# Calendar

This table provides information about both the lecture (L) and recitation (R) sessions.

SES # TOPICS KEY DATES
Introduction to course
L1 Motivation: paradigm shift from best outcome to moving distribution of outcomes to right ESD.70J in parallel for 4 days
Part 1: basics, recognition of uncertainty, valuation fundamentals, and timing issues
Conventional valuation and recognition of uncertainty
L2

Discounted cash flow and present value

Criteria for valuation

R1 Valuation methods and discussion for uncertainty exercise
L3 Uncertainty recognition
L4

Choice of discount rate

Opportunity cost, weighted average cost of capital, capital asset pricing model

Application Portfolio 1 due: Topic definition
R2 Discussion of choice of discount rate and production functions
Timing of development
Basic issue: build now or later?
L5

Asphalt vs. concrete highways

Basic system model: production function, economies of scale

L6 Optimum expansion size deterministic case
R3 Exercises on production functions and economies of scale
L7

Determining economies of scale from cost function

Constrained optimization and marginal analysis

L8

Sources of flexibility

"On" systems-timing

"In" systems-timing and function

Case examples

Application Portfolio 2 due: Defining uncertainties
R4

Discussion of flexibility in application portfolio

Review of probability determination from data and Bayesian analysis

Part 2: uncertainty modeling and flexibility valuation methods
Decision analysis
L9 Uncertainty assessment
L10

Primitive models

Introduction to decision analysis

R5 Decision analysis practice
L11

Practical issues

Solutions by "folding back"

Flaw of averages

Application Portfolio 3 due: Flexibility identification
L12

Distribution of outcomes for decision analysis

Value at risk and gain, multiple value metrics

R6 Value of information and flexibility
L13 Benefits of waiting: value of information
L14 Decision analysis examples: oil platform, wind energy, silicon wafer plant, Tokyo/Haneda runway Application Portfolio 4 due: Decision analysis
R7 Past midterm solutions
L15 Mid-semester review
L16 Midterm exam
Lattice analysis
L17

Lattice model to represent uncertainty

Regression to determine trend and variability (μ and σ)

R8 Review of midterm and of regression analysis
L18 Dynamic programming: systematic solution by "folding back"
R9 Dynamic programming and valuation of lattice model
L19

Valuation of lattice by dynamic programming

Satellite case study

L20

Combining lattice and decision analysis

Case studies: aqua line tunnel

Application Portfolio 5 due: Lattice analysis of evolution of a major uncertainty
L21 Conceptual valuation and application Application Portfolio 6 due: Decision analysis using lattice
L22 Comparing decision analysis and lattice analysis
L23

Definition and analysis of "hotspots" using change propagation analysis

Path dependency