Investment Thesis

Valero Energy Corporation is the largest petroleum refiner in the United States. Refinery capacity of nearly 3.3 million barrels per day (mbd), large holdings in pipelines and logistics, and an extensive retail network give Valero earnings stability and an enduring competitive advantage. Although refining margins and earnings are extremely volatile, I believe that emerging macroeconomic conditions and a lasting imbalance in crude oil supply and demand will lead to strong performance in Energy sector stocks. Valero is poised to be a strength leader in this sector, and I anticipate above-average returns for this stock over the next two years.

Summary I have assigned Valero Energy Corp a two year price target

of $95. The following are key assumptions supporting this valuation:

Energy prices will continue to be under pressure from lack of supply and increasing demand until at least 2010.

Price structure and technical indicators show that the crude oil market is in a healthy trend, and is not in an “overheat” or overbought condition.

Refinery margins will remain strong. Earnings and stock prices will be strong across the sector. Three standard valuation methods (Discounted Cash Flow

(Free Cash Flow to the Firm), Comparable Multiples, and Dividend Discount Model) support this valuation and suggest the intrinsic value of this stock is approximately 30%-40% above its current price.

Technical factors support the probability of a price advance at least to my target price.

VLO, Daily (200 and 49 per Moving Averages) VLO, Monthly (200 and 49 per Moving Averages)

NYSE: VLO

Valero Energy CorporationReport updated 6 August 2006

Analyst: Adam Grimes

Fisher College of Business The Ohio State University Columbus, Ohio

Contact: 614.432.5661 grimes.111@osu.edu Fund: OSU SIM Class (BUS FIN 824) Fund Manager: Royce West, CFA

Recommendation: BUY

Sector: Energy Industry: Oil & Gas, Refining and Marketing

Current Stock Price: $66.18 Target Price: $95.00 Market Cap: $40,753MM Outstanding Shares: 615MM ADV: 9,320,000 52 Week High: $70.75 52 Week Low: $41.29 YTD Return: 53.4% Beta: 0.99 Last Year Sales: $96,900M EPS: $7.82

2

Table of Contents

Investment Thesis........................................................................................................................................................................... 1 Summary........................................................................................................................................................................................... 1 Company Overview........................................................................................................................................................................ 3

Refining........................................................................................................................................................................................ 3 Retail, Marketing and Transportation ..................................................................................................................................... 3

Global Macroeconomic Analysis ................................................................................................................................................. 4

Recent Global Economic Growth........................................................................................................................................... 4 Risks to Future Growth ............................................................................................................................................................ 4

Petroleum Market Analysis ........................................................................................................................................................... 5

Market Structure and Overview............................................................................................................................................... 5 Fundamental Forecast ............................................................................................................................................................... 5 A Basic Regression Model for Crude Oil Price..................................................................................................................... 7 Other Forecasting Methods...................................................................................................................................................... 8

Sector Analysis ................................................................................................................................................................................ 9

Petroleum Economics 101........................................................................................................................................................ 9 Drivers of Performance........................................................................................................................................................... 10 Valuation.................................................................................................................................................................................... 10 Industry Analysis: Refining and Marketing ......................................................................................................................... 11

Company Analysis ........................................................................................................................................................................ 12

Sustainable Competitive Advantage? .................................................................................................................................... 12 Financial Statements Analysis................................................................................................................................................. 12 Equity Valuation: Multiples ................................................................................................................................................... 14 Equity Valuation: Dividend Discount Model..................................................................................................................... 15 Equity Valuation: Discounted Cash Flow........................................................................................................................... 17 Technical Position and Assessment ...................................................................................................................................... 19

Summary......................................................................................................................................................................................... 20

Strengths and Opportunities .................................................................................................................................................. 20 Risks and Concerns.................................................................................................................................................................. 20 Conclusions ............................................................................................................................................................................... 20

Appendix 1 Brent Crude Oil Price Forecast ............................................................................................................................ 22 Appendix 2 Valero Financial Statements from Company 10-K ........................................................................................... 23 Appendix 3 Valero Revenue Regression Model and Inputs .................................................................................................. 26 Appendix 4 Valero Discounted Cash Flow Model ................................................................................................................. 27

3

Company Overview1 Valero Energy Corporation (Valero), incorporated in 1981, owns and operates 18 refineries located in the

United States, Canada and Aruba that produce refined products, such as reformulated gasoline (RFG), gasoline meeting the specifications of the California Air Resources Board (CARB), CARB diesel fuel, low-sulfur diesel fuel and oxygenates (liquid hydrocarbon compounds containing oxygen). The Company also produces conventional gasolines, distillates, jet fuel, asphalt, petrochemicals, lubricants and other refined products.

