The Book of Alternative Data

The Book of Alternative Data

by Alexander Denev, Saeed Amen
Released July 2020
Publisher(s): Wiley
ISBN: 9781119601791

Read it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Start your free trial

Book description

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

Product information

  • Title: The Book of Alternative Data
  • Author(s): Alexander Denev, Saeed Amen
  • Release date: July 2020
  • Publisher(s): Wiley
  • ISBN: 9781119601791