General Motors

Vision
"GM’s vision is to be the world leader in transportation products and related services. We will
earn our customers’ enthusiasm through continuous improvement driven by the integrity,
teamwork, and innovation of GM people."

Mission
"G.M. is a multinational corporation engaged in socially responsible operations, worldwide. It is
dedicated to provide products and services of such quality that our customers will receive
superior value while our employees and business partners will share in our success and our
stock-holders will receive a sustained superior return on their investment."

Goal
GM's goal is to develop cars and trucks that have an emotional appeal for a new generation of
consumers - cars and trucks that people feel they must have.

Strategy
 Designing, building and selling great cars and trucks that people really want to own.
 Offer great value and quality that consumers can trust.
 Strengthening its brands, with more innovative marketing that better understands the
customer.
 Build or expand strong positions in growth initiatives.

Submitted by:
Ankita Chauhan
Roll no. 5
 Real options analysis
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In finance, real options analysis or ROA (not to be confused with return on assets) applies put
option and call option valuation techniques to capital budgeting decisions.[1] A real option itself,
is the right — but not the obligation — to undertake some business decision; typically the option
to make, abandon, expand, or shrink a capital investment. For example, the opportunity to invest
in the expansion of a firm's factory, or alternatively to sell the factory, is a real option.

ROA, as a discipline, extends from its application in Corporate Finance, to decision making
under uncertainty in general, adapting the mathematical techniques developed for financial
options to "real-life" decisions. For example, R&D managers can use Real Options Analysis to
help them determine where to best invest their money in research; a non business example might
be the decision to join the work force, or rather, to forgo several years of income and to attend
graduate school. Thus, in that it forces decision makers to be explicit about the assumptions
underlying their projections, ROA is increasingly employed as a tool in business strategy
formulation.[2]

Contents
[hide]

 1 Comparison with standard techniques

 2 Valuation
o 2.1 Valuation inputs
o 2.2 Valuation methods
o 2.3 Technical considerations
 3 History
 4 See also
 5 References
o 5.1 Notes
o 5.2 Bibliography
 6 External links

[edit] Comparison with standard techniques

ROA is often contrasted with more standard techniques of capital budgeting, such as net present
value (NPV), where only the most likely or representative outcomes are modelled, and the
"flexibility" available to management is thus "ignored"; see Valuing flexibility under Corporate
finance. The NPV framework therefore (implicitly) assumes that management will be "passive"
as regards their Capital Investment once committed, whereas ROA assumes that they will be
"active" and may / can modify the project as necessary. The real options value of a project is thus
always higher than the NPV - the difference is most marked in projects with major uncertainty
(as for financial options higher volatility of the underlying leads to higher value).

More formally, the treatment of uncertainty inherent in investment projects differs as follows.
Under ROA, uncertainty inherent is usually accounted for by risk-adjusting probabilities (a
technique known as the equivalent martingale approach). Cash flows can then be discounted at
the risk-free rate. Under DCF analysis, on the other hand, this uncertainty is accounted for by
adjusting the discount rate, (using e.g. the cost of capital) or the cash flows (using certainty
equivalents, or applying "haircuts" to the forecast numbers). These methods normally do not
properly account for changes in risk over a project's lifecycle and fail to appropriately adapt the
risk adjustment.

In general, since ROA attempts to predict the future, the quality of the output will only ever be as
good as the quality of the inputs, which by their nature are sketchy. This comment also applies to
net present value analysis, although NPV does not require volatility information (see below).
Opinion is thus divided as to whether Real Options Analysis provides genuinely useful
information to real-world practitioners. ROA is therefore increasingly used as a discussion
framework, as opposed to as a valuation or modelling technique.

[edit] Valuation
As above, ROA is distinguished from other approaches in that it takes into account uncertainty
about the future evolution of the parameters that determine the value of the project, and
management's ability to respond to the evolution of these parameters.[3][4] It is the combined
effect of these, that makes ROA technically more difficult than its alternatives.

[edit] Valuation inputs

Generically, the inputs required for modelling the real option correspond to those required for a
financial option valuation.[5]

 The option's underlying is the project in question - it is modelled in terms of:

o spot price: the starting or current value of the project is required: this is usually
based on management's best guess as to NPV; some analysts use a listed security
as a proxy;
o volatility: uncertainty as to the change in value over time is required: when the
underlying project is used, the volatility of project NPV is used (sometimes the
volatility of the first period's cash flows are preferred[4]); when a proxy is used,
this is either the volatility of the price of the security (historical volatility), or, if
options exist on this security, their implied volatility.

See further under Corporate finance for a discussion relating to the estimation of NPV
and project volatility.
  Option characteristics:
o Strike price: this usually corresponds to sunk costs. In general, management
would proceed (i.e. the option would be in the money) given that the present value
of expected cash flows exceeds this amount;
o Option term: the time during which management may decide to act, or not act,
corresponds to the life of the option. Examples include the time to expiry of a
patent, or of the mineral rights for a new mine. See Option time value.

 Option style. Management's ability to respond to changes in value is modeled at each

decision point as a series of options:
o the option to contract the project (an American styled put option);
o the option to abandon the project (also an American put);
o the option to expand or extend the project (both American styled call options);
o switching options, composite options or rainbow options which may also apply to
the project.