Its business is organized into two segments: refining and retail. The refining segment includes refining operations, wholesale marketing, product supply and distribution, and transportation operations. The refining segment is segregated geographically into the Gulf Coast, Mid-Continent, West Coast and Northeast regions. The retail segment is segregated into two geographic regions: Retail operations in the United States are referred to as the US System, and retail operations in eastern Canada are referred to as the Northeast System. On September 1, 2005, Valero completed the merger of Premcor Inc. with and into Valero Energy Corporation.

Valero markets branded and unbranded refined products on a wholesale basis in the United States and Canada through a bulk and rack marketing network. The Company also sells refined products through a network of approximately 5,000 retail and wholesale branded outlets in the United States, Canada and Aruba. It is the general partner of Valero L.P. The retail segment includes company-operated convenience stores, Canadian dealers/jobbers, truckstop facilities, cardlock facilities and home heating oil operations.

Refining As of December 31, 2005, Valero's refining operations included 18 refineries in the United States, Canada

and Aruba with a combined total throughput capacity of approximately 3.3 million barrels per day. The Company processes a slate of feedstocks, including sour crude oils, intermediates and residual fuel oil. For the year ended December 31, 2005, total throughput volumes for the Gulf Coast refining region averaged 1,364,000 bpd; total throughput volumes for the West Coast refining region averaged 311,600 bpd; total throughput volumes for the Mid-Continent refining region averaged 364,500 bpd; and total throughput volumes for the Northeast refining region averaged 447,800 bpd.

Retail, Marketing and Transportation The retail segment’s operations include sales of transportation fuels at retail stores and unattended self-

service cardlocks, sales of convenience store merchandise in retail stores, and sales of home heating oil to residential customers. Valero is an independent retailer of refined products in the central and southwest United States and eastern Canada.

Sales in the US System represent sales of transportation fuels and convenience store merchandise through the Company-operated retail sites. During 2005, total sales of refined products through the US System's retail sites averaged approximately 118,000 bpd. In addition to transportation fuels, its Company-operated convenience stores sell snacks, candy, beer, fast foods, cigarettes and fountain drinks. Its Company-operated stores are operated primarily under the brand names Corner Store and Stop N Go. Transportation fuels sold in its US System stores are sold primarily under the Valero brand, with some sites selling under the Diamond Shamrock brand pending their conversion to the Valero brand.

Sales in Valero's Northeast System include sales of refined products and convenience store merchandise through its Company-operated retail sites and cardlocks, sales of refined products through sites owned by independent dealers and jobbers, and sales of home heating oil to residential customers. The Northeast System includes retail operations in eastern Canada where it is a supplier of refined products serving Quebec, Ontario and the Atlantic Provinces of Newfoundland, Nova Scotia, New Brunswick and Prince Edward Island. During 2005, total retail sales of refined products through the Northeast System averaged approximately 76,300 bpd. Transportation fuels are sold under the Ultramar brand through a network of 987 outlets throughout eastern Canada. In addition, the Northeast System operates 89 cardlocks, which are card or key-activated, self-service, unattended stations that allow commercial, trucking and governmental fleets to buy transportation fuel 24 hours a day. The Northeast System operations also include a large home heating oil business that provides home heating oil to approximately 161,000 households in eastern Canada.

1 Adapted from 2005 Company 10-K and Reuters.

4

Global Macroeconomic Analysis In FY 2005, Valero derived 87.5% of its revenues from domestic operations, 9.2% from operations in

Canada, and the remaining 3.3% from other international refining and retail operations (primarily Aruba and the Caribbean)2. Valero is not a global player in the sense that many other petroleum companies are: it does not operate in high geo-political risk areas, it does not have to deal with the intricacies of trans-oceanic shipping, and it is insulated from most exchange rate fluctuations. However, since the energy and petroleum markets are so strongly influenced by global economic events, a brief overview of the current world economic condition is in order.

