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Risk Management & Real Options Wrap-up Stefan Scholtes Judge Institute of Management University of Cambridge MPhil Course 2004-05 Course website with accompanying.

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Presentation on theme: "Risk Management & Real Options Wrap-up Stefan Scholtes Judge Institute of Management University of Cambridge MPhil Course 2004-05 Course website with accompanying."— Presentation transcript:

1 Risk Management & Real Options Wrap-up Stefan Scholtes Judge Institute of Management University of Cambridge MPhil Course Course website with accompanying material

2 2 September 2004 © Scholtes 2004Page 2 Course content I. Introduction II. The forecast is always wrong I. The industry valuation standard: Net Present Value II. Sensitivity analysis III. The system value is a shape I. Value profiles and value-at-risk charts II. SKILL: Using a shape calculator III. CASE: Overbooking at EasyBeds IV. Developing valuation models I. Easybeds revisited V. Designing a system means sculpting its value shape I. CASE: Designing a Parking Garage I II. The flaw of averages: Effects of system constraints VI. Coping with uncertainty I: Diversification I. The central limit theorem II. The effect of statistical dependence III. Optimising a portfolio VII. Coping with uncertainty II: The value of information I. SKILL: Decision Tree Analysis II. CASE: Market Research at E-Phone VIII. Coping with uncertainty III: The value of flexibility I. Investors vs. CEOs II. CASE: Designing a Parking Garage II III. The value of phasing IV. SKILL: Lattice valuation V. Example: Valuing a drug development projects VI. The flaw of averages: The effect of flexibility VII. Hedging: Financial options analysis and Black-Scholes IX. Contract design in the presence of uncertainty I. SKILL: Two-party scenario tree analysis II. Project: Valuing a co-development contract X. Wrap-up and conclusions

3 2 September 2004 © Scholtes 2004Page 3 Aims and objectives of the course General issue: How can we use (simple) models to help us understand uncertainty and the consequences of our decisions in an uncertain world? General objectives: This is a skills-based course. You will learn to use a computer to help you understand and improve system value Computational tools based on Excel plus a few add-ins But it is also intellectually stretching. I hope to change the way you think about uncertainty in your everyday life

4 2 September 2004 © Scholtes 2004Page 4 Examples of systems we have in mind Harbour expansion in Sidney Designing communications satellites at Motorola Terminal 5, 3 rd run-way at Heathrow Satellite-based toll collection system in Germany Sonic cruiser vs 7E7 at Boeing Fleet planning at BA Bidding for G3 telecom licenses Production sharing contract between BP and Petronas, Malaysia Drug co-development contract between Cambridge Antibody Technology and Astra Zeneca

5 2 September 2004 © Scholtes 2004Page 5 Key challenges Understanding the system value Improving the system design This course focuses on the valuation and design optimisation of systems that operate in an unpredictable dynamic environment We will mainly focus on economic valuations ($$) as system values but the general framework applies to non-monetary value measures, too E.g. service level

6 2 September 2004 © Scholtes 2004Page 6 What were we concerned with? Starting point: System value is more than a number Big Points We lack an intuitive understanding and clear communication of the effects of uncertainty on system value We work with forecasts of uncertain variables to generate a single output – the “value” – to re-assure ourselves BUT: The forecast is always wrong

7 2 September 2004 © Scholtes 2004Page 7 What were we concerned with? I. Recognising uncertainty: Values as shapes Big points Uncertainty is best represented by a SHAPE If we want to work with shapes, we need a shape calculator SKILL: LEARNED HOW TO USE A SHAPE CALCULATOR

8 2 September 2004 © Scholtes 2004Page 8 What were we concerned with? II. Developing valuation models: No right answer Big points Engineering models focus on “the right answers” - economic valuation of systems must acknowledge that THERE IS NO RIGHT VALUE Disheartened response: “Hard” modelling is useless My (and hopefully our) response: “Hard” modelling is even more important BUT we have to revise our expectations on modelling Good models test and improve our intuition about the value Good models help us communicate insight - models are vehicles for story telling Work with many valuation models – each of them is part of the “Valuation puzzle”

9 2 September 2004 © Scholtes 2004Page 9 What were we concerned with? The flaw of averages The system value calculated on the basis of average conditions is not the average system value Constraints imply that the system value calculated on the basis of average conditions OVERESTIMATES the average system value Flexibility implies that the system value calculated on the basis of average conditions UNDERESTIMATES the average system value Scenario-based analyses, such as decision trees or Monte Carlo simulation, avoid the flaw

10 2 September 2004 © Scholtes 2004Page 10 What were we concerned with? III. How to cope with uncertainty: The 3 weapons Diversification: Don’t put all your eggs in one basket Information: Gather information to narrow down the level of uncertain Flexibility: Make sure you can act to avoid losses and amplify gains as uncertainties unfold Skill: HAVE SEEN SOME SIMPLE MODELLING TEMPLATES THAT ALLOW YOU TO ANALYSE THE EFFECTS OF THESE WEAPONS

11 2 September 2004 © Scholtes 2004Page 11 What were we concerned with? IV. Whose risk is it anyway? Risk sharing in contracts Contracts are the building blocks of business Need to understand the effect of contract terms on risk exposure and opportunity sharing Skill: DEVELOPING SIMPLE MODELS FOR CONTRACT VALUATION

12 2 September 2004 © Scholtes 2004Page 12 THAT’S IT! I HOPE YOU HAVE ENJOYED THE COURSE


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