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WIND ENERGY IN COLOMBIA:
An approach from the real options
Ana Maria Mora Luna
Carla Susana Agudelo Assuad
Isaac Dyner R.
Universidad Nacional de Colombia
Facultad de Minas
Instituto de Energia
ABSTRACT
Key words: investment, decision, real options, system dynamics.
It is proposed to employ the real options methodology to assess an investment project of
wind energy generation in Colombia, backed up by a model with systems dynamics which
reproduces the interaction between market values that determine the operative conditions
of the projects and that have an effect on the investment decisions.
With that purpose, the Colombian Electrical System (CES) and the investment conditions
within it are characterized. Then the real options methodology to assess investment
projects in the analyzed market is presented and the built model is described. Finally, the
found results are shown and it is given a conclusion on profitability of the real options to
assess investment projects of wind generation in Colombia.
1. INTRODUCTION
Investments in wind energy in Colombia and in other countries of the world are
irreversible, costly, and are subject to numerous uncertainty sources, such characteristics
draw complexity in the decision making process. Yet, some projects count on strategic
flexibility that allows to decide an optimum moment of completion, expansion, contraction,
interruption or quitting depending on the market conditions that determine its profitability.
In this context the investor requires methodologies that ease the decision making process,
specially when investments are done with unusual technologies without operative
antecedents in the local market.
At several times investment projects with negative net present value have been carried out,
this determination originates from investor’s intuitive perceptions that contemplate implicit
options in the project that may become profitable according to future evolution of market
variables relative to this. The real options methodology (differing from the traditional
methodology of project assessment based on discounted free cash flows) captures the
implicit strategic flexibility in investment projects with high uncertainty, conferring a
financial support to this flexibility, in order to extend the existing information in the
decision making process.
Particularly, in Colombia -differing from other countries where the operation of wind
energy parks is in a learning curve- technology has not a great background, therefore its
future development is absolutely uncertain. Additionally, the generation of wind energy is
characterized by its modularity, which facilitates investment in pilot wind energy parks
whose expansion is subject to operation and performance of technology in the market.
Facing this fact, the assessment of this kind of project must account for market uncertainty
and strategic flexibility that is inherent to it.
An options methodology is attempted to analyze the development of a wind energy project
value and its option to expand in a specific period of time, backed up with a model in
systems dynamics that capture interactions of the Colombian electrical market, in which
some variables intervening in the project assessment are produced. Thus, through a first
approach it is sought to capture in an objective way (numeric or financial) the value of the
expansion option inherent to a wind energy generation project in Colombia, and enrich the
investor’s decision project by offering him a greater financial support that lets the project to
be managed and to decide in which moment the project can be carried out giving up the
possibility of clarifying part of the uncertainty.
This paper is part of a research project in process, developed in association with
Universidad Nacional de Colombia, Colciencias and Empresas Publicas de Medellin, and
pretends to analyze the operation, risk and expansion possibilities of the wind energy
market in Colombia.
2. INVESTMENTS IN THE COLOMBIAN ELECTRICAL SECTOR
2.1. Sector characterization
The structure of the Colombian Electrical System (CES) was substantially modified with
the amendment agreed in 1994 by the law on public services (law 142) and the law on
electrics (law 143). With such reform participation of different economic agents -public,
private or mixed in the activities of the sector- is allowed, and the state -which used to play
an administrative and economical role because of its position as an only investor- is given
the duty of regulating and controlling the activities of the sector, aiming to have an
efficient, safe and reliable national electrical system.
This liberalization initiated in 1995 is the result of the experience of England and Gales in
the reform of their electrical systems (Millan, Lora y Micco, 2001, p.16-18), and of aspects
such as the technological development in the generation industry and the energy crisis of
1992 ( ISA, 1999, p.34). The reform also includes the regulation of the major energy
market and vertically separates the activities of energy generation, commercialization,
distribution and energy transmission.
The sector technological portfolio to December 2002 was formed by hydraulic generation
(65.43%), gas-thermic generation (28.90%) and coal-thermic generation (5.67%)
representing a gross connected capacity of 13678.43 MW (UPME, 2002, <on line>).
It is evident that the Colombian system depends on its hydraulic capacity, which makes it
vulnerable to hydroclimatic phenomena that may eventually restrain the water resource
availability as in past years, particularly with the El Nifio phenomena in 1991-1992 and
1997-1998, when the former case led the country to blackouts and to quite high energy
prices in the latter case (Osorio,2002,p.10).