Recent Global Economic Growth3 Real Global GDP rose 4.7% in 2005. China (9.3%) and India (7.6%) were leading drivers of this growth.

Russia and several Baltic FSU states were also in the 6%-7% range, and many other developing economies also experienced strong growth. Among major industrialized nations, the United States led at 3.5% growth and Italy trailed with 0% growth. Only 5 countries reported GDP decreases for 2005, ranging from a 3% decline in Iraq to a 7% loss for Zimbabwe. Emerging market countries have shown exceptional strength, but the major industrialized nations also experienced strong growth. In spite of high energy prices, several major natural disasters, and a variety of regional wars and conflicts, the 2005 global economy was strong, outperforming many analysts’ expectations.

This expansion has been aided by low inflationary pressure and the strength of global equity markets. Markets across the globe are experiencing a period of exceptional returns, coupled with volatility and risk premiums that are near historical lows. Some commentators have suggested that markets are not accurately discounting global risks, but current market conditions point to a healthy and sustainable trend. Perhaps the strongest warning comes from yield curves, especially in the US, which are showing a tendency to flatten—this has historically been a harbinger of softening and even recession—but it is important to note that this relationship has been weaker in the 1990’s and 2000’s than it was in the 1980’s. Other leading indicators (perhaps most significantly the OECD’s aggregate leading indicators) are rising and imply continued strength.

Risks to Future Growth4 The primary risk to future GDP growth, both domestically and abroad, is inflationary pressures from high

energy costs. Current low core inflation levels may reflect deflationary pressures from globalization, but expect that global economies will continue to be under pressure for the next few years. Emerging markets, corporations, and oil exporters have uncharacteristically been net savers, which may have contributed to low long-term interest rates. (Perhaps this factor is responsible for some of the flattening of the yield curve in the US.) In general, global markets could be vulnerable to further tightening. Yields are high and volatility in most markets is very low. If interest rates rise, a feedback loop could develop that would have very negative consequences for global equity markets.

High energy prices themselves continue to be a threat to future growth. The global economy has shown surprising momentum, and demand for petroleum products has proved resilient even at the current high levels. If energy prices continue upward, at some point the costs to developing economies will become great enough to stunt growth. It is also possible that the full effects of the current high prices have not yet been felt. Currently, excess production capacity remains at historic lows. This environment of constrained supply leaves the market vulnerable to shortages, squeezes and price shocks. It seems likely that nations and consumers alike are treating these high energy prices as temporary aberrations. How will economies adapt if it becomes clear that the current levels are more or less permanent?

Global imbalances pose a threat to future growth as well. Current account surpluses in oil-producing nations continue to rise, financed largely by the rising current account deficit in the US. This deficit is being financed easily (due in part to low interest rates), but at some point it must fall and surpluses in other countries must fall to balance. This adjustment is currently being hampered by high petroleum prices. The ideal mechanism for this adjustment is a purely market-driven one: Foreign investors must be willing to take large positions in US assets and bear the risk of US dollar depreciation in the short-term, but a premium for this risk does not appear to be priced into the market at this time. Policy changes (e.g. more flexible Chinese exchange rates) could also ease this

2 Company 10-K. 3 2005 CIA World Factbook and StockVal data. 4 A similar evaluation of future risks, with slightly different priorities, can be found in the IMF’s World Economic Outlook, April 2006. See, for instance, http://www.imf.org/Pubs/FT/weo/2006/01/index.htm.

5

adjustment. If this adjustment is not well managed through market forces and policy changes, there is a risk of serious and far-reaching shocks to global markets.

At some point the risks become so extreme that they cannot be properly evaluated. It is difficult to estimate the impact of wars, nuclear detonations, bio-terrorism, nuclear terrorism, pandemics, natural disasters and other extreme scenarios on the global economy. Each event’s impact would vary depending on its scope and location, but, in the past, major events like 9/11 have not had a lasting impact on world markets. The main risk is that the global economy is currently a delicately interlocking structure: high current account deficits have arisen in oil-consuming nations because of the high cost of energy. These deficits are being financed easily due to low interest rates which are themselves threatened by rising oil prices. Rising oil prices also threaten to push developing economies into recession and further exacerbate global imbalances. These are the main threats to consider in coming years.

