Over
the years we've collected our readers' most frequently
asked questions. The inquiries focus on the nature of
real options and specific industry applications. Here
are some highlights.
A
First Look At Real Options
Explain the
title of your book.
Tell me more about options.
Why are options so important?
You seem to be suggesting that uncertainty
can be a good thing.
Tell me more about real options.
Is this book about strategy or finance?
How do financial options relate to real
options?
Do you have to be a rocket scientist
to understand all this?
Do the financial markets know about real
options?
Who should be using real options thinking?
Where have these ideas been used?
We are already using decision analysis
in our firm. Will switching to the real options approach
change any decisions we make?
Where can I learn more about the option
valuation breakthrough?
Thinking
Through the Valuation Model
What is an
underlying asset?
Whatinformation is needed to value an
option?
What information is NOT needed to value
an option?
Why doesn't DCF work for flexible decisionmaking?
How does the real options approach compare
to the alternatives?
Getting
the Numbers
When can the
BlackScholes Equation be used to value real options?
How about the binomial method?
Tell me more about private risk.
Is the choice between a lognormal and
a meanreverting process for the underlying asset important?
If you increase volatility, the value
of the option will increase. However, increasing volatility
also decreases the discount rate, lowering the value
of the project. What's going on?
I've collected the data and calculated
some historical volatilities for three firms I'm studying.
These results are very different than the option price
volatility information available at the CBOE web site.
Which should I use?
Do I need to define a corporate utility
function to include private risk in my calculations?
Do corporate utility functions differ?
How do I get taxes into a real option
valuation?
Industry
Applications
Utilities
Water:
Has the
real options approach been used to value infrastructure
investments in the water industry?
Electricity:
In the
summer of 1998 wholesale electricity prices spiked from
$20MWh to $5,000/MWh. What was going on? Did the market
misvalue the futures prices?
In chapter 16, you do not mention the
volatility of revenue, which is dependent on the price
of eelctricity. Isn't the volatility important?
R&D,
Product Development and Technology
Pharmaceutical R&D:
What
is the best approach to valuing a drug in development,
during clinical trials?
Negative
value to R&D:
Are there
applications in which more research and more information
leads to a liability instead of an asset?
Technology
licenses:
In
a Harvard Business Review article (1984), W. Kester
defines proprietary options (those owned by your firm)
and shared options (those also held by your competitors.)
We've got some good technology, but it is not exclusive.
How do we "haircut" the value of our technologybased
options to get the correct value?
New
applications
Filmmaking:
Has the
real options approach been applied to valuation and
strategy in the film industry?
Online
Learning:
What's
the real options perspective on the following question:
Should a state university expand by investing a large
amount of money in buildings, or putting everything
on the web and presenting a webbased education?
A
First Look At Real Options
Explain
the title of your book.
When a company invests in a physical asset, they're
also acquiring options  opportunities to make decisions
in the future, based on the outcome of things that are
uncertain today. We call these real options to
distinguish them from option contracts traded in the
financial markets. Example: the value of a new manufacturing
plant includes the option to expand if sales take off
and option to abandon if sales die.
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Tell
me more about options.
In common use, the word option is used
to suggest alternatives or choices. For real and financial
options, the word has a different meaning.
An
option is the right, but not the obligation,
to take an action. For example, an option contract is
the right to buy (or sell) a stock at a date specified
in the future. Options are valuable when there is uncertainty.
For example, an option contract traded on the financial
exchanges will be exercised (used) only if the
price of the stock on that date exceeds the specified
price. The value of the contract comes from this upside
potential. Real options are created by investment 
today's investment creates the right to make a decision
later. The value of the investment includes these real
options.
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Why
are options so important?
We live in a world of uncertainty, there's a
lot of value in having options to change your mind or
update your strategy in the future. Using an options
approach a company can change how it faces uncertainty.
Options help to limit its losses from bad outcomes and
increase the payoff from good outcomes.
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You seem to be suggesting that
uncertainty can be a good thing.
If you have your options in place, an
increase in uncertainty will raise the value of your
assets. Here's an example. Suppose you just bought rights
to a new technology for $5 million. In six months time
you'll know if there is a market for this new product.
If the market looks strong you'll put in another $10
million. As of today, the most you can lose is $5 million.
However, uncertainty about the value of the market opportunity
increases the chance of a great payoff. Uncertainty
increases value because it has this onesided effect.
