risk management & real options wrap-up stefan scholtes judge institute of management university...

Risk Management & Real Options

Wrap-up

Stefan ScholtesJudge Institute of Management

University of Cambridge

MPhil Course 2004-05

Course website with accompanying material http://www.eng.cam.ac.uk/~ss248/real_options

2 September 2004 © Scholtes 2004

Course content

I. IntroductionII. The forecast is always wrong

I. The industry valuation standard: Net Present Value

II. Sensitivity analysisIII. The system value is a shape

I. Value profiles and value-at-risk charts

II. SKILL: Using a shape calculatorIII. CASE: Overbooking at EasyBeds

IV. Developing valuation modelsI. Easybeds revisited

V. Designing a system means sculpting its value shapeI. CASE: Designing a Parking Garage

III. The flaw of averages: Effects of

system constraintsVI. Coping with uncertainty I:

DiversificationI. The central limit theoremII. The effect of statistical

dependenceIII. Optimising a portfolio

VII. Coping with uncertainty II: The value of information

I. SKILL: Decision Tree Analysis

II. CASE: Market Research at E-PhoneVIII. 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


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


Examples of systems we have in mind

Harbour expansion in Sidney

Designing communications satellites at Motorola

Terminal 5, 3rd 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


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


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


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


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”


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


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


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


THAT’S IT!

I HOPE YOU HAVE ENJOYED THE COURSE

risk management & real options wrap-up stefan scholtes judge institute of management university...

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