Petroleum Market Analysis Market Structure and Overview

No market is easy to forecast but the petroleum market has several features that make it exceptionally difficult. Even the availability of fundamental data is a problem because there is concern that some nations (notably India and China) may not be reporting complete, accurate and unbiased data. The petroleum market is subject to political intervention and manipulation at several levels, and it often over-reacts in the short term to global events.

In addition, it is inaccurate to think of one petroleum market because there are many markets in many regions for a wide range of raw products and distillates. Even focusing on one specific product is difficult—crude oil itself has hundreds of varieties and grades that reflect its geographic origin and ease of processing. These grades trade at discounts and premiums so there is not one world crude oil price. The three most significant grades of crude oil are North Sea Brent which is probably the best proxy for world crude price, West Texas Intermediate Crude which is the standard for US crude oil pricing, and NYMEX futures which are the domestic standard for crude futures.

In the short term, crude oil prices tend to be extremely volatile, often overreacting to threats of shortages, transportation disruptions, regulatory changes and geopolitical events. Political events and statements from governments in major producing areas cause temporary price spikes. Margins flex and the relationships between crude and distillate pricing changes daily in most markets, but petroleum prices are remarkably stable in the long-term and lend themselves fairly well to supply/demand analysis.

Fundamental Forecast For the past several years, energy prices have been high, even on an inflation-adjusted basis.

Figure 1 shows the price of West Texas Intermediate Crude oil, in real dollars. As oil prices soar to new nominal highs, media commentators frequently point out that oil is not actually at historic highs when considered on an inflation-adjusted basis. This statement, while true, may lead one to overlook some significant facts.

First, when adjusted for inflation, crude oil is not at historic highs, but it is still higher than it has been anytime in the past 20 years. Oil has never stayed at such high levels for more than 2 years, and in the past has spiked to these levels as a result of geopolitical events and supply shocks. This time, oil prices have risen to these high levels in a steady, multi-year trend without significant political shocks. The question we all need to ask is, “Is this time different?” I believe that due to serious supply/demand imbalances, the answer is “yes”. A look at some fundamental supply/demand numbers illustrates the problem.

Current oil use is 86.8 mbd5 and is projected to grow about 2.1% each year to 2010, with most of this

5 Data in this section from EIA estimates, PIRA, BP and Platt’s data sources.

West Texas Intermediate Crude, $/bbl.

$0

$10

$20

$30

$40

$50

$60

Jan-

70

Jan-

72

Jan-

74

Jan-

76

Jan-

78

Jan-

80

Jan-

82

Jan-

84

Jan-

86

Jan-

88

Jan-

90

Jan-

92

Jan-

94

Jan-

96

Jan-

98

Jan-

00

Jan-

02

Jan-

04

Jan-

06

Figure 1. WTI $/bbl (Inflation-adjusted)

6

new demand (40%) coming from China and India. Depletion of working fields is currently about 4 mbd annually (and accelerating). Thus total new additions of 27.5 mbd are needed to match demand to 2010.

In light of these demand numbers, the supply side situation appears bleak. From 2003-2006, non-OPEC non-FSU output has grown 180,000 bbl/day each year. Best-case estimates for this component of supply hold it rising at the same rate for the next decade, but many analysts expect it to decline. In the same time period, FSU nations were forecasting 700,000 bbl/day in annual additions, but 2004 and 2005 saw no new additions due to internal politics. If the FSU is able to match that forecast every year to the end of the decade, that would bring potential annual non-OPEC additions to 1 mmb/d.

OPEC forecasts sustainable total (not annual) new additions of 4.6 mmb/d by 2010, but every OPEC member has consistently missed projections for several years: Iran and Iraq are experiencing serious logistical problems getting their oil to market, Venezuelan production is slipping in both quantity and quality, and major Kuwaiti fields are experiencing annual depletions near 5%. Consensus on realistic OPEC additions centers around 2.3 mmb/d, mostly from Saudi Arabia and the UAE, both of which hold massive potential reserves.

Some analysts forecast net additions of 3 mmb/d from Algeria, Libya, and Nigeria, but other analysts characterize these estimates as “heroic”. These countries have many political issues to resolve and would need to significantly expand their infrastructure to sustain those levels of production. Even if this is possible, the best-case estimates for new additions (from CERA) call for 11.5 mmb/d new additions, still leaving a significant shortfall between supply and demand. I believe that this shortfall will put continued pressure on petroleum prices, at least through the end of the decade. Prices significantly below current levels ($70 bbl) seem extremely unlikely, and the possibility of shortages accompanied by high volatility and price spikes remains a real threat.