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Tell me more about real options.
Real options is the extension of financial
option theory to options on real (nonfinancial) assets.
In contrast to the valuation of financial options where
decisionmaking it is a matter of shopping for the best
deal on a specified contract  the valuation of a real
option requires that it be identified and specified.
Moving from financial options to real options requires
a way of thinking, one that brings the discipline of
the financial markets to internal strategic investment
decisions.
The
real options approach works because it helps managers
with the opportunities they have to plan and manage
strategic investments. Stewart Myers of MIT coined the
term "real options" to address the gap between strategic
planning and finance.
"Strategic
planning needs finance. Present value calculations
are needed as a check on strategic analysis and vice
versa. However, standard discounted cashflow techniques
will tend to understate the option value attached
to growing profitable lines of business. Corporate
finance theory requires extension to deal with real
options."
Stewart
C. Myers, Sloan School of Management, MIT (1984),
p. 13.
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Is this book about strategy or finance?
As
you can see, options thinking is very useful for forming
strategy. But options can be very costly to acquire
and to maintain or keep alive. You should invest in
options with value greater than their cost  and you
need the optionspricing tools of finance to do this
kind of tradeoff. Also, in markets with uncertainty
both strategy and finance are focused on valuing risky
assets. This means that the risk/return tradeoff of
traded assets should be important benchmarks for corporate
assets as well. Using the financial options tools for
real options brings this type of discipline to corporate
strategy.
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How do financial options relate to
real options?
We've got a graph in our Harvard Business
Review article that summarizes this point. Basically,
financial option tools, such as the BlackScholes equation,
can be used when the options are not too complex and
there are direct comparisons to traded assets. But for
most realworld projects, the imbedded options are too
complex and/or there is less direct exposure to traded
assets. Valuing the options in real assets requires
a somewhat different, and more wideranging toolkit.
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Do you have to be a rocket scientist
to understand all this?
No! Our book has only three equations
in it. We wrote so that the power of this way of
thinking could be used by general managers.
As we've worked with companies, we've developed frameworks
and processes that build off of internal systems and
knowledge. Some of this is described in Chapter 7 of
our book.
Ironically,
our book has also attracted rocket scientists because
we show the many different applications of this approach.
They've got the math, but not a sense of the business
potential.
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Do the financial markets know about
real options?
Financial markets implicitly capitalize
real options in the stock price. Here are some data
points:
 Lucent.
If you used a traditional analysis based on projections
of cashflow from current products, Lucent would be
priced at just over $4 per share. Since its spinoff
from AT&T, Lucent has been trading far above that
amount, often in the range of $70 per share. The difference
is the capitalization by the financial markets of
Lucent's growth options
 Amazon.com.
This company went public before becoming profitable
and announced in its IPO prospectus that it would
not be profitable in the near future. Amazon.com is
also a growth option play. A large part of the company's
value is its strategy to make strategic investments
today that create options  opportunities to possibly
make further investments in the future. Enhancing
Amazon's value is Wall Street's perception that the
company has the managerial abilities to execute these
options.
 Cable
industry. Laura Martin of Credit Suisse First
Boston has used the real options approach to value
cable plant. See our downloadable case study.
 Real
estate. Quigg (1993) provides empirical evidence
that real estate prices reflect development options.
 Abandonment
options. Berger, Ofek and Swary (1996) demonstrate
that the financial markets recognize abandonment options.
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Who should be using real options
thinking?
Three kinds of managers. First, senior
management reads for the vision  particularly how corporate
strategy can be aligned to financial market valuation
of shareholder value. Second, inside companies, analysts
supporting senior management are often handed these
ideas from above, or want a way to introduce the power
of real options to senior management. Third, managers
who communicate externally. Because real options covers
uncertainty, strategic alignment and valuation, it integrates
and structures many of the issues companies want to
communicate to their customers and to Wall Street.
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Where have these ideas been used?
The range of applications is extraordinary,
including venture capital investment, to drug development,
to oil exploration, to IT implementation and to technology
licensing. See the reading list by industry application
and the FAQs by industry application below. In many
industries managers sense that they are making larger
and larger investment decisions in the face of greater
uncertainty  and so we expect that this approach will
continue to have wide application.
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We are already using decision analysis
in our firm. Will switching to the real options approach
change any decisions we make?
Decision analysis (DA) and other tools
are very useful and should be used when appropriate.
