Addressing Extreme Market Responses Using Secure Aggregation

An investor short sells when he/she borrows a security and sells it on the open market, planning to buy it back later at a lower price. That said, short-sellers profit from a drop in the price of the security. If the shares of the security instead increase in price, short sellers can bare large losses. Short interest stock market data, provide crucial information of short selling in the market for data mining by publishing the number of shares that have been sold short. Short interest reports are compiled and published by the regulators at a high cost. In particular, brokers and market participants must report their positions on a daily basis to Financial Industry Regulatory Authority (FINRA). Then, FINRA processes the data and provides aggregated feeds to potential clients at a high cost. Third party data providers offer the same service at a lower cost given that the brokers contribute their data to the aggregated data feeds. However, the aggregated feeds do not cover 100% of the market since the brokers are not willing to submit and trust their individual data with the data providers. Not to mention that brokers and market participants do not wish to reveal such information on a daily basis to a third party. In this paper, we show how to publish short interest stock market data using Secure Multiparty Computation: In our process, brokers and market participants submit to a data provider their short selling information, including the symbol of the security and its volume in encrypted messages on a daily basis. The messages are encrypted in a way that the data provider cannot decrypt them and therefore cannot learn about individual participants input. Then, the data provider, can compute an aggregation on the encrypted data and publish the aggregation of the volume per security. It is important to note that the individual volumes are not revealed to the data provider, only the aggregated volume is published.