Thematic Investing With Big Data: The Case of Private Equity

15 Pages Posted: 7 Feb 2022 Last revised: 13 Mar 2023

See all articles by Ludovic Phalippou

Ludovic Phalippou

University of Oxford - Said Business School

Date Written: December 21, 2021

Abstract

Using natural language processing, we score companies based on the frequency with which news articles contain both their names and terms Private Equity and Leveraged Buy-Out. An index is then created and can be updated seamlessly at high frequency, with the weights set as a function of a company exposure to this theme. We add several liquidity constraints to ensure minimal transaction costs. Even though the algorithm does not optimize on either return or correlation, this listed private equity index is highly correlated to commonly used private equity fund market indices: nearly 90% correlation with Burgiss LBO fund index. In addition, our index has similar returns as non-tradable LBO fund indices. Our approach can be generalized to many other investment themes.

Keywords: Private Equity, Thematic Investing, Big Data, Natural Langage Processing

JEL Classification: G24

Suggested Citation

Phalippou, Ludovic, Thematic Investing With Big Data: The Case of Private Equity (December 21, 2021). Available at SSRN: https://ssrn.com/abstract=3991158 or http://dx.doi.org/10.2139/ssrn.3991158

Ludovic Phalippou (Contact Author)

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 1HP
Great Britain

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
1,470
Abstract Views
3,786
Rank
24,665
PlumX Metrics