If you've already got the capability built up to use
these tools, then the 80/20 rule applies  real options
would need to provide a significant improvement before
I'd invest in a change. We're not wedded to a particular
tool.
However,
we've seen decisions change radically after a real options
review. Why?
 The
problem is reframed. Often engineers and others using
DA miss the market dynamics. Reframing the problem
highlights private versus marketpriced risk and puts
risk mitigation on the agenda.
 Linking
decisions to the marketpriced risk is a source of
competitive advantage. This is the point of our Harvard
Business Review article. For example, using DA one
might switch from one fuel to another at the wrong
time, a potentially costly mistake. In the small margin
commodity markets, these mistakes can be deadly.
 Risk
management. After laying out the risk, managers see
how to shape a project and change its risk profile.
We check our exposure to market movements for the
traded derivative securities we hold, but often fail
to do the same for real assets.
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Where can I learn more about the
option valuation breakthrough?
Two wonderful histories of the breakthrough
research have been written by Peter Bernstein: Capital
Ideas: The Improbable Origins of Modern Wall Street
(1992) and
Against the Gods  The Remarkable Story of Risk (1996).
The Nobel Prize web site,
http://www.nobel.se/, also has a good description
of the work by Fischer Black, Robert Merton and Myron
Scholes.
Good
introductions at the MBA level can also be found in
Brealey
and Myers (1996), Grinblatt
and Titman (1998), and Hull
(1997). Introductions at the undergraduate level
are in Brealey,
Myers and Marcus (1998), and Hull (1998).
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Thinking
Through the Valuation Model
What is
an underlying asset?
Suppose you hold a call option to purchase
IBM stock in three months. The value of this contract
depends on the value of IBM stock, the underlying asset.
Underlying assets for a real option are similar, they
are traded securities in the financial market whose
fluctuations largely determine the value of the option.
For example, the underlying asset for oil exploration
is the appropriate oil futures contract or index of
contracts. Traded contracts price in teh convenience
yield while spot prices do not include the value of
this attribute. Note that product prices (such as the
spot price of oil) or cashflows (such as profits) are
not assets. Framing must include the transformation
of these cashflows to uncertain assets.
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What information is needed to value
an option?
The following inputs are the only information
you need value an option:
 The
current value of the underlying asset,
which is observed in the market.
 The
time to the decision date, which is defined by
the features of the investment.
 The
investment cost or exercise price (also called
the strike price), which is defined by the features
of the investment.
 The
riskfree rate of interest, which is observed
in the market.
 The
volatility of the underlying asset, which is often
the only estimated input.
 Cash
payouts or noncapital gains returns to holding the
underlying asset, which are often directly observed
in the market, or sometimes estimated from related
markets.
An
example: What is the value of an option to buy TVSat
in six months time at 125% of today's price? TVSat's
stock trades on a major exchange. The inputs required
to evaluate the option are: the current value of TVSat;
six months, the length of time to the end of the option;
the guaranteed purchase price (125% of the current price);
the riskfree rate of interest,5%; the annual stock
price volatility of TVSat, 35%; and the dividends expected
to be issued by TVSat during the next six months.
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What information is NOT needed to
value an option?
Information that is not needed
to value an option contributes greatly to its power.
The following information is not used in the real options
approach:
 Probability
estimates are not needed because these are captured
by the current value of the underlying asset and the
volatility estimate.
 An
adjustment to the discount rate for risk is not
needed because the valuation solution is independent
of anyone's taste for risk.
 The
expected rate of return for the underlying asset
is not needed because the value of the underlying
asset and the ability to form tracking portfolios
already capture its risk/return tradeoff.
 The
expected rate of return of the option
is not needed because the option is valued directly
by dynamic tracking.
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Why doesn't DCF work for flexible
decisionmaking?
Most companies use some form of discounted
cash flow to value investment opportunities. However,
using the discounted cashflow approach to value contingent
investment decisions, the kinds of decisions facing
managers, produces a "showstopping" dilemma. Consider
the option to abandon. If the option is used, the asset
is abandoned and there is no further risk. If the option
is not used, there is risk to holding the option and
the asset. No single discount rate can bring these different
risks back to the present, and this problem has no remedy
inside the discounted cash flow framework.
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How does the real options approach
compare to the alternatives?
