annual report2 (3)

7/29/2019 Annual Report2 (3)

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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


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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


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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;)


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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


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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.


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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.


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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)


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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


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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:


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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.


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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


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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).


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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.


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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


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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


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. Real option analysis requires following project data:

1. Mine life2. Lease period3. Operating costs/tonne4. Current market price of copper


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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.


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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.


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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.


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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.


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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-options


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