Funding Long Shots

49 Pages Posted: 25 Oct 2017 Last revised: 19 Nov 2017

John C. Hull

University of Toronto - Rotman School of Management

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Roger Stein

Sloan School of Management, MIT

Date Written: October 25, 2017

Abstract

We define long shots as investment projects with four features: (1) low probabilities of success; (2) long gestation lags before any cash flows are realized; (3) large required up-front investments; and (4) very large payoffs (relative to initial investment) in the unlikely event of success. Funding long shots is becoming increasingly difficult—even for high-risk investment vehicles like hedge funds and venture funds—despite the fact that some of society’s biggest challenges such as cancer, Alzheimer’s disease, global warming, and fossil-fuel depletion depend critically on the ability to undertake such investments. We investigate the possibility of improving financing for long shots by pooling them into a single portfolio that can be financed via securitized debt, and examine the conditions under which such funding mechanisms are likely to be effective.

Keywords: Capital Budgeting; Impact Investing; Venture Capital; Private Equity; Megafund; Securitization; Portfolio Theory; Research-Backed Obligation

JEL Classification: G31, G32, G24, G11

Suggested Citation

Hull, John C. and Lo, Andrew W. and Stein, Roger, Funding Long Shots (October 25, 2017). Rotman School of Management Working Paper No. 3058472. Available at SSRN: https://ssrn.com/abstract=3058472 or http://dx.doi.org/10.2139/ssrn.3058472

John C. Hull

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada
(416) 978-8615 (Phone)
416-971-3048 (Fax)

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)

HOME PAGE: http://web.mit.edu/alo/www

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Stata Center
Cambridge, MA 02142
United States

Roger Stein

Sloan School of Management, MIT ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

HOME PAGE: http://www.rogermstein.com

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