10 USAGE OF ALTERNATIVE DATASETS ON THE BUY SIDE
    12. 1.11 CONCLUSION
    13. NOTES
    14. CHAPTER 2: The Value of Alternative Data
    15. 2.1 INTRODUCTION
    16. 2.2 THE DECAY OF INVESTMENT VALUE
    17. 2.3 DATA MARKETS
    18. 2.4 THE MONETARY VALUE OF DATA (PART I)
    19. 2.5 EVALUATING (ALTERNATIVE) DATA STRATEGIES WITH AND WITHOUT BACKTESTING
    20. 2.6 THE MONETARY VALUE OF DATA (PART II)
    21. 2.7 THE ADVANTAGES OF MATURING ALTERNATIVE DATASETS
    22. 2.8 SUMMARY
    23. NOTES
    24. CHAPTER 3: Alternative Data Risks and Challenges
    25. 3.1 LEGAL ASPECTS OF DATA
    26. 3.2 RISKS OF USING ALTERNATIVE DATA
    27. 3.3 CHALLENGES OF USING ALTERNATIVE DATA
    28. 3.4 AGGREGATING THE DATA
    29. 3.5 SUMMARY
    30. NOTES
    31. CHAPTER 4: Machine Learning Techniques
    32. 4.1. INTRODUCTION
    33. 4.2. MACHINE LEARNING: DEFINITIONS AND TECHNIQUES
    34. 4.3. WHICH TECHNIQUE TO CHOOSE?
    35. 4.4. ASSUMPTIONS AND LIMITATIONS OF THE MACHINE LEARNING TECHNIQUES
    36. 4.5. STRUCTURING IMAGES
    37. 4.6. NATURAL LANGUAGE PROCESSING (NLP)
    38. 4.7. SUMMARY
    39. NOTES
    40. CHAPTER 5: The Processes behind the Use of Alternative Data
    41. 5.1. INTRODUCTION
    42. 5.2. STEPS IN THE ALTERNATIVE DATA JOURNEY
    43. 5.3. STRUCTURING TEAMS TO USE ALTERNATIVE DATA
    44. 5.4. DATA VENDORS
    45. 5.5. SUMMARY
    46. NOTES
    47. CHAPTER 6: Factor Investing
    48. 6.1. INTRODUCTION
    49. 6.2. FACTOR MODELS
    50. 6.3. THE DIFFERENCE BETWEEN CROSS-SECTIONAL AND TIME SERIES TRADING APPROACHES
    51. 6.4. WHY FACTOR INVESTING?
    52. 6.5. SMART BETA INDICES USING ALTERNATIVE DATA INPUTS
    53. 6.6. ESG FACTORS
    54. 6.7. DIRECT AND INDIRECT PREDICTION
    55. 6.8. SUMMARY
    56. NOTES
  5. PART 2: Practical Applications
    1. CHAPTER 7: Missing Data: Background
    2. 7.1. INTRODUCTION
    3. 7.2. MISSING DATA CLASSIFICATION
    4. 7.3. LITERATURE OVERVIEW OF MISSING DATA TREATMENTS
    5. 7.4. SUMMARY
    6. NOTES
    7. CHAPTER 8: Missing Data: Case Studies
    8. 8.1. INTRODUCTION
    9. 8.2. CASE STUDY: IMPUTING MISSING VALUES IN MULTIVARIATE CREDIT DEFAULT SWAP TIME SERIES
    10. 8.3. CASE STUDY: SATELLITE IMAGES
    11. 8.4. SUMMARY
    12. 8.5. APPENDIX: GENERAL DESCRIPTION OF THE MICE PROCEDURE
    13. 8.6. APPENDIX: SOFTWARE LIBRARIES USED IN THIS CHAPTER
    14. NOTES
    15. CHAPTER 9: Outliers (Anomalies)
    16. 9.1. INTRODUCTION
    17. 9.2. OUTLIERS DEFINITION, CLASSIFICATION, AND APPROACHES TO DETECTION
    18. 9.3. TEMPORAL STRUCTURE
    19. 9.4. GLOBAL VERSUS LOCAL OUTLIERS, POINT ANOMALIES, AND MICRO-CLUSTERS
    20. 9.5. OUTLIER DETECTION PROBLEM SETUP
    21. 9.6. COMPARATIVE EVALUATION OF OUTLIER DETECTION ALGORITHMS
    22. 9.7. APPROACHES TO OUTLIER EXPLANATION
    23. 9.8. CASE STUDY: OUTLIER DETECTION ON FED COMMUNICATIONS INDEX
    24. 9.9. SUMMARY
    25. 9.10. APPENDIX
    26. NOTES
    27. CHAPTER 10: Automotive Fundamental Data
    28. 10.1. INTRODUCTION
    29. 10.2. DATA
    30. 10.3. APPROACH 1: INDIRECT APPROACH
    31. 10.4. APPROACH 2: DIRECT APPROACH
    32. 10.5. GAUSSIAN PROCESSES EXAMPLE