2.2. Investment decisions in the sector
Differing from the previous centralized planning market, in the current one the investments
infrastructure aim to social development by supplying the energy demand on the state part,
but they also try to reach objectives of economic development, that is to say, obtaining
profitability and risk management due to the fact that the investment comes not only from
public agents but also from private ones. Nevertheless, the adopted market structure
presents internal working mechanisms and an interaction with the market environment,
such as the subjacent relations between supply and demand, regulatory policies,
technological development, among others, which are mostly unknown by the investors,
becoming sources of uncertainty in the moment of making investment decisions (Dyner y
Larsen, 2001; Smith, 2002, p. 42). In such circumstances, the investor is exposed not only
to the risk that an investment project involves , but also to the risk in the energy price.
In this high investment and uncertainty context, capacity investment projects include
valuable strategic options stemming from the operative and management flexibility of the
investor to decide whether to carry out the project, modify it during its construction and
operation, or simply postpone it awaiting more information. The financial analysis of the
projects on generation must give account of these options and of the characteristic
uncertainty in the CES in order to improve investment decision scenarios.
In particular, as an answer to the system vulnerability and to international trends in energy
generation with renewable resources, Colombia has been developing research projects
tending to identify possibilities of development in the generation of wind energy -
technology with no antecedents in the country-, which requires orientation in eventual
investment decisions.
3. REAL OPTIONS IN INVESTMENT ASSESSMENT OF EOLIC ENERGY
GENERATION IN COLOMBIA
3.1. Traditional approach in project assessment
The method based on discounted Free Cash Flows (FCF) has been traditionally used to
assess investment projects, such method involves a deterministic nature that foresees
variables that have to do with the assessment and offers few possibilities of future
scenarios. Likewise, investment is taken as a now-or-never decision, not containing
management and operative flexibility that lets the investor alter the project along the time
when sources of uncertainty related to the project are solved.
In the CES, this method has been used to evaluate investments not only by public
companies but also by private ones depending on the nature of the project and the goals
sought. In the mean time uncertainty has incorporated by means of sensibility analyses.
However, discounted FCF methodology presents inconveniences when used to assess
projects with strategic options (like energy generation). Among the problems we find the
underestimating of projects reporting low or no cash flow, the non-consistent nature of
capital cost along the time, the exclusion of risks that capital cost does not capture, the
assessment of the project lead time, mistakes in projection of cash flows and sufficient
proofs of validity of final results (Mun, 2002, p.57; Trigeorgis, p.121).
In spite of all this, methodology based on cash flows is a clear and consistent method for all
projects, offering the same results regardless of risks preferences of each investor, it
provides a satisfactory and economically rational level of accuracy, it is a relatively simple,
widely taught and accepted method and it can be simply explainable to management (Mun,
2002, p.58).
The traditional method of assessment and decision criteria stemming from this one, are not
mistaken, but its usage in investment projects with implicit strategic attributes may lead the
investor to make decisions without the complete information of the real final state of the
project due to the fact that the Net Present Value (NPV) might be negative but the eventual
possibilities it has, may raise its value and make it a viable project.
Within the CES, in many cases investors have accepted investment projects whose NPV is
negative, however, this acceptance has been the product of intuitive perceptions regarding
the feasibility evolution of projects along the time and regarding strategic factors, such is
the case of wind energy generation in Colombia.
3.2. Real options methodology
Interaction among factors such as the number of agents, the variety of investment
alternatives, the wild competition to capture demand in liberalized markets, the opportunity
cost of resources, among others, introduce complexity in the current business atmosphere
and make the investment decisions a little trivial. The decisions are the result of rigorous
analyses processes of endogenous and exogenous variables into companies, due to the fact
that mistaken decisions may bring about disastrous consequences, however, in this context,
business alternatives are plentiful, and the investor asks himself: Which path to follow? Are
there valuable options included in the alternatives? At which point should I quit or invest in
a project? How are investments assessed in the most objective way possible? In order to
give a suitable answer to these questions, the investor requires instruments that enrich
decision making and let him choose a way of action with the most accurate and available
information at the moment.
