Upload
sudambehera
View
221
Download
2
Embed Size (px)
Citation preview
7/29/2019 Annual Report2 (3)
1/22
1
BROAD AREA OF RESEARCH-DEVELOPMENT OF A
DECISION SUPPORT SYSTEM
FOR MINING PROJECTS
FIRST ANNUAL PROGRESS REPORT (2011-2012)
Submitted by
SUDAM CHARAN BEHERA (11MI92R01)
Under the Supervision ofProf. A.BHATTACHARJEE
And
Prof. B.S.SASTRY
Department of Mining Engineering
Indian Institute of Technology
Kharagpur
7/29/2019 Annual Report2 (3)
2/22
2
1. Outline of the work done during the last one year:
I joined the Department of Mining Engineering, Indian Institute of Technology, Kharagpur
as an institute research scholar on December 29, 2011 under the supervision of Prof. A.
Bhattacharjee and Prof. B.S.Shastry. My broad area of research is Development of a
Decision Support System for a Mining Project.
1.1 Course work:
During the last one year, I have completed seven subjects of my course work as
recommended by the DSC members. The completed course works are listed below.
S.N. Subject Name Subject code L-T-P Credit Grade
1 English for Technical Writing HS63002 2-2-0 4 C
2 Society, Science and technology HS51637 3-0-0 3 B
3 Computational Geomechanics MI60004 3-1-0 4 C
4 Numerical Method for
Subsurface Environment
MI60002 3-1-0 4 C
5 Financial Engineering IM60059 3-0-0 3 A
6 Simulation of Mining Systems MI60016 3-0-0 3 B
7 Project Management BM60061 3-0-0 3 C
1.2 Technical assistantship:
I assisted Prof. B.S.Sastry and Prof. Biswajit Samant for conducting MineEnvironmental lab for B.Tech students during the autumn semester 2012.
I also assisted Prof. K.Pathak and Prof. S.K. Pal in Mining Machinery lab for B.Techstudents during the spring semester 2011-2012
7/29/2019 Annual Report2 (3)
3/22
3
2.0 INTRODUCTION
2.1 BACKGROUND
The mining industry has experienced so many ups and downs in recent timesdue to volatilities in the market, mineral commodity prices, exchange rates,
and interest rates. Due to change in world order different sets of paradigms
have been set to bring forth new challenges in mining world. Mining
sustainability, which stresses to maintain the Triple Bottom Line (TBL) has
become the central point in the mining industry after the various
deliberations on sustainable development in the different world forums since
1stUN conference on sustainable development in 1992 at Rio de janeiro and
Rio+10 at Johannesburg in 2002 and Rio+20 at Rio de janeiro in
2012(wikipedia).
The mining industry has moved to an uncertain zone since the crackdown of
the Bretton Wood agreement in 1971 and end of the gold standard era (1944
to 1971). It is a landmark system for monetary and exchange rate
management established at the United Nations Monetary and Financial
Conference held in Bretton Woods, New Hampshire in 1944(Wikipedia.2011).
The rapid fluctuations in stock market around the globe, political instabilities
in different countries, rising consciousness of environmental bodies, NGOs
and local bodies in socio-economic and environmental issues etc have
drastically changed the mindsets of mine planners and decision makers togive due attention towards the overall uncertainties and risks that play
important role in determining the mining project value.
Different techniques have been developed over time by various researchers
for the valuation of the mining project. The most popular Discounted Cash
Flow (DCF) method of project evaluation i.e. Net Present Value (NPV) has
been widely used for the valuation of mining companies across the globe
because it has following advantages:
a. Very simple to calculateb. Easy to understand
But it suffers from following limitations: (Brennan & Schwartz, 1985;
Martinez, 2009; Yeo &Qiu, 2003;)
7/29/2019 Annual Report2 (3)
4/22
4
a. Neglects time varying nature of mineral commodity prices andmanagerial flexibility in response to price variations.
b. It is static and deterministic in approach.c. It assumes that companies follow a predetermined plan irrespective of
future developments.d. It uses a single risk-adjusted discount rate for calculation of presentvalues incorporating all types of risks which is incorrect.
e. Ignores upside potential of the investment.f. Underestimates the value of the project.
