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Full-Scale Forecast Aggregation: Probing Big Data for Powerful Forecast Signals

Full-Scale Forecast Aggregation: Probing Big Data for Powerful Forecast Signals

          
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About the Book

The field of forecast aggregation has small-scale concepts that do not work in today's world of big data. The author creates a new, full-scale method, tests it in six big data settings, and reveals the highly promising results in this book.
About the Author: For most of his career, Mark Blessington has been a sales and marketing consultant, serving many of the world's largest corporations, particularly in healthcare, financial services and general industry. His first in-depth foray into forecasting began with day-trading. During a sabbatical from consulting, he diverted large portions of his personal savings into short-term investments. He used artificial intelligence and automated algorithms to take brief (i.e., often less than a minute) long and short positions on highly volatile commodities. The ruthless world of trading taught him the value of testing before investing and ruthless tracking of forecast accuracy. He later realized there were numerous applications of trading to the world of corporate and economic forecasting. Prior to founding Mark Blessington Inc, he worked at Sibson Consulting, where he served as board member and sales effectiveness practice leader for most of his 17-year tenure there. Prior to joining Sibson, he was a consultant at The MAC Group (now Capgemini) and a General Manager at Rust-Oleum. Mark Blessington has an MBA from Northwestern in marketing, a year of study in Northwestern's Organization Behavior PhD program, and has a BS from the University of Maryland in Psychology.


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Product Details
  • ISBN-13: 9781983703980
  • Publisher: Createspace Independent Publishing Platform
  • Publisher Imprint: Createspace Independent Publishing Platform
  • Height: 254 mm
  • No of Pages: 122
  • Spine Width: 8 mm
  • Weight: 308 gr
  • ISBN-10: 1983703982
  • Publisher Date: 11 Jan 2018
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Probing Big Data for Powerful Forecast Signals
  • Width: 178 mm


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