The real options approach considers strategic alternatives that certain projects under
uncertainty conditions, management and operative flexibility involve, in order to use these
options in a temporary horizon, depending on the market conditions and the learning
process reached with the time as uncertainty decreases.
Strategic options have an intrinsic value, but such value is only obtained when management
decides to use the mentioned strategies (Mun, 2002, p.24), and when it is feasible to
identify traits as: high uncertainty in operative, technological and market factors, among
others, the project value is determined by the uncertainty level, the management has
flexibility to decide, strategies are believable and achievable, and management in rational to
use strategies (Mun, 2002, p.150).
This management flexibility to perform corrections during the process when uncertainty
towards the future exists, should be considered within the value of the projects, because
they represent rights and opportunities that any organization can possibly execute when
subjacent conditions of a respective project are favorable or unfavorable accordingly.
WP Uncertain
Cpertivé 'y a7
Factors M:
ee ae Multiple
Flexibility Decisions
Technologic:
Factors
Market
Factors ae
aluation
Time
Figure 3.1. Real options assessment structure
In figure 3.1 it is shown the structure originating assessment with real options. As
previously stated, several uncertainty factors, together with management ability to switch
strategies along the time, determine strategic options in projects that must be included in its
assessment.
The real options methodology employs the theory of options to evaluate physical or real
assets (Mun, 2002, p.79; Trigeorgis, p.16). A real options resembles a financial option
which represents the rights but not the compromise to acquire an asset within certain
amount of time or within a deadline, at an agreed price called exercise price (Lamothe,
1993, p.3).
An investment project can be understood as an option that gives the investor the possibility
but not the compromise to execute it, dealing with an investment cost and obtaining a return
represented in a current value of cash flows expected in the project operation which are
unknown and uncertain. The option does not represent a compromise as for the investor
decides not to invest when he does not find it profitable.
Under this approach, the risk of obtaining undesirable results is limited (Mun, 2002, p.91;
Mascarefias, 1999, p.146; Trigeorgis, p.69, 122), because the investor does not invest if
market conditions are not favorable for the project, whereas the benefit obtained is limited
and reinforced by the investor’s flexibility to select the best strategy to implement when he
obtain new information and clarifies uncertainty (Mun, 2002, p.82).
Now, the existence of options inherent to certain investment projects is clear and must be
incorporated in the assessment of the projects.
The theory of options establishes the value of an option forming a portfolio from which all
movements and changes are controlled and has the same returns of the options (mimetism).
Under this non-arbitrage condition the equivalents between the value of the option and the
portfolio is guaranteed as its price evolutions (Amram and Kulatilaka, 2002, p.61), that is
the reason why the determination of the option value is based on the assessment of the
subjacent asset in any respective market.
There are different solution methods to calculate the option value. The analytic method
based on differential equations of Black&Scholes ,the Monte Carlo simulation and the
binomial trees (Hull, p.987-408; Mun, p.139), which application depends on the
characteristics of the option to be valued’.
For the assessment of a real option (regardless of the method employed) it is necessary to
identify the following elements (table 3.1):
Table 3.1. Elements needed for a real option assessment.
Element Input
Underlying asset Investment project
Underlying asset value Investment’s present value cash flow
Time to expiration Period in which decision can be made
Exercise price Project’s initial investment
Underlying asset volatility _| Underlying operative risk
Risk free rate Temporary money value
1 These methodologies are used to assess financial and real options. They differ in their approach,
but in many cases if inputs and application frames are correctly structured, the lead to the option
value itself with certain of accuracy.
These factors determine the option value, being volatility a crucial variable (Lamothe, 1993,
p.43-47). As long as volatility is higher the investment option is more valuable, due to the
fact that this widens the potential results, however, this does not necessarily increases the
desire of applying it, inversely, the increase in risk reduces the desire of investing. The
option becomes more valuable because it reflexes the need to wait for more information
(Mascarefias, 1999, p.147).
This method consists in supposing that the price of the underlying asset (S) develops
according to a binomial multiplicative process, that is to say, in an interval of short future
time the underlying asset may increase to a “Su” extent, with probability p, or decrease to a
“Sd” extent with probability /-p, until reaching the deadline (Amram and Kulatilaka, 2002,
p.160) with a fixed number of steps that determine the time interval between a change in
price of a underlying asset and another.