The DCF evaluation method used for the mining project gives the project value
by considering a fixed set of input parameters like discount rate and cash
flows (Martinez, 2009). The important question here is whether it gives true
value for the project in an uncertain and volatile environment, the answer is
no because it doesnt consider uncertainty and flexibility in calculation ofmining projects worth. The DCF technique considers only fixed and
deterministic values of all the input parameters for the project value
calculation which is quite wrong as input parameters like commodity price,
interest rates, exchange rates etc are stochastic and dynamic in a project
changing the future cash flows over the whole project life
(DelCastillo,2012;Martinez,2009).
There is an urgent need for an effective evaluation system which can address
the issues of uncertainty and flexibility in a mining project. Real optionmethod of evaluation of project gives an efficient and viable tool in the hands
of decision makers/managers to adopt different set of options in uncertain
scenarios in order to increase the worth of the project because what is most
important at the end of the day for any mining project is survival, growth and
profitability. Real option is a dynamic, stochastic, and flexible technique which
can take most of the advantages in the uncertain and unpredictable
environment than what DCF technique fails to do because of its static and
deterministic properties.
3.0 PROBLEM STATEMENT
The mining industry is facing different sort of issues like sustainability, risk
and uncertainty, safety management system, and strategic decision making in
the period of highly volatile and turbulent market scenario. The conventional
method of project evaluation doesnt provide sufficient and accurate
7/29/2019 Annual Report2 (3)
5/22
5
estimation of future cash flows. The discounted cash flow method uses a
single time and risk adjusted discount rate for the calculation of present
values of future cash flows. It is static in approach as production sticks to the
designed plan regardless of changes in future markets. The managerial
flexibility, a dynamic concept that mine planners/mine managers can react in
response to the emerging, volatile and uncertainty situation is lacking in the
traditional valuation approach. It underestimates the project value as it
doesnt consider flexibility and uncertainty in the estimation of project value.
This approach provides no idea regarding future course of action if anything
what is assumed in the approach has gone wrong. Many mining companies
have suffered heavy losses and some of them have closed their operation in
midway when the market tumbles to a level beyond anybodys imagination.
This is the grave situation where real option can provide impetus and clearguidelines regarding what to do and what not to do.
4.0 OBJECTIVES OF THE RESEARCH
The main objective of the research work is to find a strategy to tackle the
issues of mining project evaluation under uncertainty and risk and sustainable
development and provide a decision tool to optimize the worth of the project
and increase the competitiveness in the mining sector.
The main focus areas of the present work are the following:
1. Identify, classify, and analyze various types of risk in the mining project.2. Quantification of total risk by value at risk (VaR) technique.3. Design, develop and implement an objective, comprehensive decision
support system real option analysis with Monte Carlo simulation for
the evaluation of mining project.
7/29/2019 Annual Report2 (3)
6/22
6
5.0 SCOPE OF WORK
The scope of work consists of the followings:
Literature survey of the theoretical, empirical and analytical analysis ofthe real option research specific to mining projects.
Visit to mines for the collection of mines data. Compilation of data for various sources of uncertainties and risks. Development of risk methodology for various uncertainties in a mining
project.
Estimation of historical volatilities of commodity price. Calculation of real option value based on Monte Carlo simulation. Preparation of thesis.
6.0 LITERATURE SURVEY
6.1 HISTORICAL OVERVIEW
During last 30 years a large number of literatures has been published using
real option valuation methods for the evaluation of different types of projects
basically in the mining sector. Stewart Myers (1977) coined the term Real
Options in his work Determinantsof Corporate Borrowing which draws
attention of the management personnel of various organizations. According toMyers (1977), any mining company captures the right after making final
investment decision. This right entitles the company to buy or sell a real
(physical) asset or investment plan in the future looking into the positive or
negative scenarios. The project value will be equal to the net present value
plus real option value in the highly uncertain scenarios.
Real options evolve from financial options. Its original intention was to deal
with future uncertainties of project implementation (Zheng & Zhang, 2011).
The concept of real option has generated tremendous excitement in recent
years. Amaram & Kulatilaka (1999) has applied real option theory to the
evaluation of physical assets (investments) helping managers in strategic
decision making.
7/29/2019 Annual Report2 (3)
7/22
7
The literature survey of last thirty years brings out three important
approaches in real option research, namely theoretical, managerial and
empirical. Theoretical (Dixit &Pindyck, 1994; Trigeorgis, 1997) and
managerial (Amaram &Kulatilaka, 2000; Luehrman, 1998) work on real
option strategy which considers firm or organization as a monolithic actor
while empirical work by Folta,1998; Miller & Reuer, 1998 tends to see the
investment decisions are not integrated within organizational activities.
Brennan and Schwartz (1985) have adopted the modern option pricing
techniques to evaluate natural resource investments which provided great
impetus for further research in mining projects. Dixit (1989) analyzes the
effects of uncertainty on the magnitude of hysteresis in the models with entry
and exit. Dixit and Pindyck (1996) present a detailed overview of this earlyliterature and constitute an excellent introduction to the techniques of
dynamic programming and contingent claims analysis, which are widely
applicable in the area of real options and investment under uncertainty.
Trigeorgis (2005) has introduced real option basics. He has divided Real
Options into eight categories according to the difference in flexibility it has
provided.
The 1990s provided a huge number of publications in real option application
in diverse fields which includes managing R&D projects (Pennings, 1998),natural resources investment (Trigeorgis, 1990), real estate (Williams, 1993),
energy (Kulatilaka, 1993, and Pindyck, 1993), aerospace industry (Sick, 1999),
banking (Panayi and Trigeorgis, 1998), technology adoption (Grenadier and
Weiss, 1997), merger policy (Mason and Weeds, 2002) and biotechnology
sector (Ottoo, 1998, and Woerner, 2001). Management from around the globe
has effectively applied, managed and structured uncertainty in various capital
budgeting decisions by applying an options analysis to their evaluations of the
project (Amram and Kulatilaka (1999); Copeland and Antikarov (2003); Dixitand Pindyck (1994); Luenberger (1998); Park (2006); and Trigeorgis (1996)).
Kelly(1998) used the binomial option model for the evaluation of a gold mine.
Cortazar and Casassus (1998) evaluated a Copper mine applying expand
options in their empirical work and demonstrated that the value of expansion
options was 8 to 98 percent of the total project value. Moel and Tufano(2002)
7/29/2019 Annual Report2 (3)
8/22
8
demonstrated the options of opening and closing with the help of a huge
database of 285 developed gold mines in North America operated during the
period 1988-1997. Colwell et al. (2002) applied the Brennan and Schwartz
real option model (1985) for evaluation of gold mines in Australia. Mayer and
Kazakidis (2007) used Monte Carlo simulation approach for value different
types of real options like abandonment option, sequence option etc. From the
literature survey, it is cleared that application timing of option is very
important to get the appropriate Real Option value.
6.2 RISK AND UNCERTAINTY IN THE MINING INDUSTRY
The ISO 31000(2009)/ISO Guide 73:2002 defines risk as the effect of
uncertainty on objectives. Uncertainties indicate events which may or may
not happen and caused by ambiguity or a lack of information (Wikipedia).
Risk is the probability of the uncertain future events.
Identification of risk is limited by the certainty or uncertainty of the risk. The
difference between risk and uncertainty is that risk can be represented by
random variable which has probability distribution and uncertainty cant.
Risk can be categorized into three groups: known-knowns, known-unknowns
and unknown-unknowns.
