NEW YORK – Investors will look in many places to find insightful data that can lead to high returns. But the actual value of that data is difficult to assess. The difficulty is that the value of data depends on who else knows it. In principle, not only would one need to know who else knows the data - but also those other traders’ portfolio size, strategy, and style. Estimating all of this directly for every market participant, is hopeless.
Columbia Business School Professor Laura Veldkamp created a first of its kind, easy-to-use metric that makes it possible to measure an investor’s private value of data, without requiring them to guess the individual characteristics of others.
The measurement tool can value data that is public or private and about one or many assets. It only requires that an investor know their own characteristics and standard public data: equity returns, and accounting variables from CRSP- Center for Research in Security Prices, and Compustat.
After applying the tool, Professor Veldkamp and co-authors NYU Stern School of Business Professor Venky Venkateswaran, MIT Sloan School of Management Professor Maryam Farboodi, and Columbia Business School doctoral candidate Dhruv Singal discovered enormous differences in how different investors value the same data.
When valuing data, who is buying seems to be even more important than exactly what they buy. That large dispersion in private values of data stands in stark contrast to the more similar valuations that different investors assign to a common set of financial assets.
As the nature of the economy continues to change and we evolve to a data driven economy, investors need new tools to understand how to measure our newfound asset. There is no one-size-fits-all approach to valuing data. However, this measuring tool enables an investor to answer the question: “What is this data worth to me?” more easily than ever before.
To learn more about the cutting-edge research being conducted at Columbia Business School, visit gsb.columbia.edu.
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