Particularly, in the electrical sector, the strategic alternatives that an investor has during the
lead time of an investment project, characterize the flexibility for the delays in its
beginning, searching the optimum moment to invest and to start operation, the possibility of
quitting the operation of a plant temporarily or for good, the possibility of increasing or
decreasing the production rate, or according to the type of project, the opportunity of
alternating the production modes using different technologies (Trigeorgis, 1999, p.122;
Integral-UN-Colciencias, 2000). The traditional assessment methodologies do not give
account of this flexibility inherent to projects or investment options because they assume a
constant and predictable nature of variables that intervene in assessment, they offer a few
possibilities of future scenarios and define investments as now-or-never decisions. This
situation supports the usage of the real options methodology in the study of an investment
in an wind energy park. In order to develop the assessment in this term paper, a binomial
tree will be used, which is a flexible method that permits to easily comprehend the different
phases in the assessment of options as well as the complications that can come up during
the process (Amram and Kulatilaka, 2000, p.154).
4. SISTEMIC METHODOLOGY
A company that interacts with the electric energy market is a system that presents dynamic
complexities, that is to say situations where cause and effect are subtle, and where effects in
the intervention through the time are not obvious. The forecast, planning and conventional
analytic methods are not enriched enough to face dynamic complexity (Senge, 1995, p.96).
Most of the “systems analyses” are concentrated in the complexity of details’, not in
dynamic complexity. Simulations with thousands of variables and complex detail displays
keep from seeing patterns and interrelations (Senge, 1995, p.96). The systems dynamics is
a simulation tool based on feedback and delay premises between decision making and its
effect on the organizations, characteristics that make it different from other simulation
? Complexity of details is lineal and is characterized by the existence of many variables (Senge,
1995, p.95).
techniques used to support strategic planning. Its power comes not only from its predictive
capacity but also from the possibility to support the design of policies and give answers to
questions such as what would happen if this occurred? (Dyner, 1993, p.1). During the
decision making process it is essential to be aware of available alternatives and their
probable consequences. That is why it is important to count on instruments to select such
alternatives and to simulate the behavior of organizations under diverse considerations
(Dyner, 1993, p.2).
Because of the foundations described above, the objectives in this model will be reached
using systems dynamics, in order to get -beyond a forecast of possible scenarios-, to a
systematic analysis which permits an approach to the study of the influence of certain
variables on the value of options of a wind energy generation project in Colombia.
4.1. | Model description
The model is divided into two modules, the first one interprets the behavior of the electric
energy market and the second one comprehends the financial working structure of an
energy generation and commercialization company. Both of them interact with each other
by means of processes that include feedback and delay.
Figure 4.1 shows the main variables to study in an energy generation and
commercialization company (in blue), which interacts with the market (in red), identifying
four great loops.
Taking advantage
of options
x
Investment Debt capacity
Options . Politic
rojects
peas Investments
Demand > Risk t S
eS Resources
available to e>)
< Supply invest ht
> Leverage —p» Debt
Price Profits Capacity
Expenses
Figure 4.1. Energy generation and commercialization company dynamic.
4.2. Loops description
For a company, profits have an effect on leverage which at the same time determines the
debt capacity, the greater the debt capacity, the more resources the company has for
investment, which permits to financially carry out more projects. The eventual executions
of investment projects in infrastructure increases demand and consequently lowers the
energy price, such variable affects income and in this way it returns to profits (figure 4.2).
Projects
[ «@ ew
Resources
ee available to invest
“——~,
a Profits Leverage ———® Capacity
Income
Figure 4.2. Loop 1: Company-market interaction
On the other hand, the more project investments made, the higher the debt required, which
takes to a greater leverage, this leverage increases the debt capacity bringing about more
resources to invest, necessary to invest more in projects. The borrowing policy is an
exogenous variable that has an effect on the debt (figure 4.3).
Projects
Investments
Debt capacity
e>) policy
Resources to
invest ae
Debt
Leverage ———® Debt
capacity
Figure 4.3. Loop 2: Leverage dynamic
When investing in electric infrastructure, energy supply rises, which affects the perceived
market risk, this is a situation that leads to identify more investment options and the more
existing investment options, the more project investments will be made. Taking advantage
of options is the flexibility assessment of projects which directly affects investment options
(figure 4.4.).