It is difficult to imagine circumstances that could lead to lower oil prices in the next few years. Perhaps the most likely would be recession and weakening of demand in high-demand regions, but demand has been exceptionally resilient in the face of higher prices. The IMF’s rule of thumb, that a $10 increase in the price of a barrel of crude oil (sustained for one year) will decrease world GDP growth rate by .5%, may not apply to the rapidly expanding economies of China and India. In some sense, we find ourselves in uncharted territory with these price levels and this new demand.

It is also possible that massive new reserves could be discovered, but this seems extremely unlikely. Most of the world’s conventional reserves have probably been discovered. New reserves are likely to come from deep offshore wells or in the form of difficult-to-refine ultra-heavy unconventional reserves. It is difficult to estimate the impact of a breakthrough in new energy technology. Emergence of a technology like cold fusion, or more efficient renewable energy sources, could have dramatic effects on petroleum prices. Even if new technology significantly reduced our commitment to oil, there would still be a need for liquid fuels and a use for petroleum products for many years to come.

Perhaps the best case for lower energy prices comes from a possible accounting rule change. Current rules only permit oil companies to report proved reserves on financial statements6, and nearly all oil companies follow this policy in all reporting. Many government agencies follow GAPP regulations and also only report proved conventional reserves. Thus, current figures do not account for extra-heavy and unconventional reserves, which are many times larger than conventional reserves. If these rules were changed, the apparent supply of crude oil, at least on financial statements and reports, could double or triple overnight. Even though the actual amount of oil in the ground would not have changed, it seems likely that world markets could overreact. This could perhaps result in a downward price shock and a period of sustained lower prices.

The future is always uncertain and forecasts must involve a large margin of error. However, when considering the future of oil prices, it seems obvious that the risks are skewed to the upside. Events which would lead to higher prices and volatility seem much more likely than scenarios that could lead to lower prices. I attempted to quantify these risks into a regression model that would give a forecast range of crude oil prices for the next 10 years.

6 For a discussion on the SEC’s rules for reserve reporting, see Yergin, Daniel. “How Much Oil is Really Down There?” The Wall Street Journal. April 17, 2006. p. A18.

7

A Basic Regression Model for Crude Oil Price7 Since Energy sector companies’ earnings and stock prices are so closely related to energy prices, I thought it

necessary to have a fundamental price forecast model in place for crude oil. Several models were attempted, one incorporating over 40 factors. However, the data needed to build and test such a model is not available in sufficient resolution in the public domain, so in the end I settled on a simpler, “back of the envelope” regression model. This model is adequate for our forecasting purposes, but it has raised several questions for further investigation. Annual data on regional production and consumption obtained from the BP Statistical Review of World Energy 2006 were used as inputs in regression equations.

World supply was divided and re-categorized into several regions and regressions were run on the whole basket. It was generally found that the supply to crude oil price relationship was linear and resulted in highly significant regression equations (p values under .05 and R2 values over .85). The regression coefficient for certain areas (notably North American production) was negative, but this probably indicates that supply is not always the explanatory variable – some regions may hold back production to be able to produce more in response to higher prices rather than higher production necessarily leading to lower prices. In addition, some significant production (US) is consumed internally and never goes to the world market so it may not have the expected impact on oil prices. Middle Eastern production also showed a sometimes loose relationship to crude oil prices; this may reflect intervention of politics in the supply/demand equation. Based on these initial regression runs, supply from North America, Central America, Europe, Middle East and Africa were included in the final model. Asia-Pacific supply was not included in the model due to low significance in the regression runs.

The supply model appeared adequate (high R2 values) without a demand component, but economic common sense said demand needed to be included in the forecast. However, the demand side of the equation proved significantly more difficult to quantify. Initial regressions of the regional baskets showed poor results (p-values well over .20). Visual inspection of scatterplots showed that the demand relationships were curves. (Why is the supply relationship linear but demand is not?) Linear transformations resulted in better fits, but several regions continued to show low p-values (Asia, Middle East, and Africa). Middle Eastern consumption was probably satisfied by domestic production, insulating that demand from the global marketplace. African and Asian demand may have been too low for much of the period analyzed to have a significant impact on prices. In the end, North and Central American demand was aggregated into one variable, Middle East and African demand was eliminated from the equation, and Asian demand was retained in spite of low p-values.

