Multi-(Horizon) Factor Investing with AI

63 Pages Posted: 12 Aug 2022 Last revised: 5 Apr 2023

See all articles by Ruslan Goyenko

Ruslan Goyenko

McGill University - Desautels Faculty of Management

Chengyu Zhang

McGill University - Desautels Faculty of Management

Date Written: August 10, 2022

Abstract

Can the backbone technology behind ChatGPT create and manage portfolios? We apply this tech-engine, adapted for finance applications, to multi-factor investing by a long-horizon investor who uses bigger that traditionally used data and takes into consideration long-term versus short-term volatility, liquidity and trading costs trade offs while maximizing expected portfolio returns. The answer is yes, as we are able to actively time factors' premium realizations while dynamically re-balancing and diversifying between factors. Moreover, the long horizon perspective is critical, as it allows for more patient trading and re-balancing needs, more strategic factor timing, and a different set of fundamental signals to rely on.

Suggested Citation

Goyenko, Ruslan and Zhang, Chengyu, Multi-(Horizon) Factor Investing with AI (August 10, 2022). Available at SSRN: https://ssrn.com/abstract=4187056 or http://dx.doi.org/10.2139/ssrn.4187056

Ruslan Goyenko (Contact Author)

McGill University - Desautels Faculty of Management ( email )

1001 Sherbrooke St. West
Montreal, Quebec H3A1G5 H3A 2M1
Canada

Chengyu Zhang

McGill University - Desautels Faculty of Management ( email )

1001 Sherbrooke St. West
Montreal, Quebec H3A1G5 H3A 2M1
Canada

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