Taking advantage of
options
Investment Options )
Projects
‘isk iS) Investments
oe ___eoort
Figure 4.4. Loop 3: Investment options dynamic
Project investments increase debt, but this one reduces resources available to invest at any
moment, as far as its handling increases as it grows, this is why a debt increment reduces
resources for investing (figure 4.5).
Projects
Investments =)
f Debt capacity
Politic
Resources
available to ns -
invest
Debt
Figure 4.5. Loop 4: Investments- debt dynamic
4.3. Market behavior
Market behavior modeling was developed based on previous studies performed by the
Universidad Nacional de Colombia along with Colciencias and Integral (Integral-UN-
Colciencias, 2000), this model is attached to this research due to the current interactions
between market and the analyzed company which play an important role thanks to the
feedback between energy prices and energy supply.
The system margin, figure 4.6, representing the difference between generation capacity and
electricity demand, affects electricity price and price then affects demand due to the
existing elasticity between these variables, forming a feedback loop. On the other hand,
electricity price and capacity margin represent incentives to invest, which affect generation
capacity and another feedback loop closes again.
Energy a
Price Incentives for
Investment
Exponential Up or Down
Balance Cycle
as
a casa System .
Generation
Margin a
We Capacity
Figure 4.6. Colombia’s energy market dynamic
Energy
Demand
When analyzing market behavior, what it is basically sought is to determine the spot market
price and the price of contracts, which are variables that depend on the offer price, on
accumulated availability, on supply-demand relation and on hydrologic scenarios, where
hydrologic conditions of El Nifio, La Nifia and a normal state are reproduced. Taking these
variables into account the market model was structured like this’:
- Demand module: It is built with scenarios determined by UPME (Energy and Mining
Planning Unit) and the legal permitted limit for a company share in a total demand.
- Hydrology module: Considers different hydrologic scenarios to determine the reservoir
operation.
- Supply module: Takes the system availabilities that have been separated by technology
(hydraulic and thermic).
- Dispatch module: Determines the energy dispatch by technologies, taking into account
the supply-demand interaction.
- Expansion module: Plans CES expansion according to three determined scenarios from
an expected mean growing of GNP.
4.4. Financial structure
3 For more details on how a market model is structured see (Integral-UN-Colciencias, 2000)..
- Debt module: In this module the debt in which the company incurs to finance its
investments is analyzed*. The following variables are taken into account:
o Leverage: The company borrowing policy for any investment project is 60% debt
financed and 40% with equity.
o Term: The debt has a 10-year term regardless the nature of the project to finance.
The system of capital disbursement by the bank is done monthly in equal quantities
to complete the debt balance amount.
o Debt payments structure: These are done every six months during 10 years, time
concession period is not considered.
0 Interests: They are done every six months at a monthly nominal rate of 5%.
- Financial statements: Allows to simulate the financial statements of the company
under study and the project to evaluate, the cash flow is modeled as well as the profit
and loss statement and the ROIC.
- Investments: This module is divided into two, the project options assessment and the
expansion or not expansion of the company.
4.5. | Options assessment process
4.5.1. Application frame
In order to initiate the option assessment it is important to gather information in an
application frame that lets clearly identify the characteristics defining the option. This
application frame constitutes the foundation on which all calculations to assess the option
will be made, therefore “in the real options method it is more important to focus on the
function of the application frame, making sure it comprehends the relevant points and gets
a current balance between a simplicity that preserves intuition and a richness that brings
about realistic and useful results” (Amram y Kulatilaka, 2000, p.131). Following, an
application frame for assessing the option of expanding a wind energy park in Colombia
will be explained in detail.
- Decision: Starting from an existent pilot project with a capacity of 20 MW, the goal is
to assess the option of expanding the wind energy park or to continue with the existent
production. The possible expansion decision is described in figure 4.7.
Possible expansion
decision
lo ly l4 I5 le ly lg Ig ho
Initially there
are 20 MW 100 MW
install
Figure 4.7. Possible expansion decision
4 All figures used in this model are expressed in thousands USD.
- Uncertainty sources:
CLASIFICATION SOURCE UNCERTAINTY
There are no previous Failure in the
Private Uncertainty ——? | experience in the country —> | implementation of this
with this type of technology. technology.
= ble hydrological Variations in the spot
nstable hydrological p | market price due to the
conditions. appearance or not of El Nifio
F phenomenon (figure 4.8).
