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Enregistrement W1871424574 · doi:10.2469/faj.v56.n3.2362

Real-Options Valuation for a Biotechnology Company

2000· article· en· W1871424574 sur OpenAlex

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Notice bibliographique

RevueFinancial Analysts Journal · 2000
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueCapital Investment and Risk Analysis
Établissements canadiensKellogg's (Canada)
Organismes subventionnairesnon disponible
Mots-clésValuation (finance)BusinessEconomicsBiotechnologyFinancial economicsActuarial scienceFinanceBiology

Résumé

récupéré en direct d'OpenAlex

Many companies in the biotechnology industry have significant valuations despite having no product revenue because their products are in early stages of development. In the past 10–15 years, investors have bid up the stock prices of companies showing promise of developing a blockbuster drug. We explain the decision-tree method and binomial-lattice method (which adds a growth option) and use them to value a biotechnology company, Agouron Pharmaceuticals, as the sum of the values of its drug-development projects. The growth option was added because the development of an initial new molecular entity (NME) is similar to purchasing a call option on the value of a subsequent NME. We compare our computed values of Agouron with actual market values at selected points in time during the development of Agouron's Viracept, a drug used to treat HIV-positive patients. Many companies in the biotechnology industry have significant valuations despite having no product revenue because their products are in the early stages of development. In the past 10–15 years, investors have bid up the stock prices of companies that show promise of developing a blockbuster drug. This phenomenon is similar to the more recent rise in stock prices of Internet start-up companies, most of which have shown losses throughout their existence.Methods used in real-options valuation can be used to assess the value investors place on companies with promise but no current revenue. The value of the company is derived from the expected profits of the company's current products and services together with the potential for growth of the company into one with many profitable products and services. Real-options valuation methods can be applied to estimate the value of individual projects, but the problem addressed in our article is how to use real-options valuation models to assess the value of a company when it is viewed as a portfolio of projects.We explain decision-tree and binomial-lattice methods and use them to the compute the value of a biotechnology company, Agouron Pharmaceutical, as the sum of the values of its current projects. We find each project's real-options value by using the two real-options valuation methods. We then compare our computed values of Agouron with the actual market values at selected points in time during the development of the company's Viracept product, a drug used to treat HIV-positive patients.Our intention is to illustrate how real-options valuation methods can be used for financial analysis. Because in our analysis we used data based on results from prior studies (primarily, industry averages), the results reflect the value of Agouron under the assumption that its situation matches that of a typical research-intensive pharmaceutical company in the 1980s and early 1990s. We discuss some of the ways in which Agouron's situation differed from that assumed by the models, which a securities analyst would no doubt understand. We found that the methods used here worked best to find the value investors were placing on Agouron when all its drugs were in early stages of development. As a drug's market potential becomes clearer in the later stages of development, securities analysts with access to more specific information than we had could improve the results of using these methods. As projects progress and new information becomes available, a financial analyst who is following a particular stock closely is likely to have better estimates of the important inputs.The real-options approach outlined here can be a powerful addition to a security analyst's toolbox. In addition, financial analysts in pharmaceutical companies can use the methods to value projects at their companies and compare the projects' relative worth for capital-budgeting purposes. Executive managers of pharmaceutical companies can use these methods to increase their understanding of the value of their projects and convey that value to investors. Finally, for academic readers, this case study provides empirical evidence of the usefulness of real-options valuation methodologies.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,158
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,039
Tête enseignante GPT0,249
Écart entre enseignants0,211 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle