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ABSTRACT

This pedagogical project constructs a multi-iteration Monte Carlo model (with Oracle Crystal Ball) purposed to value the Oyu Tolgoi, LLC Copper and Gold mineral production. The analyst pursued a novel approach, using neither constant mineral pricing, nor step increments in mineral pricing. Rather, the analyst created the simulation to follow fifty to sixty-year historic patterns of inflation and individual mineral’s price volatility (Compound Annual Growth Rates: CAGR) to project future volatility (modeling inflation within the future mineral’s pricing structure). The analyst prefers this approach because inflation occurs in the real world.

The Simulation produces: 1) projected aggregate (over prospective 30-35 years) cash-flow; 2) DCF NPV projections; and finally 3) appraises the overall Oyu Tolgoi Project and apportions estimates for the principal shareholders: Erdenes MGL LLC, Rio Tinto (through its holdings in TRQ), and Turquoise Hill (TRQ excluding Rio Tinto). The model clearly shows that the Government of Mongolia is highly favored by this investment scheme. The projections suggest GoM will secure over 73% of the projected CashFlows, inclusive of Royalties, Customs charges, Taxes, and FCFE.

MONTE CARLO ANALYSISOT CASHFLOWS

What is the Monte Carlo method?

Developed by physicists in the early 20th century to account for complex interactions in quantum uncertainty; Randomly fluctuates

underlying parameters; The analysis constrains the

underlying parameters by some reasonable and justifiable measure (distribution parameters or strange attractors).

By the 1960’s economists and financial engineers had adopted the Monte Carlo method.

Merton Black Scholes options pricing model, for instance, predicts security price using a continuous lognormal distribution based upon Brownian Motion with Drift (a Monte Carlo random fluctuation, constrained to the curve parameters).

MONTE CARLO ANALYSIS

Uncertainty surrounds potential outcomes

Inflation rate; Securities prices; Commodities prices; Energy prices; Machine downtime; Productivity; Maintenance time; Etc.

Monte Carlo forces the analyst to study variables and isolate patterns (if any) to project a continuum of potential influence.

Often based upon historical data; Tuned to the analyst’s

knowledge of current news, and the behaviors of the market, the group, etc.

BENEFITS OF MONTE CARLOFOR FINANCE

Monte Carlo produces a probable range of outcome;

Some consider this superior to the traditional weighted average calculation of: Best Case; Likely Case; Worst Case scenario modeling.

Certainly, the model requires:Excellent hard data from which to draw patterns;Skill and acumen in analysis;Fine-tuning to correct for changes in trends and market behaviors;

Careful interpretation of the model projections.

BENEFITS OF MONTE CARLOFOR FINANCE

This analysis draws historical price data for the major mineral commodities OT produces: namely Cu and Au;

Price data is readily available online from a host of sources: World Bank, various universities, trade firms, etc.

This analysis isolates statistical trends (if any) among the price data;

The analyst focused on percent change in price over various intervals: moving year; 5-year; 10-year; 20-year; and 40-year; Draw basic statistics references: means, deviations, and curve shape. Oracle Crystal Ball software includes functions to isolate the particular curve

shape parameters based upon data input.

Perform an honest check for correlation;The analyst looked for correlation to a metric of inflation, in this case, the US CPI.

MONTE CARLOSTUDY OF COPPER AND GOLD PRICES

Historical StatisticsCu, Au and US CPI

Historical StatisticsCu, Au and USCPI

Historical StatisticsCu, Au and USCPI

Historical Data (1952-2013) show high correlation between the following

United States CPI and Cu Price r-Value: 0.78628United States CPI and Au Price r-Value: 0.80976CAGR US CPI and CAGR Au r-Value: 0.89198 (all years from 1955 to 2013)

Correlation analysis compelled the analyst to produce a regression equation.

MONTE CARLOSTUDY OF COPPER AND GOLD PRICES

Historical StatisticsGold and US CPI

Historical StatisticsSmoothing the Curves with Log10

The correlation and plots of the changes in price of the data suggest the following pattern:

The mean (arithmetic average) of US CPI 40-year CAGR equals 4.477% (Accounting for all years from 1952-2013) One ought to temper this view of US inflation to include the 1970’s rise of OPEC as a

factor in world economy. By the late 1970’s, this contributed to a drastic rise to US inflation; and many economists would argue that long-term US inflation is more on the order of 3.00% to 3.50%.