Market Uncertainty
YY 7 High correlation between
Country $s macroeconomic energy demand and GNP
situation. behavior (figure 4.9).
320,00% +
280,00%
240,00%
200,00%
160,00%
120,00%
80,00%
40,00%
0,00%
Dic-96
Dic-97 Dic-98__ Dic-99
Dic-00
Dic-01
Dic-02
Figure 4.8. Yearly volatility of monthly energy spot price
Source: ISA.
& ok RH ON BROWS
PB Domanda Bouricidad
Cuarto Trimestre 2.37%
Mar-25
Jun-95
Sep-95
Dic-95
Mar-26
Jun-96
Sep-95
Dic-96
Mar-07
Jun-97
Sep-97
Jun-98
Mar-28
Sep-98
Dic-98
Mar-99
Jun-99
Dic-97
Sep-99
Dic-99
Mar-00
Jun-00
Sep-00
Dic-00
Mar0t
Jun-Ot
Sep-01
Jun-02
Sep-02
Dic-02
Die-01
Mar02
Figure 4.9. Evolution of energy demand vs. GNP.
Source: ISA.
4.5.2. Option to value description
Taking an existent pilot project with 20 MW of capacity, the company studied have the
option to expand its wind energy generation capacity since 3-year in 100 MW. It was used
a closed-form approximation of an American option call because the option to expand the
firm’s wind generation can be exercised at any time since 3-year up to the expiration date.
To calculate the value of the expansion option it was used a binomial approach using 12
time-step” and do not consider dividend or income lost for not exercised the option. Table
4.1 shows the inputs to this option valuation:
Table 4.1. Input to a specific option value
Element Input
Underlying asset Energy spot price®
Underlying asset value Random (23000 ,25000) USD
Time to expiration 10-years
Exercise price 100.000 USD
Underlying asset volatility _| This is not a model parameter
Risk free rate 0.0385 annual
5 In theory 12 time-step is a few number of steps, but for the paper’s purpose this steps are enough.
6 The model takes the energy spot price like the underlying asset because the cash flows of the
project are basically defined by this factor.
7 The model calculate the underlying asset volatility while the spot prices are being generated, thus,
this variable change at any time.
4.5.3. Results
For a 10 year simulation period it was found that the value of the option not exercised to
expiration’, decreases as time to develop it decreases (figure 4.10). The variability that is
present in the option price depends in high percentage on energy price volatility which is
strongly influenced by the hydrological scenario considered for its calculation, for this
reason, it is possible to observe different behaviors in the option price along the time
according to the hydrological scenario’ on which the model is developed. In figure 4.11 as
well as in 4.12, great price fluctuations of the option can be observed during almost all the
simulated period; while in figure 4.13 these changes are presented at the end of the time
horizon and in figure 4.14 the option presents a significant drop in its price at the beginning
of the period. It has a relatively stable behavior for the rest of the months maintaining low
prices.
VALUE OF THE OPTION IN TIME
-1- 130,000
-1- 108,000 4
e-1- 86,000 |
x
cl-y- 64,000 4
-;- 42,000
-4- 20,000 + +
0 50 100
Time
Figure 4.10. Option value in time under hydrological scenario #1
8 It is supposed that no competitor will not exercise the option if the analyzed company does not do
so.
° The hydrologic scenario includes the incidence of El Nifio phenomenon at any moment during a
10-year period, and the yearly seasons of summer and winter which are characteristics of the
Colombian weather.