Known-known- It is a risk which is known to everybody involving littleuncertainty.
Known-unknowns-It is a risk which exists in our knowledge but notsure about its effects. This type of risk can be identified and managed.
Unknown-unknowns-This is a type of risk which is difficult to identifyand manage but requires extensive planning.
Mining project risks can be broadly classified into six categories.
Business risk Technical or operational (geological and engineering) risk Regulatory and legal risk Country risk
7/29/2019 Annual Report2 (3)
9/22
9
Market volatility risk Environmental risk
Business risks:
Business risk is the most important risks to be considered for any miningproject before taking into consideration of any other aspects. This type of risk
is generally of two types: Systematic risk (External) and unsystematic risk
Internal). Systematic risk which is called undiversified risk or market risk
depends upon macro-economic parameters like inflation, interest rate,
exchange rate, money supply etc. Unsystematic risk which is called diversified
risk or unique risk depends upon the firm specific factors like labour strike,
arrival of new competitor, introduction of new product etc.
Business risks
Systematic Risk Unsystematic Risk
Economic Natural Political Human Technological Physical
Systematic risks or external risks are influenced by the events outside of theorganization. These types of risks are come into the limelight due to three
factors:
i. Economic Factors: These are the most important causes ofsystematic risks.
ii. Natural Factors:iii. Political Factors
Business risks in a mining project can be classified into ten categories
(According to Ernst & Young, a global accounting firm, 2012-13 annual
report). These are the followings:
7/29/2019 Annual Report2 (3)
10/22
10
1. Resource Nationalism2. Skill Shortage3. Infrastructure Access4. Cost Inflation5.
Capital Project Execution6. Maintaining a Social license tooperate
7. Currency and PriceVolatility8. Capital Management Access9. Sharing the Benefits10. Fraud and Corruption
Technical and operational risk (geological and engineering risk)
i. Geological risk is attributed to the uncertainties in the geologicalcondition of the deposit like grade, continuity, volume
According to Hebblewhite (2010), mining project risks can be divided
into three levels:
Level 1: Day-to-day operational risks
Level 2: Specific site or mining condition related risks
Level 3: core risks associated with mining method or system
ii. Production risk covers extraction parameters and processingparameters
Legal and Regulatory risk: it covers changes in the regulatory system.
Country risk
Country risk can be divided into four classes:
i. Social risk: It covers wealth distribution among people, level ofpoverty, percentage of literacy, labour policy of government etc.
ii. Political risk: It covers stability of the government, policies of thegovernment relating to external trade, foreign investment, tax
regime, environment and mineral conservation.
iii. Geographical risk: It covers natural climatic conditions andinfrastructure development.
7/29/2019 Annual Report2 (3)
11/22
11
iv. Economic risk: It covers stability of domestic currency, foreignexchange restrictions etc.
Market volatility risk or economic risk:It is resulted from commodity price variations, market share variance,
supply and demand variance,
Environmental risk: It covers Environmental and land use impacts,
accident and health hazards and Economic-political-social-psychological
impacts.
6.3 REAL OPTIONS AS A STRATAGIC DECISION MAKING TOOL
According to Martinez (2010), real option analysis is a valuation and strategic
decision making tool that uses financial option pricing theory to real assets
like plants, machineries, buildings, any projects etc. In general option is a
derivative instrument which derives its value from its underlying instrument.
Option is nothing but right not the obligation to carry out transactions at a
predetermined price on or before a particular time period. Real options which
is applicable to tangible assets such as mining projects is right but not the
obligation to invest in a predetermined investment till the opportunity
disappears. Options are generally of two types: financial options and real
options .These options can be divided into two categories namely call option
and put option. A call/put option provides the right to buy/sell a share of
stock. These call/put options are two types: American options and European
options (Hull, 1958).