The HeadtoHead Comparison: Many corporations
have a collection of tools to better understand the
effect of uncertainty on large capital investments,
and successful consulting firms have been built to bring
these tools to their clients. Many of these methods
use discounted cash flow, and suffer from the discount
rate dilemma mentioned above. Here's a quick rundown
on how the methods compare to the real options approach
on other dimensions.
 Scenario
analysis.
Modifying a discounted cashflow analysis with scenarios
is the first step to incorporating uncertainty, but
each scenario remains fixed on a single future outcome
and investment plan. There is no clear way to reconcile,
aggregate, or choose between scenarios.
 Decision
analysis. Often called decision tree analysis,
decision analysis is a very straightforward way to
lay out future decisions and sources of uncertainty.
Decision analysis, however, relies on subjective assessments
of probabilities, subjective discount rates, and preferences
about the objective.
 Simulation
analysis. Simulation analysis lays out thousands
of possible paths for the uncertain variables. It
is very difficult to handle decision opportunities
that arise before the final decision date in a simulation
model. In addition, it is often hard to interpret
the results of a simulation analysis because simulation
models use a subjective discount rate and do not incorporate
financial market information.
 Real
options. In contrast, real option valuation is
based on objective inputs, and a precise list of which
inputs are needed and which are not. Those inputs
are used in a way that produces market values and
the real options approach guides the user on where
to look and why. Experienced users of the real options
approach see the patterns, the types of options, and
the important sources of uncertainty. In addition,
the real options approach provides a framework for
revising expectations and for managing investments
over time. The optimal exercise of managerial options
requires frequent scans of the environment and updates
of important information.
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Getting
the Numbers
When can
the BlackScholes Equation be used to value real options?How
about the binomial method?
The choice of solution method depends
on the particular features of the application. Some
applications can only be solved using certain solution
methods. For example, the BlackScholes formula does
not work for American style options.
The
Black Scholes Equation.
The partial differential equation that Black and Scholes
studied mathematically defines the evolution of the
value of the option in terms of the value of the underlying
asset, its volatility, and the riskfree rate of return.
Different partial differential equations are specified
to reflect the specific features of the option, and
not all partial differential equations have an analytical
solution. (In an analytical solution the option value
can be written as a function of the inputs.) The BlackScholes
equation is an elegant, singleequation solution to
one particular partial differential equation. When
an analytical solution is available, it is a simple
matter to program the equation(s) into a spreadsheet.
The BlackScholes equation is well suited for simple
real options, those with a single source of uncertainty
and a single decision date.
Numerical
Methods. When the application is more complex
and includes particular features of a real asset such
as multiple sources of uncertainty or many decision
dates, analytical solutions cannot be obtained. Specialized
mathematical tools known as numerical methods are
required.
The
Binomial Model. One approach for handling complex
real options, riskneutral valuation, was introduced
by John Cox and Stephen Ross in 1976 and later applied
by these authors and Mark Rubinstein in a very useful
manner in the binomial option valuation model. (See
Cox and Ross (1976) and Cox, Ross and Rubinstein (1979).)
The key insight of the riskneutral approach is that
because the option values are independent of everyone's
risk preferences, the same valuations will be obtained
even when we assume that everyone is indifferent to
risk, or riskneutral. This assumption simplifies
calculations enormously because we do not need to
estimate the premium for risk in the discount rate,
because no investor requires compensation for taking
on risk. A particularly simple, yet robust, implementation
of the riskneutral approach is the binomial option
valuation model, in which the underlying asset moves
up or down by a small amount in each short period.
There
are three advantages to the binomial option valuation
model:
 It
spans a large range of real option applications, including
those with some complexity.
 The
approach is comfortable for many users because, although
it is consistent with the option valuation breakthrough,
it retains the appearance of discounted cash flow
analysis.
 Uncertainty
and the consequences of contingent decisions are laid
out in a very natural way; the binomial model generates
good visual images.
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Tell me more about private risk.
There are several aspects to private
risk:
 Number
of sources.
Everyone tends to include quite a few, but it is not
always clear that they have economic impact. We're
in the process of developing a methodology for reduction
in the number of sources of private risk.
 Magnitude
of the economic consequences. If the economic
consequences of private risk are small, then one need
not worry about corporate attitudes towards risk and
the private risk should be folded into the analysis
and discounted at the riskfree rate. You can use
a binomial model with two sources of uncertainty for
example.