The mean (arithmetic average) of Cu $/lb 40-year CAGR equals 3.303% (Nominal basis and Accounting for all years from 1952-2013) In the recent past, nominal price of copper rose approximately 1.1% less than US CPI.

Fiber optic cable (reduced demand for copper in telephony) Recycled copper (mainly telephony and construction) produce a secondary source of supply.

The mean (arithmetic average) Au $/oz 40-year CAGR equals 6.725% (Nominal basis and Accounting for all years from 1952-2013) In the recent past, nominal price of gold rose approximately 2.25% higher than US CPI.

After revisions to the Bretton Woods accord, particularly after 1971, gold price corrected itself away from a forced parity relationship to USD to reflect a price more in tune with true supply and demand for gold to satisfy industrial use and requirements.

MONTE CARLOSTUDY OF COPPER AND GOLD PRICES

Problems with the correlation and parameters:

The parameters are based upon past data. A range of political entities and economic situations influenced

the unfolding of this past data. The future prices may unfold according to different parameters.

Future technology (influencing supply and demand), future consumption (demand), and future production (supply) may unfold differently than in the past 60 years, nullifying any implied or observed correlation.

Etc.

Solution to these problems?Temper the parameters by applying current knowledge and trends to improve the model.

MONTE CARLOSTUDY OF COPPER AND GOLD PRICES

1970’s-Present, telephony created drastic changes to Copper Supply and Demand.

These forces may be primarily responsible for the decrease in real (inflation-adjusted) copper price.

Hybrid Electric Vehicles and Plug-in Hybrid Electric Vehicles are again forcing a shift in Copper Demand

Electric vehicles use wound copper in the motor for the electro-magnet.

COPPER MACROECONOMICS

J.D. Power expects the compounded annual growth rate for global HEV sales between 2010 and 2020 to be 13.8%. Still, despite the expected rapid growth rate, sales are projected to be just 3.88 million units in 2020, or only 5.5% of the 70.9 million passenger vehicles to be sold by that year.

The United States is forecasted to account for 53% of the global HEV total, followed by Japan (20%) and Europe (16%), while the remaining 11% will be spread among all other countries.

(http://www.jdpower.com/sites/default/files/2010_WhitePaper_DriveGreen2020.pdf)

COPPER MACROECONOMICS

Create a cashflow budget projection;

Isolate the OT project parameters for prospective annual production, costs, taxes, and so forth; Assure that the coding for

the budget allows that revenue and costs drivers pull parameters from a variable field for dynamic calculation.

APPLYING THE MONTE CARLO MODELFOR OT

OT Production ProjectionSee "Oyu Tolgoi Project, Mongolia Integrated Development Plan" (August 2005), p. 32 and "2013

OYU TOLGOI TECHNICAL REPORT TURQUOISE HILL RESOURCES LTD." (March 2013), p. 54.

Run the Monte Carlo model, randomly fluctuating the underlying parameters;

This model runs approximately 250,000 iterations among each of several hundred variables.

Collect the results and analyze the projections.

APPLYING THE MONTE CARLO MODELFOR OT

Analysis of the existing Royalties and Taxation regime:

GoM assesses a 5% on Royalties directly out of the mineral sales;

GoM assesses a 5% Customs duty on Revenue (less CoGs) minus Treatment and Refining charges;

GoM assesses a 25% tax on EBT, following GAAP;

GoM assesses a 10% Value-Added Tax on EBT;

GoM assesses a 20% With-holding tax on EBT.

WHAT THE MODEL SHOWS FOR OT

Oyu Tolgoi has not completed financing for the lucrative underground sector of the mine:

Estimate of debt placement of $5 Billion or higher Add a debt service allocation

to the Cash Flow Projections; Amend all cash-flows to the

stakeholders; Lower the weighted average

cost of capital; thereby boosting the DCF valuation These graphics reflect a high

WACC of 12.913%, estimated solely upon equity. The debt component will reduce the WACC overall.

CONTINGENCIES AND OPEN ITEMS

This analysis is incomplete

After GoM and OT confirm the debt placement and the cost of debt, the analyst will complete a more thorough analysis of Aggregate CashFlow and Discounted Cash Flow (NPV);

Five years of hard production data will produce a greater confidence in the predictive power of the Monte Carlo analysis

The analyst is anxious (along with all stakeholders) for Mongolia’s prosperity and productivity – within all economic sectors.

FINE-TUNING THE MODEL