Alternative Investing
An Academic-Quality Data Library for Practitioners
October 5, 2017
Big data is about effectively gathering and analyzing available information. At AQR, we’re known for our data-driven systematic approach to asset management, applying quantitative tools to process large volumes of information on markets, economies and companies.
Success on this front motivates us to undertake intensive empirical research efforts. As of December 1, 2014, AQR employees published more than 150 scholarly journal articles and had another 53 academic working papers under way (not to mention numerous magazine and newspaper articles), so it seems fair to say that we are pretty serious about this.
As researchers, we at AQR are also naturally curious, hungry for knowledge and understanding. This means engaging in research and constructive debate not just internally but also with our clients and top-tier investment researchers. We are firm believers that a deeper understanding leads to better (and more sustainable) ideas and innovations and that a sharing of ideas is an important aspect of this.
In this spirit, we are excited to unveil AQR’s publicly available data library. The data library contains historical and updated return series from the increasing roster of published and working papers written by AQR researchers and portfolio managers. In many cases, the articles themselves are also freely available for viewing in our main library.
In the creating and making available a serious empirical library for practitioners, we believe we are, at least partially, filling an important gap in the research community. We are proud that our research articles and data are now fully integrated. It would be gratifying should these articles and data sets, over time, become a powerful learning resource for researchers around the globe seeking insights into how markets work.
In the spirit of intellectual honesty, we ask that users please credit AQR Capital Management, LLC when using the data. Also, please use the data within the terms of use that are included in a tab within each spreadsheet.
How does it work? Each data set is associated with a specific paper. Users can view and download all related return series at once, or select a subset of series as an Excel file. Some examples of data sets include:
- The returns to value and momentum portfolios and factors from “Value and Momentum Everywhere” by Asness, Moskowitz and Pedersen (Journal of Finance, 2013)
- Low- and High-beta factors from “Betting Against Beta” by Frazzini and Pedersen (Journal of Financial Economics, 2014)
- Trend following or time series momentum factor returns from “Time Series Momentum” by Moskowitz, Ooi and Pedersen (Journal of Financial Economics, 2012).
The data, along with brief descriptions and notes on the markets covered, appear in the first tab of each file, with more details on portfolio construction and sources on the second and third tabs. More information on the data sets, which are now live and downloadable, is provided in “About the AQR Data Library.”
Finally, it is important for users of the AQR data sets to understand that all data sets provided contain the returns to portfolios described in the relevant papers, and not the live returns or backtests of AQR-specific portfolios, funds, or products.
We at AQR are very excited to introduce this new tool for engaging with our clients and the wider investment community. We hope that you will have a closer look and pass along your feedback to us.
The views and opinions expressed herein are those of the author and do not necessarily reflect the views of AQR Capital Management, LLC, its affiliates or its employees.
The information contained herein is only as current as of the date indicated, and may be superseded by subsequent market events or for other reasons. Neither the author nor AQR undertakes to advise you of any changes in the views expressed herein.
This information is not intended to, and does not relate specifically to any investment strategy or product that AQR offers. It is being provided merely to provide a framework to assist in the implementation of an investor’s own analysis and an investor’s own view on the topic discussed herein.
Past performance is no guarantee of future results.
Certain publications may have been written prior to the author being an employee of AQR.