commodity risk management - guide

global Risk Center

IN PRACTICE GUIDEsix stePs to assess commoditY risK exPosure

About this RepoRt

this report and the associated workbook provide guidance for companies to better

understand and quantify the impact of commodity risks on earnings in order to improve an

organizations commodity risk management.

the supporting excel workbook is available by clicking on the pushpin icon. this guide is a

companion piece to Volatility not Vulnerability published by the Association for Financial

professionals (AFp) and oliver Wyman in october 2011. the article is available by clicking on

the pushpin icon or can be found online at www.oliverwyman.com.

CoRpoRAte ChAllenges in mAnAging Commodity Risk

developing management strategies (pricing, procurement and hedging) using a holistic risk-return perspective instead of just heuristics to make decisions

evaluating portfolios of potential mitigation strategies which have impact on internal diversification and aggregation in adequate depth

Automating the aggregation and integration of a wide range of data and assumptions (e.g., purchasing contracts, commodity forecasts, ability to pass-through)

Applying sufficient tools to engage suppliers on contract terms using a risk-return perspective and to develop innovative structures that are mutually beneficial

engaging champions and senior sponsors who are passionate about implementing long-term risk mitigation strategies such as revised contract structures or pricing changes

treating commodity price risk management as a margin stabilization process rather than a cost.

Global Risk Center

VOLATILITY, NOT VULNERABILITYTO SURVIVE SWINGS IN COMMODITY PRICES, COMPANIES MUST FIRST BUILD A RISK-MANAGEMENT FRAMEWORK

Historically, most businesses could simply withstand changes in commodity prices, given that the swings were usually temporary, cyclicaland manageable. However, structural changes in the global economy are creating wilder swings in commodity prices that are not only affecting short-term profits, but also long-term planning and investment. In this environment, every company must develop a formal risk management approach to counter the growing volatility in commodity prices. For corporate leaders, this means building the infrastructure, governance programs, and analytical capabilities that can help them better manage their exposure to commodities.

1. COMMODITY PRICES AND VOLATILITY

After a brief respite in 2009, the volatility that has come to define many commodity markets

roared back in the latter half of 2010much to the dismay of businesses for whom oil,

industrial metals, and other raw materials comprise a significant share of their costs. Crude

oil cracked the psychological barrier of $100 per barrel, major food price indexes reached

record highs in the first quarter of 2011, and base and industrial metals such as copper and

aluminum also reached new highs creating significant pain for buyers (see Exhibit 1). Even

where prices pulled back, the cost of many commodities remained higher than beforethe

result of structural shifts in supply and demand on both a local and global scale (For a closer

look at the causes of volatility see Exhibit 2).

These commodity shocks are not only cutting into corporate profits but are testing the

abilities of even the best businesses to plan for and invest in the future. Already in 2011, the

CEOs of consumer-facing companies as diverse as PepsiCo, Kraft, Kimberly-Clark, and Levis

have said they expect commodity price inflation to pose a significant challenge to continued

earnings growth over the next several years. Those in the middle of the value chain have a

tougher challenge as they cannot easily raise prices to recover lost margins. Few expect this

storm to pass quickly: The 2011 World Economic Forum Global Risks Survey found corporate

executives in agreement that a key risk they face in the coming decade is extreme volatility in

energy and other commodity prices.1

1 World Economic Forum. Global Risks 2011, 6th edition, January 2011. Oliver Wyman was a contributor to that report.

EXHIBIT 1: COMMODITY PRICES ARE SOARING INDEX

8

12

10

6

4

2

0

14

MULTIPLE OF INITIAL PRICEREAL PRICE HISTORY

1987 1991 1995 2003 20111999 2007

Crude Oil

Copper

Wheat

source: Datastream, 2011

Copyright 2011 Oliver Wyman 3

ExhIBIT 2: WhY ThE VOLATILITY?

CAUSE DESCRIPTION

Erratic weather Catastrophic weather events have affected production (2009 drought in Australia affected global wheat prices)

Emerging markets Growth in emerging markets has increased demand for food, energy, and raw materials. Global food output will have to rise 70% by 2050 to meet demand* while global energy demand is predicted to increase by 36% between 2008-2035

Speculation Emergence of commodities as an investment class (development of commodities-based ETFs)

Infrastructure spending Deteriorating infrastructure in developed countries and a lack of infrastructure in emerging economies hampers the physical flow of commodities

Supply-country strategies Development of market-distorting trade policies (Russian wheat export ban followed crop shortfall in 2010)

Purchasing-country strategies

Countries developing more sophisticated buying capabilities (Korea opened a grain-trading office in Chicago in 2011)

* Food and Agriculture Organization of the United Nations, World Summit on Food Security, November 2009 International Energy Agency, World Energy Outlook 2010

This volatility could persist for years, particularly given that governments appear willing to disrupt or intervene in markets, including halting exports. These collective forces have created pressure for corporations to develop strategies to mitigate this growing risk. While companies in agri-processing, oil refining, and wholesale electricity generation have developed formal approaches to trading and risk management programs, the majority of companies need to do moremuch more.

Given the likelihood of further volatility in commodity prices, every company must adopt an analytic risk framework based on a clear understanding of its exposure. This paper offers guidance on developing a plan for managing commodity risks that draws on the best practices of companies from around the world. The approach is built around the three pillars of a best practices program: governance, infrastructure, and analytics. The paper provides an in-depth review of the role of analytics and outlines a new systematic approach to managing commodity risk, illustrated through case studies.

ONE COMPANYS MOVES TO TAME ITS VULNERABILITY TO VOLATILITY

A leading industrial company failed to deliver its projected earnings due to a decline in the profitability of non-core energy activities. To measure the companys total exposure to energy volatilityand quantify the potential effect on future profits, it needed to develop an integrated energy risk profile. In other words, the company needed the ability to aggregate the energy exposure of each business unit and evaluate the effectiveness of existing mitigation efforts before it could truly understand net exposure.

The company analyzed commodity volatilities and correlations to produce a probabilistic analysis and derive EPS-at-risk estimates, demonstrating the portion of earnings that were vulnerable to these price volatilities. It then adopted a risk assessment tool capable of performing scenario analysis linked to alternative market states and specific events, integrating this discipline by training both operational and financial staff in Treasury, Procurement, Planning, and Operations. This helped the company to gain insights into the aspects of its energy exposure that were most sensitive to price movements under different future states, and thus were targets for mitigation efforts.


2. COMMODITY RISK MANAGEMENT FRAMEWORK

DEVELOPING A COMMODITY RISK GOVERNANCE PROGRAM

A crude oil producer/marketer in Eastern Europe was recently seeking to enhance margins by creating regional physical trading capability. First, the Board required stakeholder alignment on a multi-dimensional risk appetite statement to guide risk and scale considerations. High level loss limits were linked to the risk appetite, and from these desk-level limits were calculated. By codifying the risk limits in policies, the equity usage, growth targets, and working capital requirements were made explicit and served to support all later decisions on the business expansion plan.

A structured commodity risk management framework is built around three pillars:

Governance, Infrastructure, and Analytics. Together, these pillars support both short-term tactical decisions and long-term strategic initiatives (see Exhibit 3).

GOVERNANCE

The first pillar of this framework is Governance in which an organization identifies the main

objectives of its commodity risk management program. Companies first create a risk

appetite statement. In this critical step, an organization defines its risk tolerance and

aligns it with its broader performance objectives. The risk appetite statement thus

establishes the basis of the organizations risk limits.

ExhIBIT 3: COMMODITY RISK MANAGEMENT FRAMEWORK

SHORT-TERM TACTICAL DECISION MAKING

LONG-TERM STRATEGIC DECISION MAKING

GOVERNANCE

Risk appetite and corporate objectives Risk limits Risk policy Delegations of Authority Decision frameworks

INFRASTRUCTURE

Reporting Accounting IT/systems Organizational design Human capital

ANALYTICS

Price forecasting Commodity exposure modeling Stress and scenario testing Hedge optimization


INFRASTRUCTURE

The second pillar, Infrastructure, comprises the organizational structure, systems and

human capital that companies need to measure and manage risks. Organizations need to

assess whether they have the systems to capture and monitor the necessary data flows. The

organizational structure is important because the volatility in commodity markets requires

discipline and a tight alignment between managing cost- and revenue-related risks across

the enterprise. historically, these functions worked independently, but today that results in

inefficiencies or even conflicting actions by different internal teams. human capital is also

key. In some cases, a corporation may not have the experience or capabilities to manage

commodity risks effectively. While a company can outsource risk management to financial

institutions or other market participants, it pays a significant premium for that service and

potentially forfeits any upside potential. In the process, it gives its partner proprietary

information they can use to trade for solely their own benefit.

INCREASING EFFECTIVENESS ThROUGh IMPROVED INFRASTRUCTURE

The effects of steady growth were slowly compromising the risk management effectiveness of a major North American crude and distillates marketer/trader. Reporting timeliness was eroding, error rates were climbing, and managements confidence in risk control was decreasing, prompting a full review of the organizational design and processes. This revealed that the risk control function (middle office) was still performing much of the trade reconciliation, that trade details were transmitted by email, and that most reporting was done through spreadsheets.

Several straightforward organizational shifts and systems enhancements eliminated a number of bottlenecks, and enabled risk reporting down to the cargo level, by desk and counterparty.

ANALYTICS

The third pillar of a commodity risk management program is Analytics. Organizations

cannot assess their financial exposure to commodity price swings without robust analytical

tools. These analytics (or modeling) platforms support decision making at every level

by helping managers model the future paths of commodity prices, conduct stress- and

scenario-testing, and evaluate and optimize risk-return profiles using a range of price-risk

management strategies. however, analytical capabilities vary dramatically from firm to firm.

Companies should take a sequential approach to developing a robust analytics framework

that will support commodity risk management.


ThINK LIKE A TRADER

Trading is viewed as a necessary evil by some corporations, given the connotations of excessive speculation and risk-taking with derivatives (in this case, commodity futures contracts). A recent review of annual reports reveals that many companies disclosing commodity positions caution that these are strictly for hedging purposes and that the company does not hold financial derivative positions for the purposes of trading

Whether they realize it or not, many companies are in fact speculating on commodity priceson both the cost and revenue sides. Procurement officers are tasked with getting the best price on purchases for the company and its business units. So the procurement staff commonly enters into forward, fixed-price arrangements to guarantee both supply and pricing. Just like traders, they have thus made a bet on future prices and concluded price risk management with that view in mind.

Companies need to accept that the days of a set it and forget it approach to risk management are over. That approach was fine when volatility was low and prices increased gradually over time. Today, companies need to empower designated executives to think like traders: Is this a good or bad price? Should I buy more or run down inventory? Since most companies arent traders by nature, they need to create a trading playbook that is integrated with their overall game plans.

First, a company must understand its commodity risk profile. This helps the organization

assess its net exposure to commodity pricesand their inevitable volatilityacross

business and customer segments. Detailed analysis also allows the organization to then

develop long-term strategies to mitigate commodity-related risks.

