MULTI-STAGE CAPITAL INVESTMENT OPPORTUNITIES AS COMPOUND REAL Options

TLDR

Real options view corporate investment decisions as options, and multi‑stage decisions—where early upstream investments create valuable downstream opportunities—are a key class requiring accurate volatility estimation. The study investigates multi‑stage projects with market‑specific revenues but shared technology, extending the binomial lattice to model them as compound real options with multiple uncorrected underlying variables. The authors develop a compound‑options framework that estimates each opportunity’s volatility via Monte Carlo simulation and extends the binomial lattice to handle multiple uncorrected underlying variables.

Abstract

Abstract Real options provide a new and productive way to view corporate investment decisions as options. Multi-stage or sequential-investment decisions are an important class of real options with embedded managerial flexibility. These multi-stage real options involve a bundle of interrelated investment opportunities, with the early upstream opportunities creating potentially valuable discretionary downstream opportunities. We investigate a multi-stage project setting where each investment opportunity derives revenues from different markets but share common technological resources. In such a setting, one should consider the underlying asset volatility of each investment opportunity in a compound-options framework. In this paper, we extend the binomial lattice framework to model a multi-stage investment as a compound real option when several uncorrected underlying variables exist. Volatility estimation is important for implementing real option models. Therefore, we develop the theoretical framework for estimating the volatility parameter of an underlying variable using Monte Carlo simulation technique.