7 A note on the regression models developed in this report: This analyst is a trader with 10 years experience in the futures markets and I have seen many regression models fail for various reasons. In my experience, the most common reasons for regression models failing are: blindly developing mathematically correct models without understanding the economic implications of such models (especially include/exclude decisions on explanatory variables), and not accounting for the interaction of behavioral factors in the marketplace (expecting too much accuracy from regression models’ predictions.) As such, the methodology I followed in all regressions was to first identify explanatory variables that made economic sense and then verify the relationships with regression. I did not do shotgun-type exploratory regressions on a wide basket of variables, but I was often surprised at the explanatory variables that did not have mathematical significance. There was sometimes a tradeoff between developing a model that was mathematically correct and one that made economic sense. For instance, the regression model for crude price has a problem with multicollinearity. (This is because supply/demand figures tend to be highly correlated.) To produce a regression model that did not have issues with multicollinearity, the number of explanatory variables had to be reduced to 3, but at this point the model ceases to make economic sense! The partial multicollinearity among the independents inflates the standard errors and makes assessment of the relative impacts of each independent unreliable, but it does not bias the estimates of the coefficients. Since the purpose of this model (and all regressions in this report) is predictive rather than analytical, this type of multicollinearity is not a problem at all.

8

Many of the difficulties probably arise because demand does not follow simple, Econ 101 rules—some regions have extremely inelastic demand and some major consumers maintain large stocks which they may utilize at high prices and replenish at lower prices. Changes in supply may represent movement along the supply curve, a shift of the supply curve, or even deliberately restricted supply to force higher prices. In addition, these correlations have not been stable over time. For instance, Asian demand was not a significant part of world consumption before 2000, so the regression model showed low p-values for Asia. Thus the include/exclude decisions had to be made based on a combination of mathematical principals and economic estimates of the variable’s likely future impact.

For the forecast inputs, a baseline of recent historical years’ averages was used as a starting point for each variable. As price creeps above $80/bbl, demand was reduced slightly for each region. Demand, particularly in the Asia Pacific region, rebounds to historical highs once prices begin to ease after 2010. Supply increases at historical averages (with a random volatility component added to the inputs) and greatly increases for some regions after 2010 (to model the increase of new supply from unconventional reserves). The model predicts a high of $103.85/bbl in 2010, and then a steady decline to $66/bbl by 2015. Figure 2 is a graphical representation of the model prediction and Appendix 1 shows the actual model and inputs in more detail.

This regression model provides a forecast for Brent crude oil, which is the standard for world pricing. Regressions were attempted with several other crude oils, but Brent gave the most significant results. This is to be expected since world supply and demand figures were used as inputs.

Other Forecasting Methods As a reality check, comparisons were made with several other forecasts and forecasting methods. The US

Energy Information Administration gives three crude oil forecasts8 which differ significantly from my regression model. I believe the EIA may not be adequately accounting for the behavioral impact of perceived shortages and may also not be modeling the emergence of unconventional reserves. Thus, the EIA models forecast much less volatility in prices (the EIA “high price case” has price unchanged at $61.12/bbl to 2009, then begins a gentle curve upward to $76.30 by 2015), no price drop after 2010, and lower peak levels than my forecast. However, I also used the EIA cases as inputs into my DCF model and found that, even though the peak oil prices forecast by the EIA are considerably lower, they generally give higher DCF valuations because the overall sustained price levels are higher.

From a technical perspective, the futures markets appear to be in a healthy and sustainable uptrend. Markets which are nearing the end of trends usually show one of two conditions: either volatility expands into a “buying climax” phase which ends in dramatic price collapse (perhaps because everyone who wants to buy has already bought, and a vacuum has been created on the other side), or resistance will begin to hold and the market will begin to form one of the classical top formations (head and shoulders, rounding tops, etc). Current market conditions do not show either of these conditions—the market continues to trend higher, with periodic retracements indicative of a healthy trend.

