Project valuation in the pharmaceutical industry: a comparison of least‐squares Monte Carlo real option valuation and conventional approaches

Abstract

Least‐squares Monte Carlo simulation (LSM) is a promising new technique for valuing real options that has received little or no attention in the pharmaceutical industry. This study demonstrates that LSM can handle complex valuation situations with multiple uncertainties and compounded American‐type options. The limited application of real option valuation (ROV) in the pharmaceutical industry is remarkable, given the importance of accurate project valuation in an industry that requires large investments in high‐risk projects with long pay‐back periods, which is furthermore suffering from ever‐increasing development costs and shrinking profit margins. The LSM model developed in this study is constructed as an extension of a discounted cash flow model that should be familiar to economists active in the pharmaceutical industry. A number of pharmaceutical projects have been evaluated using LSM ROV, binominal real option valuation and expected net present value techniques. The different results yielded by these methods are explained in terms of differences in risking assumptions and ability to capture the value of flexibility. The analysis provides a framework to introduce the basic concepts of real option pricing to a non‐specialist audience. The LSM model illustrates the potential for real‐life commercial assessment as the versatility of the technique allows for an easy customisation to specific business problems.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 35 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.