ID-number: 0954209 0907725 0957430 0953949 0957081
Applied Valuation Case at Handelshøyskolen BI
- Bidding for Antamina -
Hand in date 16.03.2014
Campus BI Oslo
Course code and name:
GRA 6538 – Applied valuation
Bidding for Antamina
16.03.2014
As a part of a large scale privatization process Centromin, owned by the Peruvian government, is planning to sell of one of their eleven properties; the Antamina parcel. The mine contains both copper and zinc, but the amount is uncertain. No third party is allowed to perform any on-sit feasibility studies, only outdated and superficial estimates from the government’s sides are available. Subsequently any estimates of the value of the project will be severely volatile. The auction is structured as sealed bid first order price. Furthermore, Centromin is contemplating on three different alternative auction structures: (A) forcing the winner of the auction to operate mine even when it is unfeasible for the firm, (B) allowing the company to discontinuing the operations or (C) allowing discontinuation but with a penalty. In this report we both attempt to estimate the value of the project and derive an optimal bid. (B) and (C) are real options, which have correspondence with financial options1 Submitting a bid equaling the estimated value of the project is suggested by relevant theory to result the winner’s curse. An appropriate remedy for this problem is to shave the bid down, thus yielding an optimal bid of bi*
N 1 vi vi . N
Section A should be considered as a long position in forward contract as the winner pays for the mine and have to develop it in the future. Since the NPV of project is $1335.82, the bid should be $890.55. Section (B) is a real call options as it allows for managerial flexibility as the winner of the auction has the option to discontinue if the feasibility studies reveals unsatisfying amounts of copper and zinc in the mine. The NPV of the project using the expected PV of required investment, which is $1613.78, the optimal bid is $1075.86$. Section (C) is also a real option as it gives the winner the rights to choose whether to develop the mine after 2 years and to decide the amount of investment within 5 years (invest more than commitment or invest less and paying penalty). Using the same bidding strategy, with the NPV of the project is $1613.09, the bid should be $1075.4 with $689.76 of initial payment and $601.08 of investment commitment.
1
Exhibit 1
Side 1
Bidding for Antamina
16.03.2014
A Monte Carlo simulation2 is implemented to estimate the commodity prices, which are assumed to randomly oscillate around long term trend. The computed commodity prices are further used as input in probability weighted scenario driven Discounted Cash-Flow (DCF) analysis. Three scenario, different with respect to amount of ore and extraction, are utilized. The DCF analysis is modified for the three different auction structures; where the first is the vanilla model, the second incorporates the value of managerial flexibility (making it a real option), and the last additionally included a penalty term if RTZ-CRA should decide to pull out after two years. To investigate the given real option model through reverse engineering, we have to make the relevant assumptions concerning the appropriate discount rate, probabilities of the DCF scenarios, behavior of the variables, value drivers, and uncertainty factors. Secondly, we collect the required market data and estimates for the company-specific variables. We also take into account historical trends or patterns, volatility and any other influences on the data. No need to mention that credibility of the outputs depends on the validity of the input data and the assumptions. The model uses the follow keys assumptions:
The DGP (Data Generating Process) is unbiased (no significant omitted variable bias) and efficient (parsimonious). Furthermore an adequate probability distribution needs to be chosen.
Historic parameters are good estimates of the future parameters, and they remain constant.
Uncertainty concerning the ore reserves is removed due to the 2-year exploration of the mine.
As the current model only simulates the first aforementioned pivotal risk factor and utilizes three static scenarios for the latter, one possible improvement could therefore be to simulate both risk factors with a Monte Carlo simulation. Other improvements can be taking into account risk of exchange rates, risk of inflation in Peru. Regarding the goal fulfillment of the Peruvian Government3, if they want to maximize the initial price they should utilize structure (B).However, if the goal is
2
Exhibit 3. Further, the standard normal distribution is pragmatically assumed the be the appropriate probability density function. 3 The goal is stated to be: “We obviously want to sell at an interesting price, but the principal objective is to maintain and develop the sector by attracting quality companies”
Side 2
Bidding for Antamina
16.03.2014
to insure development of the parcel, structure (A) would be implemented. The optimal structure for them will thus depend on their priorities.
Side 3
Bidding for Antamina
16.03.2014 EXHIBIT
Exhibit 1: Real options vs Financial options4 Real Option
Variable Financial Option
Present value of expected cash flows
V
Stock price Exercise price of the option
Present value of investment outlays (cost of converting the investment
I
opportunity into the option’s underlying asset) Length of deferral time
T
Time to maturity
Time value money
rf
Risk-free rate
Volatility of project’s returns
2
Variance of stock returns
Exhibit 2: Optimal bids for Antamina Structure
NPV of project
Bid
A
$1 335.82
$890.55
B
$1 613.78
$1 075.86
Calculated in the provided excel
Explanation
file
Investment Structure
NPV
Bid
Initial Payment
Commitme nt
C
Explanation
$1 613.09
$1 075.40 bi*
N 1 NPVi N
$689.76
$601.8
1 0.3(Totalbid initialpayment )
E(capital cost)
Exhibit 3: Data Generating Process Copper:
4
References: Amram, Martha, and Nalin Kulatilaka. 1999. Real Options: Managing Strategic Investment in an Uncertain World. Havard Business School Press, Cambrige, MA Trigeorgis, L. 1996. Real Options: Managerial Flexibility and Strategy in Resource Allocation. MIT Press, Cambridge, MA.
Side 4
Bidding for Antamina
16.03.2014
Zinc:
Where
are stochastically chosen Z-values
Exhibit 4: Concept behind the model Monte Carlo Simulation Determines commodity prices
Scenario driven DCF Uses input from simulation. Scenarios differ in amount of copper/zinc, life expectations and costs.
Scenario low
Scenario expected
Scenario high
NPV DCF weighted by probabilities
Structure A
Structure B
Structure C
No option to abandon
Option to abandon, no penalty
Option to abandon, with penalty
Side 5