 The
discount rate issue. If the private risk has large
economic consequences, some academics argue that corporate
risk aversion and a riskadjusted discount rate should
apply. Others argue that on should use outputs, such
as a VARtype analysis to make decisions about the
cost/benefits of mitigation, but continue to fold
in private risk under the riskneutral framework.
Overall,
one needs to be dogmatic about using marketbased perspectives
throughout the framing steps. It is too easy to "over
model" private risk, including too many sources and
too much detail.
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Is the choice between a lognormal
and a meanreverting process for the underlying asset
important?
Professor Robert Merton of HBS, and the
1997 Nobel Prize winner in Economics, has the following
test question in his MBA Finance class: Suppose you
have two option contracts with the same terms. The first
contract is on "soap" (or some product) and the underlying
asset is a future contract on soap. Soap is known to
have a geometric brownian motion (GBM) process. The
second contract is on "butter" and the underlying asset
is a futures contract on butter. Butter has a meanreverting
process. Sigma is the same for the two futures contracts.
Which option is more valuable?
Answer:
The two options have the same value. In this case, the
futures contracts price in the appropriate stochastic
process. The futures contracts themselves have a GBM
process. The point is that the stochastic process is
priced into the asset value. This is just the same as
with stocks. Asset values capitalize information, spot
prices reflect current supply and demand.
Hence,
we think the issue about choice of stochastic process
for the underlying asset is most often a framing issue,
not one of statistics. There will be occasions in which
the underlying stochastic process must be specified,
but these are more rare than most users think. For one
application in which a choice had to be made see Tufano
and Moel (1998)
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If you increase volatility, the value
of the option will increase. However, increasing volatility
also decreases the discount rate, lowering the value
of the project. What's going on?
This is a comparison about the effects
of volatility in two different valuation models. The
optionsbased valuation model includes decision making
opportunities. When managers can avoid losses, increased
volatility only raises the upside potential. In a discounted
cash flow (DCF) model, increased volatility increases
the discount rate, holding all else constant. But can
you really hold all else constant? For example, if you
used the CAPM to calculate the discount rate, you'll
need to reestimate beta under the new volatility regime.
You might also want to check your cashflow forecast.
Thus, the total effects of volatility on a DCF model
are not entirely clear, and nothing about the model
gets managers to systematically think about the effects
of volatility.
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I've collected the data and calculated
some historical volatilities for three firms I'm studying.
These results are very different than the option price
volatility information available at the CBOE web site.
Which should I use?
There are two different ways to estimate
volatility. Historical data provides an estimate of
the volatility experienced in the past. This often is
a good guide to the future as well. Implied volatilities
(those calculated from traded options) are the market's
forecast of future volatility. In theory these are precisely
what you need, so use them!
When
comparing volatility estimates, make sure you've got
the numbers right:
 Use
atthemoney options for the best estimate of implied
volatility. The volatility estimate will vary across
strike prices, and the atthemoney estimate contains
fewer of the confounding effects.
 Keep
your units are straight, so that you are comparing
annual volatility to annual volatility and so on.
 Adjust
historical stock price series for dividend payments
before calculating returns.
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Do I need to define a corporate utility
function to include private risk in my calculations?Do
corporate utility functions differ?
Corporations maximize value, but face
constraints such as cashflow, earnings targets, and
so on, that make managers risk averse. See two good
articles, one by Froot, Scharfstein and Stein in Harvard
Business Review and another by Tufano in the Journal
of Applied Corporate Finance.
A
key question for private risk is magnitude. If the incremental
risk of the project significantly change the corporate
profile, then some have argued that adjustments should
be made to the option valuation model. If the incremental
risk does not change the corporate profile then continuing
with the option valuation approach should be fine.
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How do I get taxes into a real option
valuation?
Taxes are down two layers in an option
calculation. Starting from the top: an option depends
on an underlying asset. If this asset is present value
of future cashflow, then taxes would go in the cashflow
model. The effect is to decrease the present value of
future cashflow, an input into the option calculation.
Sometimes
the underlying asset is a price, such as when futures
contracts are used to obtain an oil price. Suppose the
solution method was the binomial model. There would
be an event tree (oil price movements), a cashflow tree
(calculation of cashflow per oil price) and a valuation
foldback. In this solution method taxes are folded into
the asset as the valuation rolls back.
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Industry
Applications
Utilities
Water:
Has
the real options approach been used to value infrastructure
investments in the water industry?