Figure 3 shows monthly bars of the NYMEX Crude Oil futures (continuous futures, rolling with open interest). Notice that, with the exception of a price spike around the 1990 Gulf War, the futures traded in a narrow band from $9.30 to $26.00 for 16 years. An old trader’s

8 See, for instance: http://www.eia.doe.gov/oiaf/aeo/index.html.

$0

$20

$40

$60

$80

$100

$120

1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Figure 2. Brent Crude Oil US$ / bbl (predicted by regression)

Figure 3. NYMEX Light Sweet Crude Futures, Monthly Bars

9

maxim says “the longer the base, the farther into space,” meaning that the longer a market trades in a tight band, the farther the breakout move will go (in both price and time) when it finally comes. Sixteen years is an exceptionally long time for a market to base, and such a base could certainly sustain a move beyond current levels. Some signs of momentum divergence are emerging, but this is to be expected in a long, sustained trend. This market does appear to be somewhat overdue for a correction. We could easily see 6-8 months of sideways-downward price action without compromising the integrity of the trend. Any retracement would probably carry at least to the 20 period exponential moving average (XMA) which is currently around $62. Market geometry suggests that any downward price action should find support around $54.50 (basis September 2006 futures). Significant violation of this level would lead us to reassess the integrity of the trend.

One last insight can be gleaned from the pricing structure of the futures markets themselves. Energy markets are normally backwardated, meaning that farther-out months trade at a discount to the near month. This is in contrast to most commodities which normally trade in contango, meaning the near month trades at a discount to

the farther out. (The farther out months in most commodities have carrying costs associated with them (insurance, warehouse charges, cost of capital, etc.) so they command a premium price.) There are several explanations for normally backwardated markets, but the clearest is that energies are consumption commodities—some market participants must carry inventory and cannot afford the risk of selling inventory and going long on futures if an arbitrage opportunity exists. (Imagine the heating oil company that has to tell its customers in December that they have no oil in the tanks but they are making a ton of money out in the April futures!) Thus, cost of carry has not traditionally applied to energy futures markets.

Table 1 shows the current NYMEX futures contract price structure. Note that the market is actually in contango (each farther out month trading at a higher price) until August 2007, at which point the normal backwardated structure reasserts itself. This unusual “hump” structure

does not mean that the current bull market in energy will end in July 2007, but it does suggest that the futures markets are expecting higher prices at least that far out. This “elbow” in the price structure will normally move and flex a bit, sometimes extending a few more months into the future and sometimes coming in closer to the spot month. The normal expectation would be that, at some point, the market will revert to its normal backwardated state and this will be a warning of potential price collapse. Currently the market shows no such warning and seems to be expecting higher prices at least for the next year. This futures pricing relationship is a bellwether to watch for clues of impending trend changes.

Sector Analysis Petroleum Economics 101

Energy sector companies’ earnings are closely tied to crude oil prices and to business cycles in the industry. The industry itself has exhibited a fairly stable and predictable “long cycle” over its 140-year life. In lean times for energy companies (most recently late 1980’s to mid 1990’s) earnings are low and companies do not have extra funds to invest in E&P and CapEx. During these times energy prices are also very low. This encourages economic growth which leads to greater demand for energy products. The low price of energy and crude distillates through the 1980’s and early 1990’s was certainly a contributing factor to the boom of growth in China and India leading into the new millennium.

As economies grow, spurred by low energy costs, demand increases which begins to push the price of energy higher. As energy prices rise, so do oil companies’ corporate profits, and companies are now able to make

9 Data from eSignal.

Table 1. NYMEX Light Sweet Crude Oil Futures9

10

investments which will eventually increase supply. However, many of these investments have long time lags from the time the first dollar is spent to the time the project returns new oil. For instance, an E&P company drilling a new oil well in a high-risk area of the world can sometimes see a decade from the initial expenditure to the time the well reaches peak production. This time lag between expenditure and return in the form of increased supply drives the cycles in this industry. Economies continue to expand as energy prices rise, and oil companies continue to make more investments to increase supply.