A commodity risk profile provides a common understanding for senior management and

a fact-based foundation for evaluating the effectiveness of risk-mitigation actions. With

this knowledge, management can determine if the companys current commodity risk

exposure is within its risk tolerance and whether it has communicated these expectations

to stakeholders. This analysis also helps the management team evaluate different risk

management strategies. It promotes risk mitigation at the portfolio level, which helps

reveal any risks lurking in individual business units or departments. In short, this analysis

will allow the company to optimize risk-return positioning.

ThE NET ExPOSURE ChALLENGE

Determining true net exposure requires consideration of several factors: gross commodity exposure, existing risk mitigations, foreign exchange flows, demand sensitivity and the interactions among these. This can be challenging for an enterprise with wide-spread operations or multiple product lines. Typically, each factors net impact at the corporate level is first assessed and any offsets across factors can then be accounted for.


To manage commodity price risks in ways that are consistent with broader corporate

objectives, companies need a robust set of analytic tools to calculate the current exposure.

Exhibit 4 offers a six-step analytical approach that companies can use to determine the

effect of commodity price risks and mitigation efforts on key financial metrics.

The first step in the analytical framework requires management to build a forecast

of commodity prices using simulations or other techniques. The company should

complement these forecasts with an analysis of alternative price outcomes based on stress

events to understand fully how prices may evolve.

In the second step, the management team estimates the volume of future commodity

purchases across the enterprise. In Step 3, this demand forecast is combined with

price projections to determine the firms gross commodity exposure. In Step 4, the risk

management strategies already in place are identified. Then, in Step5, these are applied

against the gross exposure to generate a net commodity exposure for the enterprise. The

process ends with Step 6, the creation of a holistic, company-wide risk profile with the

sensitivities in price projections identified in Step 1 used to explore the potential impact on

EBITDA, debt covenants, and other financial metrics.


ExhIBIT 4: CREATING A hOLISTIC COMMODITY RISK PROFILE

Use analytic engines to simulate potential commodity price pathways (data driven)

Incorporate market context and paradigm shifts/scenario analysis ( judgment driven)

Integrates historical patterns, market intelligence, and fundamental analysis

Unifies disparate views of expected and high/low commodity price scenarios across organization

Incorporates interrelationships and correlations between commodities and currencies

STEP ANALYSIS BENEFITS

Centralizes commodity requirements across business units and geographies

Enables testing of alternative commodity purchase requirements using price elasticity analysis

Determine expected commodity purchase volume based on sales expectations

Gives context of expected commodity exposure compared to P&L and other risks

Accounts for natural hedges in the portfolio

Shows shifts due to changes in business mix, commodity price expectations

Calculate expected commodity exposure (e.g., price multiplied by volume)

Brings together and coordinates dierent functions of the organization (e.g., Strategy, Procurement, Treasury) and geographies

Sets understanding of risk management options for key commodity exposures

Define options for managing commodity price risk

Centralize risk management options undertaken across organization

Helps management assess the eectiveness of the risk management portfolio vs. desired exposure

Provides understanding of how commodity price risk flows through the organization

Calculate exposure after incorporating current risk management portfolio

Enables objective evaluation and comparison of a range of risk management strategies

Promotes risk mitigation at a portfolio level to minimize sub-optimal risk mitigation at individual business unit or department level

Provides view of the earnings impact from commodity prices at dierent levels of probability

Determine impact of commodity price projections and exposure on financial metrics (e.g., EBITDA, cash flow, debt covenants)

COMMODITY PRICEPROJECTIONS

SALES, PRICING,ANDPURCHASE VOLUMES

GROSS EXPOSURE

RISK MANAGEMENTPORTFOLIO

NET EXPOSURE

HOLISTIC COMMODITYRISK PROFILE

Source: Oliver Wyman


IMPROVING COMPETIVENESS WITh A STRATEGIC RESPONSE TO COMMODITY VOLATILITY

A global food ingredient processor was losing sales to much smaller competitors solely because those firms were much more responsive to the highly volatile product price. By analyzing the impacts of its forward sales process and market price uncertainty, a new strategy was developed to migrate customers to shorter term contracts and to begin linking prices to market indices which immediately improved the firms competitive positioning.

STRATEGIES FOR MANAGING COMMODITY RISK

With a well-defined risk profile and an understanding of its ability to manage risk, a

company can build a plan that matches its net exposure to commodities with its tolerance

for risk. To manage commodity prices in the short term, companies generally have three

tools at their disposal:

Product pricing identifying customer segments where the company has the ability to raise prices or create pricing structures that mitigate risk

Procurement contract structuringdeveloping innovative risk-sharing contracts with suppliers

Financial hedgingusing financial instruments for hedging to reduce overall risk exposure

The effectiveness of these short-term strategies depends on the size of the organizations

exposure to a given commodity and the commodity itself. For example, financial hedging

works best in commodity markets that are liquid (e.g., energy products such as crude oil and

natural gas, or agricultural products such as wheat and corn). Meanwhile, passing higher

commodity costs to customers through price increases is often ineffective in competitive

markets such as consumer products. however, when commodity cost increases are

significant and widespread, pass-through pricing might be more viable. Some companies

have taken creative approaches to raising prices. For instance, a number of consumer

products companies have reduced the volume of productwhile keeping the same

package sizeto maintain margins in the face of higher commodity costs. Other firms have

substituted cheaper ingredients to lower their net product costs.

Over the long term, volatility in commodity prices affects the behaviors of consumers,

companies, and their suppliers. In response, some companiesand even countries--have

embedded commodity risk strategies into their long-term strategic plans.


CONCLUSION

Large and sustained commodity price swings are reshaping whole industries. This means

that commodity risk management can no longer be considered the sole responsibility of

the procurement or finance staff. With rising commodity prices affecting both the short-

term earnings and long-term strategies, it is imperative that C-level executives develop a

deeper understanding of how to mitigate these risks. Developing a structured commodity

risk management program built around the components outlined here is crucial. Given

the new realities of higher prices and more volatility in commodities, organizations must

integrate commodity risk management into their day-to-day operations. They also must

build it into their long-term strategies to ensure the viability of the firm itself.

ABOUT THE AUTHORS

MICHAEL J. DENTON

Partner, Global Risk & Trading, Oliver Wyman

Michael J. Denton, PhD, is a New York based Partner in Oliver Wymans Global Risk & Trading practice, with specialized experience in

energy, agriculture, and the commodities risk and trading sector. As a practitioner and as a consultant, he has worked extensively in market

risk modeling, portfolio dynamics, and risk-based decision frameworks. Recent projects have focused on due diligence evaluations,

competitive contracting, and counterparty credit risk mitigation.

ALEX WITTENBERG

Partner, Global Risk & Trading, Oliver Wyman

Alex is the Managing Partner of Oliver Wymans Global Risk Center and has over 20years of cross-industry experience in risk management

advisory and risk transfer solutions. Alex specializes in integrating risk into strategic decision-making and financial performance, designing

risk governance for Boards and Management, and developing corporate risk monitoring, mitigation and transfer frameworks.


Copyright 2011 Oliver Wyman. All rights reserved. This report may not be reproduced or redistributed, in whole or in part, without the written permission of OliverWyman and Oliver Wyman accepts no liability whatsoever for the actions of third parties in this respect.

The information and opinions in this report were prepared by Oliver Wyman.

This report is not a substitute for tailored professional advice on how a specific financial institution should execute its strategy. This report is not investment advice and should not be relied on for such advice or as a substitute for consultation with professional accountants, tax, legal or financial advisers. Oliver Wyman has made every effort to use reliable, up-to-date and comprehensive information and analysis, but all information is provided without warranty of any kind, express or implied. Oliver Wyman disclaims any responsibility to update the information or conclusions in this report. Oliver Wyman accepts no liability for any loss arising from any action taken or refrained from as a result of information contained in this report or any reports or sources of information referred to herein, or for any consequential, special or similar damages even if advised of the possibility of such damages.

This report may not be sold without the written consent of Oliver Wyman.

www.oliverwyman.com

Oliver Wyman is a leading global management consulting firm that combines deep industry knowledge with specialized expertise in strategy, operations, risk management, organizational transformation, and leadership development. Oliver Wymans Global Risk Center is dedicated to analyzing increasingly complex risks that are reshaping industries, governments, and societies. Its mission is to assist decision makers in addressing risks by combining Oliver Wymans rigorous analytical approach to risk management with leading thinking from professional associations, non-governmental organizations, and academic institutions. For further information, please visit www.oliverwyman.com/globalriskcenter.

The Association for Financial Professionals (AFP), headquartered outside Washington, D.C., serves a network of more than 16,000members with news, economic research and data, treasury certification programs, networking events, financial analytical tools, training, and public policy representation to legislators and regulators. AFP is the daily resource for the finance profession.

For more information, please contact:

MIChAEL J. DENTON

Partner, Global Risk & Trading, Oliver Wyman +1.646.364.8423 [email protected]

ALEx WITTENBERG

Partner, Global Risk & Trading, Oliver Wyman +1.646.364.8440 [email protected]

BRIAN T. KALISh

Director, Finance Practice Lead +1.301.961.6564 [email protected]

Oliver WymanFile AttachmentCommodity volatility.pdf

intRoduCtion

given the current and future trends in commodity prices and volatility, every company must

better understand its true commodity exposure. Companies can often be squeezed by

rising and volatile commodity input prices that cannot be passed along to customers in

their entirety. A commodity risk management program can help. not all organizations can,

or should, adopt the sophisticated mechanisms of a pure commodity business. however,

most organizations, particularly those in the middle of the value chain, can improve their

commodity risk analytics.

exhibit 1: CompAnies ARe ChAllenged by Rising Commodity volAtility

Output prices

Competitive pressures Limited ability to pass

through higher costs

COMPANY

Understand current forecasts (starting position and price curve)

Trace impact of price volatility to earnings

Align commodity risk management program strategy with corporate objectives

Commodity risk management program strategy, instruments, etc.

Input prices

Increasing volatility Increasing absolute price Breakdown in correlations

the starting point is to understand the companys holistic commodity risk profile using

analytics and modeling tools. A holistic commodity risk profile helps the organization assess

its individual and net exposure to commodity pricesand the inevitable volatilityacross

business and customer segments on a forward-looking basis. the profile provides a common

understanding for senior management and a fact-based foundation for evaluating the

effectiveness of current risk-mitigation actions and alternative risk management strategies.

With this knowledge, management teams can determine if current commodity risk exposure

is within the companys risk tolerance and communicate these expectations to stakeholders.

it also helps to promote risk mitigation at the portfolio level by identifying the most

important drivers of overall risk and ensuring the capture of any offsetting risks that may be

present. in short, this analysis will allow the company to optimize risk-return positioning.

this In Practice Guide provides an overview of a stepwise approach and analytic processes

necessary to develop an organizations net commodity exposure.