The water industry is undergoing deregulation,
spurring a need for asset valuations that are aligned
with water pricing. This is the same phenomena that
has previously occurred in the electricity and gas industry,
and articles about the financiallyengineered products
and asset valuation in these industries might be of
use. Enron has a business unit active in the water industry,
so expect an invasion of real options thinking.
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Electricity:
In
the summer of 1998 wholesale electricity prices spiked
from $20MWh to $5,000/MWh. What was going on? Did the
market misvalue the futures prices?
The electricity market is not fully deregulated,
constraining supply in response to high prices. This
causes electricity price spikes to reach higher levels
and to last longer than would occur in a fully deregulated
market. Also, transmission capacity and geographical
layout plays an important role, placing supply response
constraints on the system. These two factors can cause
spot prices to deviate from the market's forecast in
the futures price. As market participants learn more
detailed information about how these two factors affect
spot price dynamics, the futures and spot prices will
line up better. As we note in our book (page 95, "Electricity
Trades Shocked by BlackScholes"), market participants
learn fast.
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In chapter 16, you do not mention
the volatility of revenue, which is dependent on the
price of eelctricity. Isn't the volatility important?
The analysis we presented is about acquiring
a physical asset to produce steam. Because the physical
asset came in tree types, we focused on those. However,
expanding the set of alternatives would be the right
thing to do, particularly to include producing steam
from electric powered boilers or possibly buying steam
from the electric company. The importance of these alternate
investments depends on the relative levels and volatility
of gas, oil, and electricity prices.
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R&D,
Product Development and Technology
Pharmaceutical R&D:
What
is the best approach to valuing a drug in development,
during clinical trials?
This is an active area of research, so
expect more soon on this topic. R&D projects can be
viewed as investments that create options. The value
of a drug in the R&D stage can be obtained through a
nested options valuation model. See Chapter 11 of Amram
and Kulatilaka for an overview, and their Guide to the
Literature for some pointers to other papers.
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Negative
value to R&D:
Are
there applications in which more research and more information
leads to a liability instead of an asset?
In
the options approach, R&D creates information used by
managers to make better decisions. However, if the same
information allows another party to make a better decision,
the net value of the information might be negative.
For example, tobacco companies funded research on the
effects of smoking, and then withheld the results. They
may have used this information for internal decision
making, but the legal system also allowed prosecutors
to use this information (once discovered) to make other
decisions.
So
the key question is about decision rights. If R&D creates
information that can only be used by your company, the
options results as described in our book apply. If R&D
also creates information that others can use, then you
need to ask whether they may make decisions that destroy
value.
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Technology
licenses:
In
a Harvard Business Review article (1984), W. Kester
defines proprietary options (those owned by your firm)
and shared options (those also held by your competitors.)
We've got some good technology, but it is not exclusive.
How do we "haircut" the value of our technologybased
options to get the correct value?
First, the core technology might not
be exclusive, but what you do with it might develop
an exclusive implementation. Thinking through all the
subsequent investments might redefine the option from
shared to proprietary.
Second,
you might be interested in some recent papers by Steve
Grenadier at Stanford who has been tackling the issue
of industry dynamics when all players hold options,
both shared and proprietary.
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New
applications
Filmmaking:
Has
the real options approach been applied to valuation
and strategy in the film industry?
We know of at least one project underway
in this area, so expect more soon on this topic. Basically
films in production can be valued as optioncreating
investments. The application frame is similar to investments
in earlystage oil exploration or earlystage pharmaceutical
R&D. Firm libraries are portfolios of options, and are
similar to portfolios of patents. In each case an initial
investment has been made that creates an option to make
follow on investments.
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Online
Learning:
What's
the real options perspective on the following question:
Should a state university expand by investing a large
amount of money in buildings, or putting everything
on the web and presenting a webbased education?
Although, for many companies, certain
types of experiences and costumer solutions can be delivered
through the internet, without entry barriers created
by bricks and mortars, there is enormous competition
through rapid technology change on the web. It is expensive
to keep web services on the leading edge. This suggests
that a state government might not be the right vehicle
to be creating online education. It is now a national
market. Perhaps vouchers for accredited online education
would be better than state ownership.
Traditionally,
many universities have not been able to fully exploit
the options created by their facilities. For example,
summer school is there, but underutilizes the physical
plant. Special courses don't fill the gap. Perhaps the
marketing cost or organizational structure increases
the cost of exercising these options. Face to face contact
is the most effective form of learning. You don't get
it on the web.
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