MSc in Engineering Management

Course Information Package

Course Unit CodeMEM519
Course Unit DetailsMSc Engineering Management (Electives Courses) -
Number of ECTS credits allocated7
Learning Outcomes of the course unitBy the end of the course, the students should be able to:
  1. Explain the theoretical foundations of the real options approach.
  2. Identify and describe the different types of managerial investment and operational flexibility options.
  3. Implement analytic solutions for the evaluation of different investment strategies with options involved.
  4. Build scenario trees and simulations to evaluate complex multi-stage investment decisions under uncertainty in one or many dimensions.
  5. Find the optimal timing of strategies of implementing investment options or switching to alternative strategies.
  6. Apply the methodologies in challenging cases in engineering and new technologies.
  7. Explain important recent developments in real option analysis.
Mode of DeliveryFace-to-face
Recommended optional program componentsReadings:
The students are expected to read and review 4-5 papers from relevant scientific and business journals.
Course ContentsPart 1: Categorization of real options
Investment options and operational flexibility options with examples from various industries.

Part 2: Theoretical foundations
Stochastic modelling assumptions and Ito’s Lemma. Derivation of option partial differential equation through replication or equilibrium model CAPM. Risk neutral valuation of real options. 

Part3: Analytic solutions in one dimension
The option to defer. The option to abandon. Sensitivities of option formulas.
Dynamic parameters

Part 4: Numerical lattice valuation of simple options
The Cox-Ross-Rubinstein binomial model. Pricing simple options with/without optimal timing. Deriving the optimal investment trigger boundary.

Part 5: Sequential options in one dimension
Compound and growth options using the binomial lattice. Analytic compound options solutions. Interactions between sequential options.

Part 6: Multi-dimensional options
Options to exchange one asset for another. Options on the maximum or minimum of 2 stochastic variables. Analytic solutions and two dimensional lattice implementation.
Reduction of dimensionality.

Part 7: Monte Carlo simulation option valuation using Excel in one and many dimensions
Evaluation of simple call and put, evaluation of options on the maximum or minimum and options to exchange one asset for another.

Part 8: Applications with portfolios of real options
Backwards dynamic programming solutions on binomial trees when many options are involved. Applications to real cases in automobile manufacturing plant, energy, pharmaceutical R&D, telecommunications and technology.

Part 9: Other issues in real options analysis
Path-dependency and the general switching model. Options with jump-to-ruin risk.
Research and development and learning options. Valuation of firm’s equity with option to invest and default. 
Recommended and/or required reading:
  • Lenos Trigeorgis, Real Options: Managerial Flexibility and Strategy in Resource Allocation, The MIT press, 1996. ISBN10: 026220102X
  • Spiros Martzoukos and Lenos Trigeorgis, Real Options Analytic Foundations, Cambridge University Press (Forthcoming).
  • Avinash Dixit and Robert Pindyck, Investment Under Uncertainty, Princeton University Press, 1994. ISBN-10: 0691034109
  • Martha Amram and Nalin Kulatilaka, Real Options: Managing Strategic Investment in an Uncertain World, Harvard Business School Press, 1999. ISBN-10: 0875848451
  • Tom Copeland and Vladimir Antikarov, Real Options: A Practitioner’s Guide, Texere, 2001
  • Eduardo Schwartz and Lenos Trigeorgis (eds), Real Options and Investments Under Uncertainty: Classical Readings and Recent Contributions, The MIT Press, 2001.ISBN: 0262693186
  • David Shimko, Continuous Time Finance: A Primer, Blackwell Pub, 1994. ISBN-10: 1878975072
  • John Hull, Options, Futures and Other Derivatives, 6th edition, 2006, Pearson-Prentice Hall. ISBN 0131499084
Planned learning activities and teaching methodsThe course is delivered through three hours of lectures per week. Lectures also include in-class exercises to enhance the material learning process. The course also includes coursework involving computer exercises in Microsoft Excel and Visual Basic for Applications in Excel.

The course material (notes, exercises, forum, etc) is maintained on the university’s e-learning platform
Assessment methods and criteria
Midterm Exam30%
Language of instructionEnglish
Work placement(s)NO