Copyright 2012 oliver Wyman 3

six steps to deteRmining Commodity exposuRe And impACts

exhibit 2 provides an overview of a six-step analytical approach to determine the impact of

commodity price risks on key financial metrics.

exhibit 2: six steps to CReAte A holistiC Commodity Risk pRoFile

6. HOLISTIC COMMODITY RISK PROFILE

5. NET EXPOSURE

4. RISK MANAGEMENT

PORTFOLIO

3. GROSS EXPOSURE

2. SALES, PRICING AND COMMODITY

PURCHASE VOLUMES

1. COMMODITY PRICE

PROJECTIONS

STEPS

ANALYSISUse analytic engines to simulate potential commodity price pathways (data driven)

Incorporate market context and paradigm shifts/ scenario analysis (judgement driven)

Calculate expected commodity exposure (i.e. price multiplied by volume)

Define options for managing commodity price risk

Centralize risk management options undertaken across organization

Calculate exposure after incorporating current risk management portfolio

Determine impact of commodity price projections and exposure on financial metrics (e.g. EBITDA, cash flow, debt covenants)

Determine expected commodity purchase volume based on sales expectations


step 1: Commodity pRiCe pRojeCtions

CoRe AnAlysis user-defined, baseline commodity prices and volatilities for a predefined set of commodity

inputs are incorporated into a standard simulation process to generate a distribution of

potential future price paths for each commodity

outputs A distribution of terminal price values for each commodity and time horizon

beneFits integrates historical patterns, market intelligence and fundamental analysis

unifies views of commodity price scenarios across the organization

incorporates interrelationships and correlations between commodities and other price risk factors (e.g., currencies)

the first step in the analytical framework requires

management to build assumptions for commodity

prices in the future using simulation or other techniques.

the management team should complement these

forecasts with an analysis of alternative price outcomes,

based on stress events, to understand fully how prices

may evolve.

A simple price simulation model is presented in the

attached workbook (accessed through the pushpin

icon). the inputs for these simulations are located on

the tab labeled interface under the heading price

and volatility. the user defines base case prices and

volatilities for each commodity and forward period

(i.e., 1st quarter, 2nd quarter and so on). the simulated

terminal value prices or outcomes for each commodity

and time horizon are shown on the tab labeled Cmdy

price proj. each of these values reflects possible future

outcomes for commodity prices based on three factors:

mean price, volatility and time.

the outputs of the simulations for each commodity are

summarized on the interface page in the Commodity

price projections section. in each case, 5th and 95th

percentile outcomes are shown along with the baseline

price scenario over the course of the time period to

provide a richer understanding of possible outcomes

versus a single, static forecast. not surprisingly, the

uncertainty of price forecasts grows with the increasing

time horizon.


ReadMe

Oliver Wyman: Six Steps to Assess Commodity Risk Exposure

Read Me - File Overview

Overview

The workbook has been prepared as a supplement to the In Practice Guide, "Six Steps to Assess Commodity Risk Exposure," prepared by Oliver Wyman for AFP members and available at www.afponline.org. The purpose of this workbook is to provide a simple tool for illustration purposes only to better understand and quantify commodity risk impacts on earmings. The example focuses on a corporation which utilizes key commodities including natural gas, diesel fuel, sugar, electricity and aluminum. The components of the workbook include a primary "Interface" worksheet as well as support worksheets which house the calculations used to generate outputs on the "Interface" sheet. Note that all user inputs and outputs are exclusively contained in the "Interface" sheet - all other sheets are for reference only. Cells in white in the "User Inputs" block represent input cells (prices, volatilities and hedge designation). Any changes in outputs are generated by using the "Calculate" button.

The "Interface" worksheet receives inputs and provides outputs for a probabilistic earnings forecast model and illustrates the impacts of commodity prices and volatilities on the earnings profile. In particular, each of the outputs reflects one of the steps in the 6 step process. Outputs include:

(1) Commodity price projections - User-defined, baseline commodity prices and volatilities for a pre-defined set of commodity inputs are incorporated into a standard simulation process to generate a distribution of potential future price paths for each commodity

(2) Estimated commodity volumes - A predefined set of commodity volumes reflecting commodity demand over time

(3) Gross commodity exposure - User-defined baseline prices are combined with simulated price paths and volumes to generate commodity exposure - measured as the difference between the 95th percentile worst case outcome and the baseline, expected outcome (4) Net commodity exposure - Gross commodity exposure is adjusted for any financial or physical hedges for each of the commodities. Hedges are assumed to "lock in" the commodity at the baseline, expected price. Price correlations between commodities are taken into account.

(5) Holistic commodity risk profile - Commodity exposures are combined with predefined estimates for revenues and other fixed costs/SGA to illustrate both positive and negative impacts on the earnings profile

Key assumptions

Key assumptions in the model include the following: - A GBM process is used to simulate all of the commodity price paths - Correlations are predefined and fixed resulting in a static set of shocks used in the simulation process- User defined volumes and revenues are static- User defined prices and volatiliities are used as baseline assumptions for each quarter

Interface

Oliver Wyman: Six Steps to Assess Commodity Risk Exposure

USER INPUTSRISK PROFILE OUTPUTS

Date1/1/125. Holistic commodity profile and impact on earnings (baseline, 95% confidence band, 5% confidence band)

Price and VolatilityBase5th %-ile95th %-ile

Q1Q2Q3Q42012Un hedgedHedgedImpactUn hedgedHedgedImpact

PriceVolatilityPriceVolatlityPriceVolatilityPriceVolatilityof hedgeof hedge

Sugar ($/lbs)$0.2070%$0.2170%$0.2270%$0.2370%Sales2,0692,0692,0690.02,0692,0690.0

Natural gas ($/MMBTU)$5.7348%$5.7348%$5.7348%$5.7348%Cost of Goods Sold

Electricity ($/MWh)$62.2769%$62.2769%$62.2769%$62.2769%Fixed Costs4804804800.04804800.0

Diesel ($/gal)$2.2437%$2.2437%$2.2437%$2.2437%Sugar11958580.03113110.0

Aluminum ($/KTon)$18.7832%$18.7832%$18.7832%$18.7832%Natural gas2371121120.03513510.0

Electricity24987870.03813810.0

Exposure risk level95%Diesel1551011010.01661660.0

Aluminum13191910.02482480.0

Commodity volumes (in millions)Variable Costs8924504500.01,4561,4560.0

Q1Q2Q3Q4Total COGS1,3729309300.01,9361,9360.0

Sugar (lbs)128.0134.0141.0150.0Gen. & Admin. Exp.3603603600.03603600.0

Natural gas (MMBTU)9.610.110.611.1EBITDA3377797790.0(228)(228)0.0

Electricity (MWh)1.01.01.01.0

Diesel (gal)16.016.817.618.5

Aluminum (KTon)1.61.71.81.94. Net commodity exposure 2012 by commodity (in millions $)

Other financial statement assumptions

Q1Q2Q3Q4

Sales volume (in millions)3200336035283704

Sales price ($)0.150.150.150.15

Fixed costs ($ millions)120120120120

G&A Exp ($ millions)90909090

Hedge Selection

Futures

SugarNo

Natural gasNo

ElectricityNo

DieselNo

AluminumNo

3. Gross commodity exposure 2012 (in millions $)

a) By quarterb) By commodity

All exposures reported as the difference between the 95th percentile highest exposure and the expected, baseline gross commodity exposure

2. Estimated commodity volumes for 2012 by quarters (variable units, in millions $)

1. Commodity price projections (baseline, 95% confidence band, 5% confidence band)

Interface

1

#REF!

Cmdy Price Proj

2012 Gross Exposure2012 Gross Exposure124.418764137136.7693617635264.858061148378.621793223380.3244438443

560.5736599794124.418764137SugarSugarSugarSugarSugar

423.8042982159136.7693617635Natural gasNatural gasNatural gasNatural gasNatural gas

158.9462370676264.8580611483ElectricityElectricityElectricityElectricityElectricity

80.324443844378.6217932233DieselDieselDieselDieselDiesel

080.3244438443AluminumAluminumAluminumAluminumAluminum

Invisible

Grey

Sugar

Natural gas

Electricity

Diesel

Aluminum

Correlations

0.11070873170.34527157280.2

0.08545521290.40508272140.21

0.06956460390.46167296350.22

0.0610346050.53404686860.23

5%

95%

Mean:

Sugar

Sales, Pricing, Volumes

18.594761323620.970001661238.128995505611.349690950810.5940968217

26.141084666227.820295760263.644092627215.977750784116.4064511715

34.075887859437.468427825876.165867101223.889316659523.0844682326

45.607030287850.510636516286.919105914527.40503482930.2394276185

Sugar

Natural gas

Electricity

Diesel

Aluminum

Gross Exposure

1

#REF!

EPS-at-risk

Risk Mgmt Portfolio

1

#REF!

EBITDA

Simulation Net Exposure

4.06886109037.91546800285.7310928297

3.27420301868.48557755845.7310928297

2.88870253039.26585017185.7310928297

2.667994756410.2816006245.7310928297

Diesel

Electricity

Natural gas

Crude oil

Price change

EPS impact

Invisible

Grey

Sugar

Natural gas

Electricity

Diesel

Aluminum

2012 Gross Exposure

2012 Gross Exposure

2012 Gross Exposure

2012 Gross Exposure

2012 Gross Exposure

2012 Gross Exposure

2012 Gross Exposure

Sugar

Sugar

Sugar

Sugar

Sugar

Sugar

Sugar

Natural gas

Natural gas

Natural gas

Natural gas

Natural gas

Natural gas

Natural gas

Electricity

Electricity

Electricity

Electricity

Electricity

Electricity

Electricity

Diesel

Diesel

Diesel

Diesel

Diesel

Diesel

Diesel

Aluminum

Aluminum

Aluminum

Aluminum

Aluminum

Aluminum

Aluminum

191.2572265773

113.8117311849

131.9658025171

11.406289411

116.2397994146

373.4236225276

191.2572265773

259.6118913427

113.8117311849

127.6460888256

131.9658025171

116.2397994146

11.406289411

0

116.2397994146

5%

95%

Mean:

Natural Gas

Net Exposure

34.4141498094100.399538895762.2705433902

26.4877650618125.914636017362.2705433902

21.9723962528138.435867101262.27

15.528763279149.189649304662.2705433902

5%

95%

Mean:

Electricity

Fin Statement

1.65081892052.95381393172.2444582473

1.46726970383.19551484162.2444582473

1.30747670023.60180578482.2444582473

1.19538910333.72581148132.2444582473

5%

95%

Mean:

Diesel

Price shock contuity

13.476902836925.401310513618.78

11.972165240128.427959942518.7771063122

10.634717634931.601810885918.7771063122

9.583960912434.692594532518.7771063122

5%

95%

Mean:

Aluminum

Graph support

1289.61161.6

13410.1116.81.7

14110.6117.61.8

15011.1118.51.9

Sugar

Natural gas

Electricity

Diesel

Aluminum

-16.1353539101132.656980337761.1516334878

-42.1367106558179.814703640376.0774397443

-64.2177203637214.439926492891.8591594906

-105.0874848209252.1161989213108.0153466317

95%ile

5%ile

Earnings statement

Price Simulations

Commodity prices are simulated through geometric brownian motion and utilize correlated random shocks based on an input correlation matrix

SugarNatural gasElectricityDieselAluminum

Period:Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4

Mean:0.200.210.220.235.735.735.735.7362.2762.2762.2762.272.242.242.242.2418.7818.7818.7818.78

Volatility:0.700.700.700.700.480.480.480.480.690.690.690.690.370.370.370.370.320.320.320.32

Time:0.250.500.751.000.250.500.751.000.250.500.751.000.250.500.751.000.250.500.751.00

Simulated

5%0.110.090.070.064.073.272.892.6734.4126.4921.9715.531.651.471.311.2013.4811.9710.639.58

95%0.350.410.460.537.928.499.2710.28100.40125.91138.44149.192.953.203.603.7325.4028.4331.6034.69

Std Dev:0.070.100.120.161.351.862.382.7021.0030.7437.1345.210.440.620.770.913.394.935.967.07

10.130.120.110.094.974.154.143.7955.6654.6049.5640.772.382.492.432.2720.1420.5419.9420.24

20.210.180.180.185.385.155.004.8952.3150.9045.9646.232.232.202.312.0316.1314.5014.5114.09

30.100.080.070.064.464.133.623.1848.1041.0437.0530.502.172.272.182.1215.2014.5612.6812.13

40.120.100.090.084.994.664.403.9946.7942.8941.7536.302.272.222.022.0715.6414.0713.2813.21

50.140.120.140.104.794.934.163.6150.3142.0938.3936.832.252.222.282.3614.9413.7412.5912.05

60.250.280.280.357.747.868.499.6088.4789.37105.90131.502.632.852.803.1321.4823.3223.7125.13

70.210.240.230.257.047.828.138.2795.26103.96111.49121.512.772.963.123.5017.8517.4117.4217.29

80.150.150.120.115.344.844.584.1156.9153.4852.9654.691.861.791.541.6121.0121.3422.5721.46

90.170.170.160.154.343.523.353.0936.8726.5922.0815.571.671.471.261.2015.0713.7712.4811.73

100.290.330.370.404.173.893.372.9648.6844.0838.0934.011.811.671.431.4515.3813.9412.7911.58

110.110.080.060.054.494.083.543.3447.5839.3535.2432.361.951.911.761.5318.7117.7717.9517.51

120.200.200.220.236.656.687.126.3792.15113.63138.42143.272.222.152.151.8418.7318.1818.0918.39

130.210.210.200.237.838.428.429.0788.1195.6386.8692.202.462.342.462.5421.2421.9723.0723.36

140.160.140.120.116.035.905.706.4963.0160.1058.1957.712.212.102.202.1321.3922.8122.2624.47

150.250.290.320.346.807.147.127.5581.6884.2490.9485.822.692.903.092.9919.9819.9619.6619.27

160.230.260.230.277.358.058.718.3673.1783.1985.9992.602.562.672.653.1321.5322.5522.6822.33

170.160.150.140.137.067.928.718.2894.5794.9695.57117.332.342.462.322.5417.9917.1016.4915.44

180.210.240.210.216.437.056.996.7975.4587.0678.8879.602.342.362.322.3417.9516.8216.8816.43

190.170.160.160.157.917.958.8110.53104.20128.31148.42148.802.762.943.023.0126.4530.6131.5835.17

200.120.090.080.085.455.255.324.8349.6449.7844.1837.342.522.462.402.4217.7317.9317.9215.50

210.260.280.310.339.8011.7315.3116.23129.34170.45205.68255.873.564.325.045.5521.6822.0122.2524.30

220.220.240.220.245.394.895.134.7453.2348.3940.7839.742.071.952.041.8715.2513.7412.4111.60

230.160.150.140.115.295.064.954.1457.6161.0353.6546.952.082.031.992.0120.9020.9520.8921.03

240.250.280.270.338.8910.3912.1613.04116.17153.34167.48192.962.852.883.213.1825.5928.4232.0034.67

250.220.220.230.246.176.146.416.6173.8177.4177.3473.552.011.831.811.6719.5219.9620.1719.82

260.300.400.360.476.386.466.116.4476.3183.8175.9283.002.001.861.761.7318.8118.4717.4618.05

270.150.140.120.135.054.654.224.3361.1159.4053.3848.221.701.521.311.3415.4013.7313.6812.91

280.160.130.120.124.664.374.253.6848.3743.3937.8630.722.082.032.011.7217.9018.1117.3916.86

290.110.080.060.064.223.482.902.7646.9539.9232.1327.351.741.651.421.3116.8916.4516.5815.18

300.170.160.150.145.485.134.855.0460.6660.5053.8253.142.212.272.182.0416.4014.9514.8513.75

310.160.140.130.135.515.245.044.2057.2249.4844.4240.391.961.751.621.5921.0021.3321.6323.68

320.290.300.340.384.984.433.953.4941.4732.9829.7425.121.941.791.691.5115.1713.6013.1212.09

330.230.240.270.296.786.957.247.3278.6882.3084.4384.492.552.752.652.9427.4531.4234.9238.08

340.350.400.490.547.828.439.259.7977.5578.2181.6688.652.883.073.443.3419.9720.5920.9522.39

350.120.100.090.085.515.325.654.8869.8573.6368.7261.152.122.192.012.0419.5620.3318.6618.58

360.360.510.600.747.488.219.029.0884.3988.8395.35112.482.402.482.312.4528.2031.9137.6642.38

370.180.160.150.154.313.893.383.0341.0734.3431.5725.201.871.711.511.4213.4812.0010.679.59

380.250.280.300.295.816.115.255.4758.3049.6246.8143.742.532.612.692.7022.0723.0723.3125.11

390.220.240.240.276.826.747.036.9062.8967.0761.8857.352.332.492.442.5020.9320.9122.3523.35

400.250.300.350.337.688.238.349.69101.34125.86138.76156.682.923.113.713.9223.5227.1427.5128.83

410.250.300.270.317.097.228.138.5880.6681.2890.7582.882.712.903.053.1917.2415.8216.0215.58

420.120.100.080.062.962.161.691.5123.1014.359.867.711.501.211.090.9012.5310.549.407.89

430.180.170.160.147.087.407.768.8889.39106.41100.54106.322.732.892.953.1619.3719.3219.9419.38

440.160.140.140.144.173.583.182.8843.7334.2028.9725.431.791.611.451.2818.3718.4918.1117.83

450.240.260.260.264.684.233.933.7048.2038.7834.3628.252.082.031.881.6917.2416.7217.2116.91

460.190.200.200.195.766.376.106.1065.3365.9866.6667.862.042.071.811.8119.4619.8820.7819.28

470.080.050.040.043.082.471.921.7726.3718.9814.089.721.331.050.860.7511.269.258.157.39

480.310.360.380.436.817.747.878.6057.8260.0860.5456.912.592.622.652.7218.4218.3418.0516.57

490.150.150.130.145.885.815.905.8276.1292.2983.7785.732.021.901.821.7818.3718.3318.1517.62

500.160.140.120.104.093.462.962.7334.4827.2824.3316.801.651.581.391.3413.3611.519.899.56

510.220.210.240.226.316.546.286.5665.1262.3868.6357.332.352.372.282.4521.0621.8821.7423.10

520.140.130.110.115.445.444.915.0560.0752.4348.2349.221.881.771.661.5518.5118.9917.7118.06

530.170.160.160.147.969.1910.2910.80100.35126.87125.87169.052.903.193.683.5324.3228.0429.1932.92

540.360.450.510.537.518.059.549.1170.5076.4375.1073.162.682.832.903.1721.5122.1223.6324.17

550.120.090.080.063.532.822.282.0832.6824.4619.8914.811.571.291.121.1111.559.688.496.85

560.160.140.130.144.654.093.713.3740.0430.1826.2723.062.132.122.141.9517.2316.4415.3915.73

570.350.440.570.768.689.4110.8511.27108.66146.32174.31200.892.632.922.893.1827.2333.3036.1838.36

580.250.290.280.326.117.026.647.2057.7362.8853.4657.872.242.152.012.0816.9516.0415.0114.66

590.150.150.130.116.416.946.826.7269.3270.9974.7269.622.532.832.942.8219.5519.8819.1919.87

600.130.120.100.093.702.982.752.4130.2322.3819.4714.411.421.171.000.8515.2413.7313.3511.03

610.220.240.220.257.157.767.848.4972.8180.6187.2185.622.662.762.832.8121.0421.8721.3021.21

620.130.110.110.095.695.305.074.9353.4348.9045.3441.222.322.252.352.4414.3212.8311.419.91

630.130.110.100.084.634.243.543.4638.3832.6925.4022.231.921.781.651.5919.1519.0819.5218.90

640.140.130.110.106.656.856.747.1172.5475.7782.4273.892.762.843.123.4319.0218.7717.8418.81

650.260.290.350.367.918.448.9810.0897.27109.40127.87134.833.013.353.513.7124.5828.5730.2231.26

660.160.150.150.134.564.013.763.4140.1830.1126.7321.471.671.501.311.3317.3516.3115.1413.58

670.230.230.250.287.018.298.488.1684.9590.0197.5499.792.953.153.443.7218.8119.7519.6819.60

680.140.110.100.083.622.802.372.1833.1522.2817.5713.791.721.571.391.2515.0313.5113.0910.81

690.140.140.130.124.694.564.243.9640.9532.3527.1624.692.322.182.352.1518.4617.8317.6917.59

700.190.200.190.186.406.746.706.7267.8563.0464.1961.862.502.472.472.4120.6221.7524.2124.30

710.200.210.230.226.676.777.077.5281.4683.2588.7983.412.372.412.362.4220.9322.7522.3222.74

720.190.160.170.166.456.376.816.0864.3262.6763.6455.362.763.153.093.3816.9517.3016.8917.02

730.220.240.260.267.387.888.318.6082.0685.6494.1987.043.213.623.774.4020.8223.0522.8122.63

740.120.100.090.075.064.704.364.3152.4347.5846.8739.991.941.781.621.4817.2916.0815.7416.32

750.280.300.340.397.057.268.357.9564.0867.5960.9457.392.702.863.013.2619.3719.5418.9619.22

760.230.240.210.216.827.107.217.8878.8878.5889.0083.403.003.383.603.9221.7022.1222.9524.79

770.370.430.460.537.288.468.798.4586.0383.7697.76103.682.372.492.632.6119.9421.6321.8522.64

780.250.250.240.316.757.077.647.5186.0999.4096.32111.282.602.662.672.7520.3721.1620.3320.58

790.280.300.370.385.635.385.385.3960.6964.2857.3253.822.071.981.781.6919.9720.5121.4621.50

800.210.200.240.236.246.496.346.4956.6456.2848.6248.652.492.762.772.7919.9119.7820.4220.79