Comparison between financial option on a stock and real option on a mining
project (Luehrman, 2009)
Financial option Real option on mining projects
Current value of stock Present value of expected cash flows
Strike/exercise price Total investment cost
7/29/2019 Annual Report2 (3)
12/22
12
Time to expiration Time period until opportunity disappears
Risk free interest rate Risk free interest rate
According to Trigeorgis (2005), real options can be placed in eight groups.
1. defer2. Staging (compound)3. Expand4. Contract5. Temporary shut down6. Abandon7. Switching8.
Growth
According to Amram and Kulatilaka (1999), real options are of seven types.
1. Timing2. Growth3. Staging (compound)4. Exit5. Flexibility6.
Operating
7. LearningDefer option provides the option holder or buyer to wait until the
uncertainty disappears.
Broadly Real Options can be grouped into three categories
(Wikipedia)
a. Options relating to project size.b.
Options relating to project life and timing.c. Options relating to project operation.
a. Options relating to project size can be of three types: option toexpand, option to contract and option to expand or contract
(switching option).
7/29/2019 Annual Report2 (3)
13/22
13
When management is of the view that company is operating in a high
growth environment, then option to expand can be applied. That is
equivalent to call option. If it feels that the company is entering in a low
growth environment, then option to contract can be applied. This is like
a put option.
b. Options relating to project life and timing can be of three types:option to initiation or defer, option to abandon, and sequencing
options.
c. Options relating to project operation can be of three types: outputmix (product flexibility), input mix (process flexibility) and operating
scale options or intensity options.
Valuation approach for the Real options:
Real Options can be evaluated by three types of approaches:
Partial Differential Equations : Closed form Solutions using Black-Scholes Model,
Analytical Approximations Numerical Methods (e.g. Finite Difference
Method)
Binomial option pricing model
Monte Carlo Simulation.According to Sheng Baozhu et al. (2010), Real Option models can be
divided into two categories:
Discrete time models and Continuous time models.
Discrete time models are binomial option pricing model developed by Cox,
Ross, and Rubinstein (1974). Continuous time model are famous Black-
Scholes model and Monte Carlo simulation
Black-Scholes Model for Real Options:
Black-Scholes model was developed by Fisher Black, Robert Merton and
Myron Scholes in 1973 for which they got Nobel prize in 1997.
7/29/2019 Annual Report2 (3)
14/22
14
According to the Black-Scholes Model, the price or pay-off of a Real
Option at maturity in a risk neutral world has a closed form solution.
C=SN(d1)-X exp-r(T-t) N(d2)
Where C: price of real options
S: the present value of the future cash flows
X: total investment
T-t: length of time the decision to be deferred
r: risk-free rate of return
N(x): cumulative probability distribution function for standard normal
distribution
d 1: ln(S/X)+(r+2/2)(T-t)/ )1/2
d 2 = d 1-(T-t)1/2
7.0 PROPOSED METHODOLOGY
The methodology consists of followings:
1. Development of base case net present value (NPV)2. Identification, analysis and documentation of uncertainties and risks.3. Estimation of project volatilities from uncertain parameters.4. Identification of opportunities in response to different uncertainties.5. Make a synergy between uncertainties and opportunities6. Determination of real option value7. True value of the project= Base case NPV + Real Option value
Development of Base case NPV: It is the primary input to the real option
analysis. This is calculated considering risk-adjusted rate of return and
discounting the future cash flows.
Base case NPV= Future cash flows/ (1+R)^tInitial Investment
R is the hurdle rate
7/29/2019 Annual Report2 (3)
15/22
15
Identification, Analysis and Documentation of Risks and Uncertainties
i. Identifying important sources of uncertainties and risks by adoptingdifferent qualitative and quantitative techniques.
ii.
Developing relative impact on the project value.
Estimation of Project Volatilities:
There are five techniques used in estimation of volatility in real option
approach:
1. Historical volatility of underlying asset i.e mining project2. Historical volatility of the compatible assets3. Historical volatility of traded assets(companys stock price)4. Historical volatility of the industrial group index5. Monte Carlo Simulation
Opportunities: Wait for future market movements and when news is good
then apply option to expand and option to growth.