[edit] Valuation methods

The valuation methods employed are generally adapted from techniques developed for valuing
financial options. The most commonly employed are Closed form solutions - often modifications
to Black Scholes - and binomial lattices; the latter are probably more widely used due to their
flexibility. Specialised Monte Carlo Methods have also been developed and are increasingly
applied particularly to high dimensional problems. When the Real Option can be modelled using
a partial differential equation, then Finite difference methods for option pricing are sometimes
applied. Although many of the early ROA articles discussed this method, its use is relatively
uncommon today - particularly amongst practitioners - due to the required mathematical
sophistication. For a general discussion, see Option (finance): Model implementation.

In general, these methods are limited either as regards dimensionality, or as regards early
exercise, or both; in selecting a model, analysts must usually trade off between these
considerations. Additionally, sometimes, the stochastic nature of such projections can make
analysis using the Monte Carlo method infeasible, necessitating other investigatory methods,
such as Robinson differentials. Other new methods have recently been introduced to simplify the
calculation of the real option value and thus make the numerical use of the methods easier for
practitioners; these include the Datar-Mathews method (2004,2007) and the Fuzzy Pay-Off
Method for Real Option Valuation (2008).

[edit] Technical considerations

Limitations as to the use of these models arise due to the contrast between Real Options and
financial options, for which these were originally developed.

The main difference is that the underlying is often not tradeable - e.g. the factory owner cannot
easily sell the factory upon which he has the option. As above, this results in difficulties as to
estimating the value (i.e. spot price) and volatility of the underlying which are key valuation
inputs - this is further complicated by uncertainty as to management's actions in the future.
Further, and relatedly, difficulties arise in applying the rational pricing assumptions which
underpin these option models: often the "replicating portfolio approach", as opposed to Risk
neutral valuation, must be applied.

Additional difficulties include the fact that the real option itself is also not tradeable — e.g. the
factory owner cannot sell the right to extend his factory to another party, only he can make this
decision; however, some real options can be sold, e.g., ownership of a vacant lot of land is a real
option to develop that land in the future. Some real options are proprietary (owned or exercisable
by a single individual or a company); others are shared (can be exercised by many parties).
Therefore, a project may have a portfolio of embedded real options; some of them can be
mutually exclusive.

[edit] History
Whereas business operators have been making capital investment decisions for centuries, the
term "real option" is relatively new, and was coined by Professor Stewart Myers at the MIT
Sloan School of Management in 1977. It is interesting to note though, that in 1930, Irving Fisher
wrote explicitly of the "options" available to a business owner (The Theory of Interest, II.VIII).
The description of such opportunities as "real options", however, followed on the development
of analytical techniques for financial options, such as Black–Scholes in 1973. As such, the term
"real option" itself is closely tied to these new methods.

Real options are today an active field of academic research. Professor Eduardo Schwartz
(UCLA) was a pioneering academic in the field. Professor Lenos Trigeorgis (University of
Cyprus) has been a leading name for many years, publishing several influential books and
academic articles. An academic conference on real options is organized yearly (Annual
International Conference on Real Options).

Amongst others, the concept was "popularized" by Michael J. Mauboussin, the chief U.S.
investment strategist for Credit Suisse First Boston and an adjunct professor of finance at the
Columbia Business School.[6] Mauboussin uses real options in part to explain the gap between
how the stock market prices some businesses and the "intrinsic value" for those businesses as
calculated by traditional financial analysis, specifically using discounted cash flows. Trigeorgis
also has broadened exposure to real options through layman articles in publications such as The
Wall Street Journal.[7] This popularization is such that ROA is now a standard offering in
postgraduate finance degrees, and often, even in MBA curricula at many Business Schools.

Recently, real options have been employed in business strategy, both for numerical-valuation
purposes and as a conceptual framework. The idea of treating strategic investments as options
was conceived by Timothy Luehrman [8] in two HBR articles:[5] "In financial terms, a business
strategy is much more like a series of options, than a series of static cash flows". Using
Luehrman's framework, investment opportunities are plotted in an "option space" with
dimensions "volatility" & value-to-cost ("NPVq"). The higher either of these, the greater the
option value inherent in the investment.
Options in mutually exclusive projects of unequal lives

Christine Browna and Kevin Davisa

a
The University of Melbourne, Australia

Available online 19 January 2000.

Standard techniques advocated for choosing between mutually exclusive projects of unequal
lives make an implicit assumption of continued project replication. While intuitively appealing,
those techniques ignore the fact that project replication is one outcome of a repeated choice
situation, and may not be the optimal outcome once stochastic features of the environment are
taken into account. In essence, standard techniques ignore the real options relating to the
subsequent choices inherent in each decision. By means of a simple example, assuming interest
rate uncertainty, it is demonstrated that the standard techniques can lead to errors in a stochastic
environment. Because of the idiosyncratic characteristics of project comparisons and the
compound nature of the options involved, neat analytical solutions and techniques are not
available to replace the elegant, but inadequate, textbook models. Financial managers need to
model each choice on a case by case basis, appropriately identifying the key drivers of Net
Present Value and specifying the stochastic environment pertaining to each.