On arbitrage-free pricing for general data queries

Bing Rong Lin, Daniel Kifer

Research output: Contribution to journalConference articlepeer-review

51 Scopus citations


Data is a commodity. Recent research has considered the mathematical problem of setting prices for different queries over data. Ideal pricing functions need to be flexible - defined for arbitrary queries (select-project-join, aggregate, random sample, and noisy privacy-preserving queries). They should be fine-grained - a consumer should not be required to buy the entire database to get answers to simple \lowinformation" queries (such as selecting only a few tuples or aggregating over only one attribute). Similarly, a consumer may not want to pay a large amount of money, only to discover that the database is empty. Finally, pricing functions should satisfy consistency conditions such as being \arbitrage-free" { consumers should not be able to circumvent the pricing function by deducing the answer to an expensive query from a few cheap queries. Previously proposed pricing functions satisfy some of these criteria (i.e. they are defined for restricted subclasses of queries and/or use relaxed conditions for avoiding arbitrage). In this paper, we study arbitrage-free pricing functions de fined for arbitrary queries. We propose new necessary conditions for avoiding arbitrage and provide new arbitrage-free pricing functions. We also prove several negative results related to the tension between flexible pricing and avoiding arbitrage, and show how this tension often results in unreasonable prices.

Original languageEnglish (US)
Pages (from-to)757-768
Number of pages12
JournalProceedings of the VLDB Endowment
Issue number9
StatePublished - 2014
EventProceedings of the 40th International Conference on Very Large Data Bases, VLDB 2014 - Hangzhou, China
Duration: Sep 1 2014Sep 5 2014

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • General Computer Science


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