Combine uncertainties and opportunities and get the real option value.
True project value will be the summation of base case NPV and Real Optionvalue.
7.1 Case study of a copper project in India:
A Mining company is planning to invest in a copper project in India. It requires
a thorough evaluation of the project as the international market for mineral
commodities is volatile and involves different uncertainties from various
sources.In this volatile and uncertain environment, real option is the best
evaluation method for quantifying true project value
7/29/2019 Annual Report2 (3)
16/22
16
. Real option analysis requires following project data:
1. Mine life2. Lease period3. Operating costs/tonne4. Current market price of copper
7/29/2019 Annual Report2 (3)
17/22
17
5. Copper price volatility(% in yearly terms)6. Risk-free interest rate7. Risk adjusted interest rate8. Initial project investment9. Mine closure costs10. Mine lease cost for delay
8.0 Future Work
Future work will be
Collection of copper mines project data. Collection of historical copper price data for last20 years (1990-2010). Estimation of price volatility by time series analysis. Identification of risk in a project. Analysis of effect of risk on project value. Study the effect of various real options on project value Preparation of thesis.
7/29/2019 Annual Report2 (3)
18/22
18
REFERENCES
Tong, Tony W. and Reuer Jeffrey J., (2007) Real Option in Strategic Management, Journal
of Advances in Strategic Management, vol. 24, pp. 3-18.
Martinez, Luis A., and McKibben, J., (2010) Understanding Real Options in Mine Project
Valuation: A Simple Perspectives (2010), MiNiN 2010.Santiago, Chile.
Sun, Baojing and FU, XueSheng (2010) The Option Value Analysis and Application of
Uncertainty ofMining Investment Projects,2nd IEEE International Conference on
Information Management and Engineering (ICIME) pp. 411-415.
Del Castillo, Maria Fernando (2012) A Real Option Application to Manage Risk Related to
Intrinsic Variables of a Mine Plan: A Case Study on Chuquicamata U/g Project, MasterThesis, Pontificia Universdad Catolica de Chile.
Martinez, L. A., (2009) Why Accounting for Uncertainty and Risk can Improve Final
Decision-Making in Strategic Open Pit Mine Evaluation (2009), Proceedings of 2009
Project Evaluation Conference, The Australian Institute of Mining and Metallurgy, pp. 113-
124.
Rogers, J.,(2009) Strategy, Value and Risk: The Real Options Approach: Reconciling
Innovation, Strategy and Value Management, pp.141, (2009)
Li, Z. and Shao, Q. (2008) the Application of Real Option Approach in Decision Making ofMineral Resources Project Investment, The Journal of Scientific and Technological
Progress and Countermeasures, Vol. 25, No. 6, 2005.
Liao, Z., Huang, J., and Li, X. (2005) The Uncertainty of Mining Investment Project and Real
Option Analysis, Industrial Technology Economics, Vol. 24, No. 7, (2005).
Han, Hyun Jin (2000) Estimating Project Volatility and Developing Decision Support in
Real Option
Hull, J., (1989) Options, Futures and Other Derivative Securities, Prentice Hall
(Englewood Cliffs. (1989).
Gentry, D.W. & O'Neil, T.J., (1984) Mine Investment Analysis, Society for Mining,
Metallurgy, and Exploration, pp. 510.
Mun, Jonathan, (2006) Real Option Analysis: Tools and Techniques for Valuing Strategic
Investments and Decision, second edition Hoboken, New Jersey, John Wiley& Sons, 2006.
7/29/2019 Annual Report2 (3)
19/22
19
Hilli, P., Kallio, M. and Kallio, Markku,(2007) Real Option Analysis of a Technology
Portfolio, Journal of Review of Financial Economics, Vol. 16, Issue 2, pp. 127-147 (2007).
