Japan POS Data

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Japan POS Data

These Point-of-Sales (POS) datasets are derived from data that provides insights into product sales across Japan, and serve as an early indicator of a company’s top-line performance.

The datasets are for consumer goods companies and retailers, and they can predict future revenue growth and revenue surprises of Japanese equities. Furthermore, a simple signal based on these datasets can also predict stock returns.

  • The POS Consumer Goods data is collected from the barcodes of products being scanned at cash registers at 6,000 retail outlets nationwide in Japan. 
  • The POS Retailer data is collected through a monthly consumer panel survey from 52,000 respondents nationwide on their consumption behaviors
  • The POS Electric Goods data tracks consumer purchases and covers all electronic devices and appliances, except for large appliances. The dataset covers 240 tickers
 
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Alan joined ExtractAlpha in 2024. He is a tenured associate professor of finance at the University of Hong Kong, where he serves as the program director of the MFFinTech, teaches classes on quantitative trading and big data in finance, and conducts research in finance specializing in big data and alternative datasets. He has published research in prestigious journals and regularly presents at financial conferences. He previously worked in technical and trading roles at DC Energy, Bridgewater Associates, Microsoft and advises several fintech startups. He received his PhD in finance from Cornell and his Bachelors from Dartmouth.

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Perry Stupp

Perry brings more than 20 years of Enterprise Software development, sales and customer engagement experience focused on Fortune 1000 customers. Prior to joining ExtractAlpha as a Technical Consultant, Perry was the founder, President and Chief Customer Officer at Solution Labs Inc. a data analytics company that specialized in the analysis of very large-scale computing infrastructures in place at some of the largest corporate data centers in the world.

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Vinesh founded ExtractAlpha in 2013 with the mission of bringing analytical rigor to the analysis and marketing of new datasets for the capital markets. Since ExtractAlpha’s merger with Estimize in early 2021, he has served as the CEO of both entities. From 1999 to 2005, Vinesh was the Director of Quantitative Research at StarMine in San Francisco, where he developed industry leading metrics of sell side analyst performance as well as successful commercial alpha signals and products based on analyst, fundamental, and other data sources. Subsequently, he developed systematic trading strategies for proprietary trading desks at Merrill Lynch and Morgan Stanley in New York. Most recently he was Executive Director at PDT Partners, a spinoff of Morgan Stanley’s premiere quant prop trading group, where in addition to research, he also applied his experience in the communication of complex quantitative concepts to investor relations. Vinesh holds an undergraduate degree from the University of Chicago and a graduate degree from the University of Cambridge, both in mathematics.

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