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Record W1489537383

Real Options at Bell Canada

2003· article· en· W1489537383 on OpenAlexaboutno aff
Marcel Boyer, Éric Gravel

Bibliographic record

VenueCIRANO Project Reports · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCapital Investment and Risk Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Order (exchange)HumanitiesWelfare economicsPolitical scienceEconomicsFinancePhilosophyHistory
DOInot available

Abstract

fetched live from OpenAlex

In this report, we first develop a simplified example that illustrates the importance of considering the option ``waiting to invest'' when valuing an investment. This is followed by a short description of other options that could be embedded in an investment opportunity. In order to stress the importance of the real option mind-set in strategic planning and competitive assessment, we present three examples of possible applications of real options for evaluating investments at Bell Canada. A brief discussion follows on the importance of a real options mind-set in the telecommunications regulation context. Finally we conclude by underlining the importance of an efficient information gathering and processing framework to implement a real options framework. Two technical appendices provide more details on both the modeling and the solving techniques that are commonly used to implement real options. The complete version of this publication is confidential. Nous débutons ce rapport en développant un exemple simplifié qui illustre l'importance de valoriser l'option de retarder un investissement. Une courte description des différentes options susceptibles d'être incorporées dans un projet d'investissement est ensuite donnée. Pour illustrer l'importance d'adopter un cadre d'analyse basé sur la méthodologie des options réelles pour la planification stratégique et l'analyse concurrentielle, nous présentons trois applications possibles d'options réelles dans l'évaluation d'investissements chez Bell Canada. La nécessité de l'adoption d'un tel cadre d'analyse dans le contexte de la réglementation des télécommunications fait ensuite l'objet d'une brève discussion. Nous terminons en soulignant que le succès de la mise en pratique d'un cadre «options réelles» dépend essentiellement d'un système efficace de collecte et de traitement de l'information. Deux appendices techniques fournissent plus de détails sur les techniques de modélisation et de solution qui sont couramment utilisées pour des problèmes d'options réelles. La version complète de cette publication est confidentielle.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.217
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2003
Admission routes1
Has abstractyes

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