Mason, R. and Weeds, H., (2010) Investment, Uncertainty and Preemption, International
Journal of Industrial Organization, Vol. 28, Issue 3, May 2010, pp. 278-287 (2010).
Chen, T., Zhang, J. and Lai K., (2009) an Integrated Real Option Evaluating Model for
Information Technology Projects under Multiple Risks, International Journal of Project
Management, Vol. 27, Issue 5, November 2009, pp. 776-786.
Maharam, F.M., (2011) Assessing Risk for Strategy Formulation in Steel Industry through
Real Option Analysis, 7th International Strategic Management Conference, Procedia Social
and Behavioural Sciences, Vol. 24, 2011, pp. 991-1002.
Chorn, L.G., and Shokhor, S., (2006) Real Option for Risk Management in Petroleum
Development Investments, Journal of Energy Economics, Vol. 28, (2006), pp. 489-505.
Miller, Kent D. and Waller, H. Gregory (2003) Scenarios, Real Option and Integrated Risk
Management, Journal of Long Range Planning, Vol. 36, Issue 1, February 2003, pp. 93-107.
Amram, M. and Kulatilaka, N. (1999) Real Options-Managing Strategic Investment in an
Uncertain World, Boston: Harvard Business School Press, 1999.
Dixit, A. and Pindyck, R. (1993) Investment under Uncertainty, New Jersey: Princeton
University Press, 1993.
Miller, L. T. and Chan, S. P., (2002) Decision Making under Uncertainty-Real Options to the
Rescue? The Journal of the Engineering Economist, Vol. 47, Issue 2, 2002, pp. 105-150.
Jaimungal, Sebastian, de Souza, Max O., and Zubelli, Jorge P. (2011) Real Option Pricing
with Mean-Reverting Investment and Project Value, The European Journal of Finance, Vol.
0, Issue 0, pp. 1-20(2011).
Mogi, G. & Chen, F. (2007) Valuing a Multi-Product Mining Project by Compound Rainbow
Option, International Journal of Mining, Reclamation, and Environment, Vol. 20, Issue 1,
pp. 46-56(2006).
Trigeorgis, L. (2007) Real Option, Tsinghua University Press, 2007.
Smit, Han T. J. & Trigeorgis, Lenos, (2004) Strategic Investment: Real Option and Games,
Princeton University Press.
Baranouskaya, Vera (2010) Three Essays on Real Option, Ph.D Thesis, Faculty of
Economics, University of Lugano, Switzerland.
7/29/2019 Annual Report2 (3)
20/22
20
Kjaerland, Frode(2009) Valuation of Generation Assets-A Real Option Approach, Ph.D
Thesis, Bodo Graduate School of Business.
Pedersen, Jacob Kjaer(2011) Valuation of a Real Estate Development Project-A Real
Option Approach Master Thesis, Aarhus School of Business, Aarhus University.
Mbolo, Thomas Ukela (2008) Project Valuation Using Real options, Master Thesis, Swiss
Federal Institute of Technology, Zurich (2008).
Shafiee, Shahriar (2010) Integrating Economic Models in Real Option Valuation of Coal
Mining Projects, Ph.D Thesis, School of Mechanical and Mining Engineering, University of
Queensland.
Babajide, Abisoye (2007) Real Option Analysis as a tool in Oil Field Developments Master
Thesis, Tufts University, Massachusetts Institute of Technology (MIT).
Brach, Marion A. (2002) Real Options in Practice
Han, Hyun j. & Park, Chan S. (2008) A Study on Estimating Investment Timing of Real
Options, the Journal of Engineering Economist, Vol. 53, Issue 4, pp. 197-229 (2008)
Tufano, Moel and Tufano, Peter (2002) When are Real Options Exercised? An Empirical
Study of Mine Closings Review of Financial Studies, Vol. 15, No. 1, pp. 35-64.