    33. 10.6. SUMMARY
    34. 10.7. APPENDIX
    35. NOTES
    36. CHAPTER 11: Surveys and Crowdsourced Data
    37. 11.1. INTRODUCTION
    38. 11.2. SURVEY DATA AS ALTERNATIVE DATA
    39. 11.3. THE DATA
    40. 11.4. THE PRODUCT
    41. 11.5. CASE STUDIES
    42. 11.6. SOME TECHNICAL CONSIDERATIONS ON SURVEYS
    43. 11.7. CROWDSOURCING ANALYST ESTIMATES SURVEY
    44. 11.8. ALPHA CAPTURE DATA
    45. 11.9. SUMMARY
    46. 11.10. APPENDIX
    47. NOTES
    48. CHAPTER 12: Purchasing Managers' Index
    49. 12.1. INTRODUCTION
    50. 12.2. PMI PERFORMANCE
    51. 12.3. NOWCASTING GDP GROWTH
    52. 12.4. IMPACTS ON FINANCIAL MARKETS
    53. 12.5. SUMMARY
    54. NOTES
    55. CHAPTER 13: Satellite Imagery and Aerial Photography
    56. 13.1. INTRODUCTION
    57. 13.2. FORECASTING US EXPORT GROWTH
    58. 13.3. CAR COUNTS AND EARNINGS PER SHARE FOR RETAILERS
    59. 13.4. MEASURING CHINESE PMI MANUFACTURING WITH SATELLITE DATA
    60. 13.5. SUMMARY
    61. CHAPTER 14: Location Data
    62. 14.1. INTRODUCTION
    63. 14.2. SHIPPING DATA TO TRACK CRUDE OIL SUPPLIES
    64. 14.3. MOBILE PHONE LOCATION DATA TO UNDERSTAND RETAIL ACTIVITY
    65. 14.4. TAXI RIDE DATA AND NEW YORK FED MEETINGS
    66. 14.5. CORPORATE JET LOCATION DATA AND M&A
    67. 14.6. SUMMARY
    68. NOTE
    69. CHAPTER 15: Text, Web, Social Media, and News
    70. 15.1. INTRODUCTION
    71. 15.2. COLLECTING WEB DATA
    72. 15.3. SOCIAL MEDIA
    73. 15.4. NEWS
    74. 15.5. OTHER WEB SOURCES
    75. 15.6. SUMMARY
    76. NOTES
    77. CHAPTER 16: Investor Attention
    78. 16.1. INTRODUCTION
    79. 16.2. READERSHIP OF PAYROLLS TO MEASURE INVESTOR ATTENTION
    80. 16.3. GOOGLE TRENDS DATA TO MEASURE MARKET THEMES
    81. 16.4. INVESTOPEDIA SEARCH DATA TO MEASURE INVESTOR ANXIETY
    82. 16.5. USING WIKIPEDIA TO UNDERSTAND PRICE ACTION IN CRYPTOCURRENCIES
    83. 16.6. ONLINE ATTENTION FOR COUNTRIES TO INFORM EMFX TRADING
    84. 16.7. SUMMARY
    85. CHAPTER 17: Consumer Transactions
    86. 17.1. INTRODUCTION
    87. 17.2. CREDIT AND DEBIT CARD TRANSACTION DATA
    88. 17.3. CONSUMER RECEIPTS
    89. 17.4. SUMMARY
    90. NOTE
    91. CHAPTER 18: Government, Industrial, and Corporate Data
    92. 18.1. INTRODUCTION
    93. 18.2. USING INNOVATION MEASURES TO TRADE EQUITIES
    94. 18.3. QUANTIFYING CURRENCY CRISIS RISK
    95. 18.4. MODELING CENTRAL BANK INTERVENTION IN CURRENCY MARKETS
    96. 18.5. SUMMARY
    97. CHAPTER 19: Market Data
    98. 19.1. INTRODUCTION
    99. 19.2. RELATIONSHIP BETWEEN INSTITUTIONAL FX FLOW DATA AND FX SPOT
    100. 19.3. UNDERSTANDING LIQUIDITY USING HIGH-FREQUENCY FX DATA
    101. 19.4. SUMMARY
    102. NOTE
    103. CHAPTER 20: Alternative Data in Private Markets
    104. 20.1. INTRODUCTION
    105. 20.2. DEFINING PRIVATE EQUITY AND VENTURE CAPITAL FIRMS
    106. 20.3. PRIVATE EQUITY DATASETS
    107. 20.4. UNDERSTANDING THE PERFORMANCE OF PRIVATE FIRMS
    108. 20.5. SUMMARY
  6. Conclusions
    1. SOME LAST WORDS
  7. References
  8. About the Authors
  9. Index
  10. End User License Agreement
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