810.360.490.580.756.827.638.218.2186.88100.0296.62115.952.562.632.672.7225.3928.2732.2436.03

820.250.280.270.314.594.043.603.4142.5136.5330.9027.162.182.092.132.1721.1321.3922.2021.71

830.320.400.450.585.655.345.725.1954.9250.6344.5741.352.001.891.891.7613.9512.4411.6410.68

840.200.180.180.186.246.586.936.2067.9270.8764.8668.222.292.482.402.3518.7218.5718.0017.82

850.190.190.190.185.685.054.914.7960.7756.5654.3557.572.031.831.741.6215.0313.1012.3411.58

860.250.280.290.318.229.029.0510.2796.57117.30122.87139.473.714.434.945.6721.4622.1924.3224.37

870.170.170.170.174.594.423.703.5943.5836.1029.9525.072.111.981.921.8418.5018.3418.6018.86

880.150.150.120.125.214.724.284.1056.9456.5345.9742.342.372.512.402.3717.2516.2615.7214.14

890.170.150.160.164.393.903.563.1942.0232.7829.3827.411.651.401.351.1513.0210.879.498.34

900.290.350.420.446.386.637.588.2283.6094.2797.5890.922.722.943.083.1722.9423.9226.1226.39

910.110.100.080.075.104.964.674.3256.6750.2541.5040.242.212.042.001.9320.3721.3522.3522.28

920.190.190.170.204.684.524.123.8646.8137.8434.7630.302.021.891.811.7315.5013.2512.7212.04

930.090.070.050.044.874.143.883.9254.7044.1439.9034.222.162.082.041.9719.3619.1820.1320.08

940.120.110.090.085.255.064.774.5554.6151.9741.8235.412.072.141.831.9317.4916.6416.1315.59

950.140.120.110.106.536.816.237.2087.4593.44106.28113.022.923.163.293.4723.6627.5028.0630.56

960.160.160.140.145.345.395.044.6860.8756.3760.3451.872.342.412.392.4218.2117.7717.4916.62

970.110.090.070.064.163.292.902.6836.1128.9826.2919.451.861.791.581.4815.6013.9713.3511.68

980.260.310.320.387.037.648.018.5374.6579.4079.7164.892.642.802.833.0316.7914.9614.1113.93

990.210.210.220.215.465.104.794.8958.5152.7657.8748.322.322.222.182.3717.4517.0616.6417.48

1000.160.140.120.115.715.625.945.2362.3861.4963.7563.922.612.712.852.9020.8421.4823.0222.67

Simulation of commodity prices provides a richer understanding of possible price outcomes vs. a single, static forecast. Simulations also support analysis of possible physical and/or financial hedging strategies

Disclaimer: The calculation methodology is intended to support an illustrative, high-level example of risk exposure determination. More robust and accurate methods should be used to determine forward price evolution and subsequent risk measurement and mitigation.

Correlations

Correlated random shocks generated from correlation matrix

CorrelationsSugarNatural gasElectricityDieselAluminum

Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4

SugarQ11.000.990.990.990.650.650.650.650.550.550.550.550.470.470.470.470.430.430.430.43

Q20.991.000.990.990.650.650.650.650.550.550.550.550.470.470.470.470.430.430.430.43

Q30.990.991.000.990.650.650.650.650.550.550.550.550.470.470.470.470.430.430.430.43

Q40.990.990.991.000.650.650.650.650.550.550.550.550.470.470.470.470.430.430.430.43

Nat GasQ10.650.650.650.651.000.990.990.990.940.940.940.940.860.860.860.860.690.690.690.69

Q20.650.650.650.650.991.000.990.990.940.940.940.940.860.860.860.860.690.690.690.69

Q30.650.650.650.650.990.991.000.990.940.940.940.940.860.860.860.860.690.690.690.69

Q40.650.650.650.650.990.990.991.000.940.940.940.940.860.860.860.860.690.690.690.69

ElectricityQ10.550.550.550.550.940.940.940.941.000.990.990.990.820.820.820.820.710.710.710.71

Q20.550.550.550.550.940.940.940.940.991.000.990.990.820.820.820.820.710.710.710.71

Q30.550.550.550.550.940.940.940.940.990.991.000.990.820.820.820.820.710.710.710.71

Q40.550.550.550.550.940.940.940.940.990.990.991.000.820.820.820.820.710.710.710.71

DieselQ10.470.470.470.470.860.860.860.860.820.820.820.821.000.990.990.990.660.660.660.66

Q20.470.470.470.470.860.860.860.860.820.820.820.820.991.000.990.990.660.660.660.66

Q30.470.470.470.470.860.860.860.860.820.820.820.820.990.991.000.990.660.660.660.66

Q40.470.470.470.470.860.860.860.860.820.820.820.820.990.990.991.000.660.660.660.66

AluminumQ10.430.430.430.430.690.690.690.690.710.710.710.710.660.660.660.661.000.990.990.99

Q20.430.430.430.430.690.690.690.690.710.710.710.710.660.660.660.660.991.000.990.99

Q30.430.430.430.430.690.690.690.690.710.710.710.710.660.660.660.660.990.991.000.99

Q40.430.430.430.430.690.690.690.690.710.710.710.710.660.660.660.660.990.990.991.00

ColumnCCCCGGGG0.0KKK0.0OOOSSSS

Indirect:C_Prices!0.00.0

CorrelatedSugarNatural gasElectricityDieselAluminum

N(0,1)Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4

1(1.08)(0.92)(0.82)(1.07)(0.47)(0.78)(0.57)(0.62)(0.15)(0.03)(0.08)(0.27)0.410.520.410.220.520.510.360.39

20.31(0.07)(0.06)(0.03)(0.15)(0.14)(0.12)(0.09)(0.33)(0.17)(0.21)(0.09)0.050.050.26(0.09)(0.87)(1.03)(0.79)(0.74)

3(1.76)(1.67)(1.59)(1.55)(0.92)(0.79)(0.90)(0.98)(0.58)(0.61)(0.57)(0.69)(0.09)0.180.070.02(1.24)(1.01)(1.28)(1.21)

4(1.34)(1.19)(1.12)(1.22)(0.46)(0.44)(0.43)(0.52)(0.66)(0.52)(0.37)(0.44)0.160.09(0.16)(0.03)(1.06)(1.16)(1.11)(0.94)

5(0.75)(0.80)(0.49)(0.77)(0.63)(0.28)(0.57)(0.72)(0.45)(0.56)(0.51)(0.42)0.110.100.210.32(1.35)(1.27)(1.30)(1.23)

60.820.820.720.951.371.101.151.321.190.981.191.430.951.040.851.080.921.070.981.07

70.350.500.380.440.981.081.051.001.401.291.271.311.231.191.191.39(0.24)(0.22)(0.13)(0.10)

8(0.56)(0.44)(0.76)(0.66)(0.17)(0.33)(0.33)(0.45)(0.09)(0.07)0.030.16(0.91)(0.74)(1.02)(0.71)0.780.680.800.58

9(0.25)(0.15)(0.23)(0.27)(1.04)(1.27)(1.09)(1.05)(1.35)(1.50)(1.44)(1.66)(1.49)(1.48)(1.65)(1.51)(1.30)(1.26)(1.34)(1.31)

101.261.161.151.12(1.20)(0.97)(1.07)(1.14)(0.54)(0.46)(0.52)(0.53)(1.07)(0.99)(1.25)(0.99)(1.17)(1.20)(1.25)(1.35)

11(1.66)(1.82)(1.73)(1.74)(0.90)(0.83)(0.95)(0.89)(0.61)(0.70)(0.65)(0.60)(0.66)(0.48)(0.61)(0.84)0.06(0.13)(0.02)(0.06)

120.140.140.340.340.740.620.730.461.311.481.641.550.03(0.03)0.02(0.35)0.06(0.03)0.000.10

130.340.280.110.351.421.301.131.201.181.120.860.910.600.300.440.520.850.810.880.84

14(0.48)(0.59)(0.63)(0.68)0.330.260.200.500.210.170.190.230.01(0.12)0.090.050.890.970.750.99

150.790.910.900.910.830.820.730.810.960.860.930.811.071.121.150.960.470.380.300.24

160.580.710.340.591.161.171.221.030.640.840.840.920.810.800.681.080.930.920.820.70

17(0.46)(0.41)(0.43)(0.48)0.991.121.211.011.381.111.021.260.310.490.270.52(0.19)(0.30)(0.33)(0.45)

180.300.520.250.240.600.780.680.590.730.930.690.700.310.330.260.30(0.20)(0.37)(0.24)(0.26)

19(0.34)(0.31)(0.25)(0.26)1.461.141.241.511.661.731.751.611.211.161.080.972.222.272.012.12

20(1.19)(1.38)(1.36)(1.14)(0.09)(0.09)0.03(0.12)(0.48)(0.21)(0.28)(0.40)0.730.480.370.39(0.28)(0.09)(0.03)(0.44)

210.920.810.850.852.362.282.572.412.292.312.302.392.592.642.692.630.980.820.750.97

220.470.520.310.42(0.14)(0.30)(0.06)(0.16)(0.28)(0.27)(0.41)(0.31)(0.35)(0.40)(0.14)(0.31)(1.22)(1.27)(1.35)(1.34)

23(0.43)(0.47)(0.46)(0.69)(0.21)(0.19)(0.14)(0.44)(0.05)0.200.05(0.06)(0.32)(0.25)(0.21)(0.12)0.750.600.520.51

240.820.830.640.891.951.922.021.951.982.091.951.981.381.091.281.132.011.942.062.08

250.390.300.350.390.420.370.480.540.670.690.660.59(0.50)(0.65)(0.51)(0.61)0.320.380.400.33

261.301.571.131.380.570.520.360.480.760.850.630.76(0.53)(0.58)(0.61)(0.52)0.090.04(0.12)0.04

27(0.63)(0.63)(0.67)(0.46)(0.41)(0.45)(0.53)(0.35)0.120.150.04(0.03)(1.40)(1.36)(1.52)(1.20)(1.16)(1.27)(1.01)(1.01)

28(0.51)(0.67)(0.68)(0.58)(0.75)(0.63)(0.51)(0.68)(0.56)(0.50)(0.53)(0.68)(0.31)(0.25)(0.19)(0.53)(0.22)(0.05)(0.14)(0.18)

29(1.65)(1.63)(1.76)(1.55)(1.15)(1.30)(1.43)(1.28)(0.65)(0.67)(0.81)(0.85)(1.28)(1.05)(1.26)(1.27)(0.58)(0.47)(0.31)(0.50)

30(0.29)(0.31)(0.29)(0.32)(0.07)(0.16)(0.19)(0.03)0.100.180.050.120.010.170.07(0.07)(0.77)(0.89)(0.71)(0.81)

31(0.40)(0.55)(0.58)(0.43)(0.04)(0.09)(0.10)(0.41)(0.07)(0.23)(0.27)(0.28)(0.65)(0.82)(0.86)(0.75)0.780.680.650.89

