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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 material http://www.eng.cam.ac.uk/~ss248/real_options. Introduction The forecast is always wrong

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Risk Management & Real Options Wrap-up

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Risk Management & Real OptionsWrap-up

Stefan Scholtes

Judge Institute of Management

University of Cambridge

MPhil Course 2004-05

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


Introduction

The forecast is always wrong

The industry valuation standard: Net Present Value

Sensitivity analysis

The system value is a shape

Value profiles and value-at-risk charts

SKILL: Using a shape calculator

CASE:Overbooking at EasyBeds

Developing valuation models

Easybeds revisited

Designing a system means sculpting its value shape

CASE: Designing a Parking Garage I

The flaw of averages: Effects of system constraints

Coping with uncertainty I: Diversification

The central limit theorem

The effect of statistical dependence

Optimising a portfolio

Coping with uncertainty II: The value of information

SKILL:Decision Tree Analysis

CASE: Market Research at E-Phone

Coping with uncertainty III: The value of flexibility

Investors vs. CEOs

CASE: Designing a Parking Garage II

The value of phasing

SKILL: Lattice valuation

Example: Valuing a drug development projects

The flaw of averages: The effect of flexibility

Hedging: Financial options analysis and Black-Scholes

Contract design in the presence of uncertainty

SKILL:Two-party scenario tree analysis

Project: Valuing a co-development contract

Wrap-up and conclusions

Course content

© Scholtes 2004


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

© Scholtes 2004


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

© Scholtes 2004


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

© Scholtes 2004


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

© Scholtes 2004


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

© Scholtes 2004


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”

© Scholtes 2004


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

© Scholtes 2004


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

© Scholtes 2004


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

© Scholtes 2004


THAT’S IT!

I HOPE YOU HAVE ENJOYED THE COURSE

© Scholtes 2004


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