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Advanced Analytics for Finance Theory and Empirics Using Big Data

Coming soon in September 2026

Authors

, Georgetown University, Washington DC

Description

Businesses are increasingly leveraging big data in financial analysis to improve decision-making, risk management, and market competitiveness, and professionals who know how to apply this data are in high demand. Designed for graduate programs and advanced undergraduate studies, this text synthesizes traditional statistics and econometrics with contemporary artificial intelligence and machine learning methods, preparing readers for the realities of modern-day financial data analysis. It studies known unknowns versus unknown unknowns and provides a systematic and objective characterization of statistical versus…

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Key features

  • Text synthesizes traditional statistics and econometrics with artificial intelligence and machine learning
  • Full datasets offered to adopters with 25 TB of data that includes all inputs, outputs and SAS code used in the book
  • Detailed calculations and stepped-out algorithms guide learners in employing statistical tools and measurements
  • Unique focus on the differences in analyzing daily data and intraday data

About the book

  • Subjects Economics,Finance and Accountancy,Statistics and Probability,Statistics for Econometrics, Finance and Insurance
  • Format: Hardback
    • Expected publication date: 30 September 2026
    • ISBN: 9781009632966
    • Dimensions (mm): 254 x 178 mm
    • Page extent: 482 pages
    • Availability: Not yet published - available from
  • Format: Paperback
    • Expected publication date: 30 September 2026
    • ISBN: 9781009632980
    • Dimensions (mm): 254 x 178 mm
    • Page extent: 482 pages
    • Availability: Not yet published - available from
  • Format: Digital
    • Expected publication date: 03 September 2026
    • ISBN: 9781009632959