321.230.981.021.05(0.47)(0.59)(0.69)(0.79)(1.01)(1.06)(0.94)(0.97)(0.69)(0.74)(0.72)(0.89)(1.25)(1.31)(1.15)(1.22)

330.570.520.660.700.820.740.770.750.850.820.810.790.790.900.680.912.452.392.382.37

341.741.561.621.561.421.311.361.350.810.710.750.861.431.331.501.260.460.520.530.71

35(1.21)(1.27)(1.11)(1.22)(0.04)(0.05)0.18(0.09)0.510.590.460.32(0.21)0.03(0.18)(0.08)0.340.460.120.13

361.872.051.952.031.231.231.301.201.050.971.011.200.460.510.250.422.622.462.652.70

37(0.19)(0.31)(0.29)(0.29)(1.06)(0.97)(1.06)(1.08)(1.03)(0.98)(0.84)(0.97)(0.90)(0.92)(1.07)(1.06)(1.99)(1.87)(1.90)(1.94)

380.800.800.810.690.180.36(0.01)0.14(0.02)(0.22)(0.18)(0.17)0.740.710.730.691.091.020.921.07

390.400.530.440.580.850.650.700.630.200.400.290.230.290.530.420.470.760.590.770.84

400.851.001.080.891.341.231.111.331.581.691.641.681.511.381.731.691.491.741.521.50

410.820.970.610.761.010.851.051.080.920.790.930.761.111.111.121.13(0.45)(0.64)(0.44)(0.42)

42(1.23)(1.34)(1.35)(1.47)(2.63)(2.71)(2.74)(2.54)(2.70)(2.76)(2.79)(2.68)(2.10)(2.23)(2.08)(2.27)(2.45)(2.44)(2.36)(2.55)

43(0.16)(0.18)(0.18)(0.34)1.000.920.941.151.221.341.101.121.151.091.021.110.270.240.350.26

44(0.48)(0.52)(0.42)(0.35)(1.20)(1.22)(1.21)(1.19)(0.85)(0.98)(0.98)(0.95)(1.12)(1.15)(1.20)(1.32)(0.06)0.050.01(0.00)

450.690.670.590.54(0.73)(0.73)(0.70)(0.67)(0.57)(0.73)(0.70)(0.80)(0.33)(0.26)(0.39)(0.57)(0.45)(0.40)(0.18)(0.17)

460.050.110.130.050.140.480.360.370.310.360.410.47(0.43)(0.18)(0.52)(0.39)0.300.370.500.24

47(2.35)(2.56)(2.32)(2.22)(2.47)(2.31)(2.42)(2.21)(2.32)(2.19)(2.19)(2.35)(2.72)(2.77)(2.82)(2.78)(3.12)(3.01)(2.87)(2.75)

481.431.311.191.260.841.060.971.08(0.04)0.170.250.210.870.720.670.71(0.04)0.01(0.00)(0.23)

49(0.63)(0.45)(0.54)(0.35)0.230.210.280.270.751.050.800.81(0.48)(0.52)(0.49)(0.45)(0.06)0.010.02(0.04)

50(0.55)(0.60)(0.66)(0.79)(1.29)(1.32)(1.38)(1.30)(1.54)(1.45)(1.27)(1.55)(1.57)(1.21)(1.33)(1.21)(2.05)(2.05)(2.17)(1.95)

510.390.280.440.310.520.560.430.520.300.250.460.230.350.340.220.420.790.790.670.81

52(0.87)(0.75)(0.88)(0.67)(0.09)0.02(0.16)(0.02)0.07(0.11)(0.13)0.00(0.87)(0.77)(0.79)(0.81)(0.01)0.16(0.07)0.04

53(0.32)(0.24)(0.25)(0.35)1.491.561.611.561.561.701.481.791.481.471.701.411.701.881.731.91

541.861.791.681.551.241.171.431.210.530.660.610.581.061.010.951.120.930.840.970.95

55(1.35)(1.44)(1.37)(1.50)(1.90)(1.92)(2.01)(1.88)(1.70)(1.67)(1.61)(1.74)(1.85)(1.99)(2.01)(1.71)(2.96)(2.81)(2.73)(2.99)

56(0.52)(0.51)(0.58)(0.40)(0.75)(0.83)(0.84)(0.87)(1.11)(1.24)(1.15)(1.09)(0.19)(0.09)0.02(0.19)(0.46)(0.47)(0.58)(0.39)

571.731.741.862.061.851.631.741.651.791.992.022.040.951.130.951.132.402.642.512.39

580.760.870.720.840.390.770.560.72(0.05)0.260.040.240.08(0.04)(0.18)(0.02)(0.56)(0.58)(0.67)(0.61)

59(0.72)(0.37)(0.56)(0.72)0.590.730.630.570.480.510.600.510.741.021.000.800.330.370.220.34

60(1.09)(0.93)(1.04)(1.06)(1.70)(1.75)(1.56)(1.56)(1.92)(1.85)(1.65)(1.78)(2.38)(2.34)(2.37)(2.43)(1.22)(1.27)(1.09)(1.50)

610.440.480.320.471.041.060.961.060.630.770.860.811.020.920.890.800.790.790.590.54

62(1.05)(1.01)(0.86)(0.94)0.09(0.06)(0.09)(0.07)(0.27)(0.25)(0.23)(0.25)0.260.150.300.41(1.61)(1.57)(1.66)(1.84)

63(0.95)(1.03)(1.05)(1.22)(0.77)(0.72)(0.95)(0.81)(1.23)(1.08)(1.20)(1.15)(0.77)(0.75)(0.81)(0.75)0.200.180.280.18

64(0.79)(0.70)(0.83)(0.86)0.740.700.600.690.620.650.770.591.211.031.191.330.160.11(0.05)0.17

650.960.931.060.971.461.311.291.421.471.401.501.461.691.661.561.541.761.971.861.75

66(0.49)(0.46)(0.37)(0.42)(0.84)(0.88)(0.81)(0.84)(1.10)(1.25)(1.12)(1.20)(1.49)(1.40)(1.51)(1.24)(0.42)(0.51)(0.64)(0.85)

670.610.450.520.640.961.261.150.981.071.001.051.031.571.421.501.550.090.340.310.29

68(0.85)(1.14)(1.00)(1.17)(1.80)(1.94)(1.92)(1.78)(1.65)(1.86)(1.82)(1.84)(1.35)(1.23)(1.34)(1.40)(1.31)(1.34)(1.16)(1.57)

69(0.84)(0.62)(0.57)(0.60)(0.71)(0.50)(0.52)(0.53)(1.04)(1.10)(1.09)(1.00)0.280.020.310.08(0.03)(0.12)(0.08)(0.04)

70(0.02)0.110.070.020.580.650.580.570.420.270.350.340.690.500.450.370.660.761.060.97

710.230.240.350.270.750.660.710.810.950.840.890.770.390.400.320.390.760.960.760.76

72(0.05)(0.26)(0.08)(0.13)0.610.480.620.360.270.260.340.171.211.431.161.29(0.56)(0.25)(0.24)(0.15)

730.480.500.560.531.181.111.101.090.970.900.990.832.031.961.782.000.721.020.840.74

74(1.19)(1.22)(1.10)(1.37)(0.40)(0.41)(0.45)(0.36)(0.33)(0.31)(0.18)(0.30)(0.71)(0.76)(0.86)(0.93)(0.44)(0.57)(0.50)(0.28)

751.140.951.031.100.980.871.110.920.260.410.260.231.091.061.081.200.270.290.170.23

760.570.480.220.220.850.800.760.900.860.720.900.771.671.691.631.690.980.840.861.03

771.901.711.521.551.121.321.241.051.110.851.051.080.400.530.650.590.460.740.690.75

780.770.590.480.770.800.790.900.801.111.201.031.190.890.770.700.730.590.640.420.45

791.181.001.161.070.05(0.02)0.060.110.100.310.160.13(0.33)(0.34)(0.56)(0.59)0.460.500.620.58

800.330.170.450.320.470.530.450.50(0.10)0.04(0.12)(0.01)0.660.930.820.770.450.340.440.48

811.821.971.902.050.851.011.070.991.141.221.031.250.810.730.710.711.971.922.092.20

820.760.810.620.78(0.80)(0.86)(0.91)(0.84)(0.93)(0.85)(0.87)(0.86)(0.06)(0.14)(0.00)0.090.820.690.740.61

831.561.531.471.660.06(0.04)0.200.03(0.19)(0.18)(0.26)(0.25)(0.52)(0.52)(0.37)(0.48)(1.78)(1.71)(1.59)(1.60)

840.17(0.10)(0.00)0.030.480.580.660.400.420.510.370.480.200.520.370.300.060.06(0.01)(0.00)

850.060.070.06(0.00)0.09(0.20)(0.17)(0.13)0.100.050.070.23(0.45)(0.64)(0.63)(0.69)(1.31)(1.48)(1.38)(1.35)

860.780.800.760.771.621.501.311.451.441.541.441.512.812.732.622.690.910.851.070.97

87(0.34)(0.19)(0.10)(0.11)(0.80)(0.60)(0.85)(0.74)(0.86)(0.87)(0.93)(0.97)(0.24)(0.34)(0.33)(0.36)(0.01)0.010.100.17

88(0.70)(0.46)(0.64)(0.58)(0.28)(0.40)(0.49)(0.46)(0.09)0.05(0.21)(0.21)0.380.560.360.33(0.45)(0.52)(0.50)(0.73)

89(0.31)(0.37)(0.25)(0.13)(0.99)(0.97)(0.94)(0.98)(0.97)(1.07)(0.96)(0.84)(1.58)(1.67)(1.44)(1.63)(2.21)(2.30)(2.32)(2.38)

901.231.301.361.280.570.600.880.991.031.091.050.891.121.161.151.121.331.181.331.22

91(1.46)(1.26)(1.33)(1.32)(0.37)(0.26)(0.29)(0.35)(0.10)(0.20)(0.38)(0.29)0.00(0.24)(0.20)(0.22)0.590.680.770.69

92(0.01)0.07(0.09)0.18(0.73)(0.53)(0.58)(0.58)(0.65)(0.78)(0.68)(0.70)(0.48)(0.52)(0.51)(0.52)(1.12)(1.43)(1.27)(1.23)

93(2.26)(2.02)(2.25)(2.16)(0.56)(0.79)(0.73)(0.55)(0.20)(0.46)(0.45)(0.52)(0.11)(0.17)(0.14)(0.16)0.270.210.390.37

94(1.31)(1.13)(1.12)(1.15)(0.25)(0.19)(0.23)(0.24)(0.21)(0.13)(0.37)(0.47)(0.34)(0.05)(0.48)(0.23)(0.37)(0.42)(0.41)(0.42)

95(0.87)(0.84)(0.91)(0.90)0.660.680.410.721.161.081.191.211.521.441.361.361.521.801.591.68