Hall, Jason and Nicholls, Shannon (2007) Valuation of Mining Projects Using Option Pricing
Techniques, Journal of the Securities Institute of Australia, Issue 4, pp. 22-29.
Brennan, Michael J, and Schwartz, Eduardo S. (1985) Evaluating Natural Resource
Investments, The Journal of Business, Vol. 58, No. 2, pp. 135-157.
Akbari, A., Osanloo, M., & Shirazi, M. A. (2009) Reserve estimation of an open pit mine
under price uncertainty by real option approach, Mining Science and Technology, Vol. 19,
Issue 6, pp. 709-717. China University of Mining and Technology.
Hebblewhite, B. K.,(2003) Management of Geotechnical Risks in Mining Projects,
University of the New South Wales, Sydney.
Slade, Margaret E. (2000) Valuing Managerial Flexibility-An Application of Real Option
Theory to Mining Investments, The University of British Columbia.
Kodukula, Prasad and Papudesu, Chandra (2006) Project Evaluation Using Real Options-A
Practitioners Guide, J. Ross Publishing Inc., 2006.
7/29/2019 Annual Report2 (3)
21/22
21
Yeo, K. T. and Qiu, Fasheng (2003) The Value of Management Flexibility- a Real Option
Approach to Investment Evaluation, International Journal of Project Management, Vol. 21,
pp. 243-250.
Zeng, Shihong and Zhang, Shuai (2011) Real Options Literature Review, iBusiness 2011,
Vol. 3, pp. 43-48.
Kogut, Bruce and Kulatilaka, Nalin (2001) Capabilities as Real Options, School of
Management, Boston University.
Ernest & Young Annual Report on Business Risks Facing Mining and Metals - 2012-13
en.wikipadia.org/wiki/Real-Option-Valuation
Understanding Real Options,http://www.qfinance.com/business-strategy-
checklists/understanding-real-options.
Valuing Risk Projects with Real Options,
http://www.iriweb.org/Public_Site/RTM/Volume_52_Year_2009/September-
October2009RTM/Valuing_Risky_Projects_with_Real_Options.aspx
http:www.real-options.com
http://www.deruijter.net/uk/?tag=real-options
http:www.realoptions.org, Annual International Conference on Real Options: Theory Meets
Practice.
Real option Links and Resources/Information Base-v2.moneyscience.com/journal-
contents/article48
http://www.puc-rio.br/marco.ind
http://business.gov.in/growing_business/types_business.php
http://www.qfinance.com/business-strategy-checklists/understanding-real-optionshttp://www.qfinance.com/business-strategy-checklists/understanding-real-optionshttp://www.qfinance.com/business-strategy-checklists/understanding-real-optionshttp://www.qfinance.com/business-strategy-checklists/understanding-real-optionshttp://www.iriweb.org/Public_Site/RTM/Volume_52_Year_2009/September-October2009RTM/Valuing_Risky_Projects_with_Real_Options.aspxhttp://www.iriweb.org/Public_Site/RTM/Volume_52_Year_2009/September-October2009RTM/Valuing_Risky_Projects_with_Real_Options.aspxhttp://www.iriweb.org/Public_Site/RTM/Volume_52_Year_2009/September-October2009RTM/Valuing_Risky_Projects_with_Real_Options.aspxhttp://www.puc-rio.br/marco.indhttp://www.puc-rio.br/marco.indhttp://www.puc-rio.br/marco.indhttp://www.iriweb.org/Public_Site/RTM/Volume_52_Year_2009/September-October2009RTM/Valuing_Risky_Projects_with_Real_Options.aspxhttp://www.iriweb.org/Public_Site/RTM/Volume_52_Year_2009/September-October2009RTM/Valuing_Risky_Projects_with_Real_Options.aspxhttp://www.qfinance.com/business-strategy-checklists/understanding-real-optionshttp://www.qfinance.com/business-strategy-checklists/understanding-real-options7/29/2019 Annual Report2 (3)
22/22
22