VALUE OF THE OPTION IN TIME
130,000 —
106,000 +
82,000 +
58,000 +
34,000 +
10,000 ' '
0 50 100
Time
Figure 4.11. Option value in time under hydrological scenario #5
a=
VALUE OF THE OPTION IN TIME
130,000
106,000 +
82,000 +4
58,000 4
34,000 4
10,000 ' '
0 50 100
Time
Figure 4.12. Option value in time under hydrological scenario #3
VALUE OF THE OPTION IN TIME
-4- 130,000 -
-4- 108,000 4
S-1- 86,000 4
y
w!-;- 64,000 +
-4- 42,000 +
-4- 20,000 ' '
0 50 100
Time
Figure 4.13. Option value in time under hydrological scenario #7
VALUE OF THE OPTION IN TIME
-1- 130,000 -
-1- 106,000 +4
@-1- 82,000 4
ay
<!-4- 88,000
-4- 34,000 4
-4- 10,000 t t
0 50 100
Time
Figure 4.14. Option value in time under hydrological scenario #10
In figure 4.15 it can be clearly seen that traditional assessment (NPV) produces negative
results, then, because of this criterion the project would never be financially feasible and its
development would not be possible. However, the expanded NPV can sometimes turn the
project into an achievable investment. For example, for the hydrological scenario #1 this
occurs approximately between months 0-22 and 41-53 (figure 4.15), while in the rest of the
months the project has no financial possibilities to be carried out, because the option value
drops dramatically as the main consequence of low volatility in prices, consequently, the
option value does not reach the initial investment, that is to say, low uncertainty turns the
waiting for more information option into a non-value adding option for the project, this
behavior is seen in all hydrological scenarios, from which we can conclude that in spite of
the fact that the option price is high at the moment and is greatly valued for its future
expansion opportunities consideration, in many cases, this over information lowers the
financial possibilities of the studied project.
EXPANDED NPV VS. TRADITIONAL NPV
50,000,
1
oF
—,— EXPANDED_NPV
=~ TRADITIONAL_NPV
-50,000} phy
See
0 50 100
Time
Figure 4.15. Expanded NPV vs. Traditional NPV
In figure 4.16 it is shown the dynamics of free cash flow of the company, which does not
present considerable decrements due to the fact that the investment is not executed at any
moment of the simulation period.
At any moment it is performed, the free cash flow expansion experiments a drop, figure 19
shows this effect. When expansion is performed in month 56, a cash deficit occurs which is
immediately recuperated by the company superavit thanks to high incomes and few
expenses.
COMPANY CASH FLOW WITHOUT PROJECT
40,000,
30,0004
20,000) | melon
= \— 4 4 ‘i
Hy CAC
10,0004 | | = eRe
L_, _,—NP
% a +; a DEPRE
-10,0004
0 50 100
Time
Figure 4.16. Company cash flow without project
EXPANSION IN MONTH 56
50,000,
| =v escola
A A
0735 =a — 33 _,—FCF
vy? ~y y =p CALC
== GPC
-50,000] ac ail
—g— DEPRE
0 50 100
Time
Figure 4.17. Expansion in month 56
Lastly, it is important to mention that the analyzed option behaves according to the theory
of options.
5. CONCLUSIONS
The project assessment under real options permits to incorporate in it the option value to
expand the planted capacity of the park, which is an option that originates in the investor to
carry out the expansion depending on the market conditions, an aspect that is not
considered by the traditional methodology of assessment which supposes a deterministic
future. The assessment option adds value to the project, this fact makes sometimes the
project financially feasible, but at times can not reach this point.
From simulation of evolution of project and option value during a 10-year period, it is seen
the dynamic form in which the option value behaves in the influenced time by the
interaction between variables determining its value, based on this behavior and its market
expectations, the investor is the one who decides when to use the option and thus
renounces to obtain more information. The posterior assessment of the decision must be
done based on the available information in the moment of decision and not only based on
the obtained result.
Actually, many options inherent to the projects are influenced by several sources of
uncertainty, these options are called “rainbow options” (Damodaran, 2002, p.22) or options
which assessment process is more complex. In the case of a wind energy generation
project, besides uncertainty of spot future price of energy, there is also a failure risk of
technology operation within the interconnected national system, therefore, in future studies
it is essential to incorporate this uncertainty source within the assessment process to
observe its influence in the project value. Likewise, modular projects like the one analyzed
in this paper, enclose compounded options (Mun, 2002, p11-23) for example, expansion
options at a higher level that depend on previous execution of expansion options, for these
ones as well as for rainbow options, the assessment process is more complex. However,
those are explicit alternatives and are expected to be studied by the Colombian electrical
sector. Likewise it would be interesting to analyze investment projects of different
technologies and incorporate a decision pattern in the model which shapes the investor’s
decision process and allows to simulate the future expansion of the Colombian Electrical
sector under this methodology.
The expanded NPV is the sum of traditional NPV and the option value Net Income (NI)
which is mostly defined by the spot market price, and determines the free cash flow trend
(figure 4.16), whereas oscillations are determined by variations in work capital.
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