96(0.42)(0.35)(0.40)(0.38)(0.18)(0.01)(0.10)(0.18)0.110.040.250.080.310.400.350.39(0.11)(0.13)(0.12)(0.22)

97(1.51)(1.57)(1.67)(1.62)(1.22)(1.47)(1.43)(1.34)(1.41)(1.32)(1.14)(1.34)(0.93)(0.74)(0.93)(0.93)(1.08)(1.19)(1.09)(1.32)

980.961.010.911.090.971.021.011.070.700.740.710.400.970.980.890.99(0.62)(0.89)(0.89)(0.77)

990.330.280.290.21(0.08)(0.17)(0.22)(0.09)(0.01)(0.10)0.18(0.02)0.270.080.070.33(0.38)(0.31)(0.30)(0.06)

100(0.55)(0.51)(0.66)(0.67)0.110.110.290.050.180.220.340.380.910.850.910.880.730.710.870.75

Correlations among commodity prices dictate the way in which commodity prices move together and are used to develop commodity price projections via simulation


Sales, Pricing and Volumes

all figures in millions (except prices)Q1Q2Q3Q42012

Sales480.00504.00529.20555.602,068.80

Volume3,200.003,360.003,528.003,704.0013,792.00

Price ($)0.150.150.150.150.16

0.00

Cost of Commodity Goods Sold328.85337.92347.34357.581,371.70

Fixed Costs120.00120.00120.00120.00480.00

Sugar ($)25.6028.1431.0234.50119.26

Volume (lb)128.00134.00141.00150.00

($/lb)0.200.210.220.23

0.00

Natural gas ($)55.0257.8860.7563.62237.27

Volume (MMBTU)9.6010.1010.6011.10

Price ($/MMBTU)5.735.735.735.73

0.00

Electricity ($)62.2762.2762.2762.27249.08

Volume1.001.001.001.00

Price62.2762.2762.2762.27

0.00

Diesel ($l)35.9137.7139.5041.52154.64

Volume16.0016.8017.6018.50

Price2.242.242.242.24

0.00

Aluminum ($)30.0531.9233.8035.68131.44

Volume1.601.701.801.90

Price18.7818.7818.7818.78

Variable Costs208.85217.92227.34237.58891.70

Commodity volumes may be determined by reviewing sales and demand planning forecasts. Volumes may be aggregated when sourced from different business divisions or regions to arrive at a corporate-wide volume estimate.

Gross exposure calculations

Gross Exposure

all figures in millions (except prices)Q1Q2Q3Q4Q1Q2Q3Q4Total

Simulated commodity costs

Sugar44.254.365.180.118.626.134.145.6124.4

Volume (lbs)128.0134.0141.0150.0

Price0.350.410.460.53

0.00.00.00.00.0

Natural gas76.085.798.2114.121.027.837.550.5136.8

Volume (MMBTU)9.610.110.611.1

Price7.928.499.2710.28

0.00.00.00.00.0

Electricity100.4125.9138.4149.238.163.676.286.9264.9

Volume (MWh)1.01.01.01.0

Price100.4125.9138.4149.2

0.00.00.00.00.0

Diesel47.353.763.468.911.316.023.927.478.6

Volume (gal)16.016.817.618.5

Price2.953.203.603.73

0.00.00.00.00.0

Aluminum40.648.356.965.910.616.423.130.280.3

Volume (tons)1.61.71.81.9

Price25.4028.4331.6034.69

Total308.5367.9422.0478.399.6150.0194.7240.7685.0

Risk management portfolio

FuturesDescription

SugarFutures or OTC contracts may be used to "lock in" or fix commodity prices for defined periods of time

Natural gasFutures or OTC contracts may be used to "lock in" or fix commodity prices for defined periods of time

ElectricityFutures or OTC contracts may be used to "lock in" or fix commodity prices for defined periods of time

DieselFutures or OTC contracts may be used to "lock in" or fix commodity prices for defined periods of time

AluminumFutures or OTC contracts may be used to "lock in" or fix commodity prices for defined periods of time

Correlated Price Simulations

Commodity prices are simulated through geometric brownian motion and utilize correlated random shocks based on an input correlation matrix

SugarNatural gasElectricityDieselAluminumTotal Net Exposure

Period:Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Q1Q2Q3Q4Full-Year

Mean:0.200.210.220.235.735.735.735.7362.2762.2762.2762.272.242.242.242.2418.7818.7818.7818.78

Volatility:0.700.700.700.700.480.480.480.480.690.690.690.690.370.370.370.370.320.320.320.32

Time:0.250.500.751.000.250.500.751.000.250.500.751.000.250.500.751.000.250.500.751.00

Volume:128.00134.00141.00150.009.6010.1010.6011.101.001.001.001.0016.0016.8017.6018.501.601.701.801.90

Simulated

5%0.140.110.100.083.622.802.372.1833.1522.2817.5713.791.721.571.391.2515.0313.5113.0910.81487.15

95%0.360.510.600.747.488.219.029.0884.3988.8395.35112.482.402.482.312.4528.2031.9137.6642.381457.22

Std Dev:0.070.100.120.161.351.862.382.7021.0030.7437.1345.210.440.620.770.913.394.935.967.07

Mean:

Net ExposureNet Portfolio Exposure

323.80470.080.050.040.043.082.471.921.7726.3718.9814.089.721.331.050.860.7511.269.258.157.39323.80

339.48420.120.100.080.062.962.161.691.5123.1014.359.867.711.501.211.090.9012.5310.549.407.89339.48

399.48550.120.090.080.063.532.822.282.0832.6824.4619.8914.811.571.291.121.1111.559.688.496.85399.48

435.42600.130.120.100.093.702.982.752.4130.2322.3819.4714.411.421.171.000.8515.2413.7313.3511.03435.42

449.77680.140.110.100.083.622.802.372.1833.1522.2817.5713.791.721.571.391.2515.0313.5113.0910.81449.77

489.11500.160.140.120.104.093.462.962.7334.4827.2824.3316.801.651.581.391.3413.3611.519.899.56489.11

498.24970.110.090.070.064.163.292.902.6836.1128.9826.2919.451.861.791.581.4815.6013.9713.3511.68498.24

526.1490.170.170.160.154.343.523.353.0936.8726.5922.0815.571.671.471.261.2015.0713.7712.4811.73526.14

542.47890.170.150.160.164.393.903.563.1942.0232.7829.3827.411.651.401.351.1513.0210.879.498.34542.47

544.67290.110.080.060.064.223.482.902.7646.9539.9232.1327.351.741.651.421.3116.8916.4516.5815.18544.67

560.81370.180.160.150.154.313.893.383.0341.0734.3431.5725.201.871.711.511.4213.4812.0010.679.59560.81

569.50660.160.150.150.134.564.013.763.4140.1830.1126.7321.471.671.501.311.3317.3516.3115.1413.58569.50

587.40440.160.140.140.144.173.583.182.8843.7334.2028.9725.431.791.611.451.2818.3718.4918.1117.83587.40

592.33630.130.110.100.084.634.243.543.4638.3832.6925.4022.231.921.781.651.5919.1519.0819.5218.90592.33

602.39110.110.080.060.054.494.083.543.3447.5839.3535.2432.361.951.911.761.5318.7117.7717.9517.51602.39

603.1630.100.080.070.064.464.133.623.1848.1041.0437.0530.502.172.272.182.1215.2014.5612.6812.13603.16

616.64560.160.140.130.144.654.093.713.3740.0430.1826.2723.062.132.122.141.9517.2316.4415.3915.73616.64

652.6940.120.100.090.084.994.664.403.9946.7942.8941.7536.302.272.222.022.0715.6414.0713.2813.21652.69

652.73920.190.190.170.204.684.524.123.8646.8137.8434.7630.302.021.891.811.7315.5013.2512.7212.04652.73

657.64690.140.140.130.124.694.564.243.9640.9532.3527.1624.692.322.182.352.1518.4617.8317.6917.59657.64

658.76930.090.070.050.044.874.143.883.9254.7044.1439.9034.222.162.082.041.9719.3619.1820.1320.08658.76

660.78870.170.170.170.174.594.423.703.5943.5836.1029.9525.072.111.981.921.8418.5018.3418.6018.86660.78

661.16740.120.100.090.075.064.704.364.3152.4347.5846.8739.991.941.781.621.4817.2916.0815.7416.32661.16

665.62280.160.130.120.124.664.374.253.6848.3743.3937.8630.722.082.032.011.7217.9018.1117.3916.86665.62

667.8150.140.120.140.104.794.934.163.6150.3142.0938.3936.832.252.222.282.3614.9413.7412.5912.05667.81

682.44270.150.140.120.135.054.654.224.3361.1159.4053.3848.221.701.521.311.3415.4013.7313.6812.91682.44

692.90940.120.110.090.085.255.064.774.5554.6151.9741.8235.412.072.141.831.9317.4916.6416.1315.59692.90

697.01320.290.300.340.384.984.433.953.4941.4732.9829.7425.121.941.791.691.5115.1713.6013.1212.09697.01

707.96100.290.330.370.404.173.893.372.9648.6844.0838.0934.011.811.671.431.4515.3813.9412.7911.58707.96

712.22620.130.110.110.095.695.305.074.9353.4348.9045.3441.222.322.252.352.4414.3212.8311.419.91712.22

712.61450.240.260.260.264.684.233.933.7048.2038.7834.3628.252.082.031.881.6917.2416.7217.2116.91712.61

727.02910.110.100.080.075.104.964.674.3256.6750.2541.5040.242.212.042.001.9320.3721.3522.3522.28727.02

737.34200.120.090.080.085.455.255.324.8349.6449.7844.1837.342.522.462.402.4217.7317.9317.9215.50737.34

738.01520.140.130.110.115.445.444.915.0560.0752.4348.2349.221.881.771.661.5518.5118.9917.7118.06738.01

741.08880.150.150.120.125.214.724.284.1056.9456.5345.9742.342.372.512.402.3717.2516.2615.7214.14741.08

743.1710.130.120.110.094.974.154.143.7955.6654.6049.5640.772.382.492.432.2720.1420.5419.9420.24743.17

746.60220.220.240.220.245.394.895.134.7453.2348.3940.7839.742.071.952.041.8715.2513.7412.4111.60746.60

748.08310.160.140.130.135.515.245.044.2057.2249.4844.4240.391.961.751.621.5921.0021.3321.6323.68748.08

749.98820.250.280.270.314.594.043.603.4142.5136.5330.9027.162.182.092.132.1721.1321.3922.2021.71749.98

753.5080.150.150.120.115.344.844.584.1156.9153.4852.9654.691.861.791.541.6121.0121.3422.5721.46753.50

758.50850.190.190.190.185.685.054.914.7960.7756.5654.3557.572.031.831.741.6215.0313.1012.3411.58758.50

762.7020.210.180.180.185.385.155.004.8952.3150.9045.9646.232.232.202.312.0316.1314.5014.5114.09762.70

780.37300.170.160.150.145.485.134.855.0460.6660.5053.8253.142.212.272.182.0416.4014.9514.8513.75780.37

782.26230.160.150.140.115.295.064.954.1457.6161.0353.6546.952.082.031.992.0120.9020.9520.8921.03782.26

810.22960.160.160.140.145.345.395.044.6860.8756.3760.3451.872.342.412.392.4218.2117.7717.4916.62810.22

820.68990.210.210.220.215.465.104.794.8958.5152.7657.8748.322.322.222.182.3717.4517.0616.6417.48820.68

826.43350.120.100.090.085.515.325.654.8869.8573.6368.7261.152.122.192.012.0419.5620.3318.6618.58826.43

870.60140.160.140.120.116.035.905.706.4963.0160.1058.1957.712.212.102.202.1321.3922.8122.2624.47870.60

876.14830.320.400.450.585.655.345.725.1954.9250.6344.5741.352.001.891.891.7613.9512.4411.6410.68876.14

896.14460.190.200.200.195.766.376.106.1065.3365.9866.6667.862.042.071.811.8119.4619.8820.7819.28896.14

902.971000.160.140.120.115.715.625.945.2362.3861.4963.7563.922.612.712.852.9020.8421.4823.0222.67902.97

914.92490.150.150.130.145.885.815.905.8276.1292.2983.7785.732.021.901.821.7818.3718.3318.1517.62914.92

922.85790.280.300.370.385.635.385.385.3960.6964.2857.3253.822.071.981.781.6919.9720.5121.4621.50922.85

925.17800.210.200.240.236.246.496.346.4956.6456.2848.6248.652.492.762.772.7919.9119.7820.4220.79925.17

925.20580.250.290.280.326.117.026.647.2057.7362.8853.4657.872.242.152.012.0816.9516.0415.0114.66925.20

932.97380.250.280.300.295.816.115.255.4758.3049.6246.8143.742.532.612.692.7022.0723.0723.3125.11932.97

934.92840.200.180.180.186.246.586.936.2067.9270.8764.8668.222.292.482.402.3518.7218.5718.0017.82934.92

940.10720.190.160.170.166.456.376.816.0864.3262.6763.6455.362.763.153.093.3816.9517.3016.8917.02940.10

953.55250.220.220.230.246.176.146.416.6173.8177.4177.3473.552.011.831.811.6719.5219.9620.1719.82953.55

959.81510.220.210.240.226.316.546.286.5665.1262.3868.6357.332.352.372.282.4521.0621.8821.7423.10959.81

965.90700.190.200.190.186.406.746.706.7267.8563.0464.1961.862.502.472.472.4120.6221.7524.2124.30965.90

966.59590.150.150.130.116.416.946.826.7269.3270.9974.7269.622.532.832.942.8219.5519.8819.1919.87966.59

989.84390.220.240.240.276.826.747.036.9062.8967.0761.8857.352.332.492.442.5020.9320.9122.3523.35989.84

994.73640.140.130.110.106.656.856.747.1172.5475.7782.4273.892.762.843.123.4319.0218.7717.8418.81994.73

1,004.38180.210.240.210.216.437.056.996.7975.4587.0678.8879.602.342.362.322.3417.9516.8216.8816.431,004.38

1,049.25260.300.400.360.476.386.466.116.4476.3183.8175.9283.002.001.861.761.7318.8118.4717.4618.051,049.25

1,066.83710.200.210.230.226.676.777.077.5281.4683.2588.7983.412.372.412.362.4220.9322.7522.3222.741,066.83

1,070.46480.310.360.380.436.817.747.878.6057.8260.0860.5456.912.592.622.652.7218.4218.3418.0516.571,070.46

1,089.29750.280.300.340.397.057.268.357.9564.0867.5960.9457.392.702.863.013.2619.3719.5418.9619.221,089.29

1,097.89170.160.150.140.137.067.928.718.2894.5794.9695.57117.332.342.462.322.5417.9917.1016.4915.441,097.89

1,099.40980.260.310.320.387.037.648.018.5374.6579.4079.7164.892.642.802.833.0316.7914.9614.1113.931,099.40

1,119.63610.220.240.220.257.157.767.848.4972.8180.6187.2185.622.662.762.832.8121.0421.8721.3021.211,119.63

1,131.40410.250.300.270.317.097.228.138.5880.6681.2890.7582.882.712.903.053.1917.2415.8216.0215.581,131.40

1,144.75150.250.290.320.346.807.147.127.5581.6884.2490.9485.822.692.903.092.9919.9819.9619.6619.271,144.75

1,154.20760.230.240.210.216.827.107.217.8878.8878.5889.0083.403.003.383.603.9221.7022.1222.9524.791,154.20

1,154.70120.200.200.220.236.656.687.126.3792.15113.63138.42143.272.222.152.151.8418.7318.1818.0918.391,154.70

1,155.43430.180.170.160.147.087.407.768.8889.39106.41100.54106.322.732.892.953.1619.3719.3219.9419.381,155.43

1,155.99160.230.260.230.277.358.058.718.3673.1783.1985.9992.602.562.672.653.1321.5322.5522.6822.331,155.99

1,156.28950.140.120.110.106.536.816.237.2087.4593.44106.28113.022.923.163.293.4723.6627.5028.0630.561,156.28

1,156.95130.210.210.200.237.838.428.429.0788.1195.6386.8692.202.462.342.462.5421.2421.9723.0723.361,156.95

1,167.47780.250.250.240.316.757.077.647.5186.0999.4096.32111.282.602.662.672.7520.3721.1620.3320.581,167.47

1,187.94330.230.240.270.296.786.957.247.3278.6882.3084.4384.492.552.752.652.9427.4531.4234.9238.081,187.94

1,207.98670.230.230.250.287.018.298.488.1684.9590.0197.5499.792.953.153.443.7218.8119.7519.6819.601,207.98

1,221.3470.210.240.230.257.047.828.138.2795.26103.96111.49121.512.772.963.123.5017.8517.4117.4217.291,221.34

1,235.16730.220.240.260.267.387.888.318.6082.0685.6494.1987.043.213.623.774.4020.8223.0522.8122.631,235.16

1,256.06900.290.350.420.446.386.637.588.2283.6094.2797.5890.922.722.943.083.1722.9423.9226.1226.391,256.06

1,269.28540.360.450.510.537.518.059.549.1170.5076.4375.1073.162.682.832.903.1721.5122.1223.6324.171,269.28

1,288.46770.370.430.460.537.288.468.798.4586.0383.7697.76103.682.372.492.632.6119.9421.6321.8522.641,288.46

1,288.7860.250.280.280.357.747.868.499.6088.4789.37105.90131.502.632.852.803.1321.4823.3223.7125.131,288.78

1,308.07340.350.400.490.547.828.439.259.7977.5578.2181.6688.652.883.073.443.3419.9720.5920.9522.391,308.07

1,403.98190.170.160.160.157.917.958.8110.53104.20128.31148.42148.802.762.943.023.0126.4530.6131.5835.171,403.98

1,424.14810.360.490.580.756.827.638.218.2186.88100.0296.62115.952.562.632.672.7225.3928.2732.2436.031,424.14

1,439.17530.170.160.160.147.969.1910.2910.80100.35126.87125.87169.052.903.193.683.5324.3228.0429.1932.921,439.17

1,450.05650.260.290.350.367.918.448.9810.0897.27109.40127.87134.833.013.353.513.7124.5828.5730.2231.261,450.05

1,456.38360.360.510.600.747.488.219.029.0884.3988.8395.35112.482.402.482.312.4528.2031.9137.6642.381,456.38

1,473.30400.250.300.350.337.688.238.349.69101.34125.86138.76156.682.923.113.713.9223.5227.1427.5128.831,473.30

1,499.55860.250.280.290.318.229.029.0510.2796.57117.30122.87139.473.714.434.945.6721.4622.1924.3224.371,499.55

1,673.85240.250.280.270.338.8910.3912.1613.04116.17153.34167.48192.962.852.883.213.1825.5928.4232.0034.671,673.85

1,784.69570.350.440.570.768.689.4110.8511.27108.66146.32174.31200.892.632.922.893.1827.2333.3036.1838.361,784.69

1,958.30210.260.280.310.339.8011.7315.3116.23129.34170.45205.68255.873.564.325.045.5521.6822.0122.2524.301,958.30

Simulation of commodity prices provides a richer understanding of possible price outcomes vs. a single, static forecast. Simulations also support analysis of possible physical and/or financial hedging strategies


Impact of hedging

all figures in millions (except prices)

FuturesUsed

SugarNo

Natural gasNo

ElectricityNo

DieselNo

AluminumNo

Net exposure (95%)

Q1Q2Q3Q4Q1Q2Q3Q4Total

Simulated commodity costs

Sugar46.368.684.0111.620.740.453.077.1191.3

Volume (lbs)128.0134.0141.0150.0

Price0.360.510.600.74

0.00.00.00.00.0

Natural gas71.882.995.6100.816.825.034.837.2113.8

Volume9.610.110.611.1

Price7.58.29.09.1

0.00.00.00.00.0

Electricity84.488.895.3112.522.126.633.150.2132.0

Volume1.01.01.01.0

Price84.488.895.3112.5

0.00.00.00.00.0

Diesel38.541.640.745.32.63.91.23.811.4

Volume16.016.817.618.5

Price2.42.52.32.4

0.00.00.00.00.0

Aluminum45.154.367.880.515.122.334.044.8116.2

Volume1.61.71.81.9

Price28.231.937.742.4

Total286.1336.1383.4450.777.3118.2156.1213.1564.7

Earnings statement

all figures in millions (except prices)Q1Q2Q3Q42012

Sales480.00504.00529.20555.602,068.80

Volume3,200.003,360.003,528.003,704.0013,792.00

Price ($)0.150.150.150.15

0.00

Cost of Goods Sold328.85337.92347.34357.581,371.70

Fixed Costs120.00120.00120.00120.00480.00

Sugar ($/lbs)25.6028.1431.0234.50119.26

Volume (lbs)128.00134.00141.00150.00

Price0.200.210.220.23

0.00

Natural gas ($/Kcf) - Henry Hub55.0257.8860.7563.62237.27

Volume9.6010.1010.6011.10

Price5.735.735.735.73

0.00

Electricity ($/MWh) - NY ISO62.2762.2762.2762.27249.08

Volume1.001.001.001.00

Price62.2762.2762.2762.27

0.00

Diesel ($/gal) - NY Harbour35.9137.7139.5041.52154.64

Volume16.0016.8017.6018.50

Price2.242.242.242.24

0.00

Aluminum30.0531.9233.8035.68131.44

Volume1.601.701.801.90

Price18.7818.7818.7818.78

Variable Costs208.85217.92227.34237.58891.70

0.00

General & Admin. Exp.90.0090.0090.0090.00360.00

0.00

EBITDA61.1576.0891.86108.02337.10

TitleTo quickly check to make sure prices are still the same, filter the prices on the tab proj 3 to go in order 1 to 100 and this should match

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