Eventually, existing supply reaches capacity and energy prices rise to a point where economic expansion is restricted. Demand has outpaced supply growth. Recession sets in, demand begins to dry up and energy prices tumble. Previous E&P investments finally begin to return new supply, and this excess capacity only serves to drive price down even faster. After a period of several years, energy prices are at low and attractive levels, which begins to fuel economic growth and the cycle

repeats itself. Figure 4 shows the “long cycle” with turning points marked. The regularity of the cycle (with the exception of the first 25 years)—about 30 years from peak to peak and trough to trough—suggests that we are currently probably nowhere near a peak in energy prices and can expect higher prices for some time to come. This assessment is consistent with the higher price levels implied by current pricing structure in the futures markets, supply and demand models, and many industry analysts’ estimates.

Drivers of Performance The major driver of sector performance is

the price of crude oil. Crude oil itself is virtually worthless. What value crude has comes from the willingness of refiners to purchase it because they know they can process it and sell the distillates for more than they paid for the crude. Other players in the industry also attempt to extract value at various points in the process: E&P companies try to sell crude to refiners for less than they spent finding it and getting it out of the ground; Pipeline companies charge a fee for moving crude and refined products; and Retailers charge a mark-up to sell refined products to the public. The whole industry hinges on participants being able to add incremental value to crude oil at each stage of the process.

To investigate the connection between crude oil prices and Energy stock performance I created an equal-weighted (not market cap-weighted) index of Energy sector stocks and then calculated a cumulative log change measure of that index. There was no commercially available index that targeted the specific companies I wanted, so I selected 30 Energy sector stocks for the broad Energy index, and repeated the process with 12 Refining and Marketing stocks. (Results were very similar for the broad Energy index and the specific Refining index so only the broad index is discussed here.) Conventional wisdom says that Energy stocks do well when energy prices rise. The purpose of this exercise was to verify that a relationship exists and to see if the correlation between stock prices and energy prices was strong enough to justify the work involved in building a valuation model. Figure 5 shows that a sufficiently strong relationship exists to warrant further investigation.

Valuation Currently, the sector appears to be relatively cheap by most valuation methods. Price to Forward Earnings

is near historic lows, as is Price to EBITDA. Price to Sales is perhaps the most accurate valuation measure for this

Figure 4. The Business Cycle in the Petroleum Industry

Figure 5. Scatterplot of Cumulative Log Change Energy Index and WTI price.

y = 0.8454x - 7.3859R2 = 0.8189

0

10

20

30

40

50

60

$10 $20 $30 $40 $50 $60 $70 $80

Crude Oil $/bbl (Nominal)

Equa

l wei

ghte

d in

dex

Correlation = 0.905

11

sector (and least subject to manipulation) and is also in the lowest 30% of its 10-year range. There are several explanations for these low valuations. The most obvious is that the sector could be simply undervalued. Most of these valuations began to drop to low levels in 1999 as the price of crude oil began to climb (see Figure 6). It is possible that the market, maybe thinking the high crude oil prices were an aberration, did not adjust to these companies’ improved performance with proportionate stock prices. On a more negative note, there is also the possibility that the market “knows” something we do not. Whenever valuations appear unreasonably low there is often a problem with the company or sector that may not be apparent at first glance. But in this case, this seems less likely since this low valuation condition has persisted for 5 years.

Another explanation is that perhaps the denominators of these measures are so inflated due to the oil price boom that it does not make sense to compare current values to past values. Perhaps there is a new paradigm and different appropriate multiples should apply to oil companies in this new environment. Perhaps we should be using the last 5 years’ data as our baseline rather than the past 10? Rather than use these valuations to justify an investment, I suggest using them as a double check to ascertain that we are not buying something that is already overpriced. It is impossible to come to any firm conclusion, but at least we can see from these valuations that the sector is not overpriced.

Figure 6. Valuations for S&P Energy Sector

Industry Analysis: Refining and Marketing Refineries purchase crude oil and process it into a wide variety of refined products. The distillation process

“cracks” the molecules of crude oil apart and reassembles them into new molecules that are in most cases larger and lighter (less dense) than the original crude oil. This causes a refinery gain of about 5%—a 42 gallon barrel of crude oil will produce a little more than 44 gallons of distillates. The exact proportion of distillate yields will vary depending on the facility, process, and type of crude oil, but the largest yield is gasoline and heating oil. Figure 7

shows an abbreviated list of distillates from a typical of crude oil. There are many different grades of crude oil, differing in

density, viscosity and ease of refining. Cheaper grades of crude oil are harder to refine and are much harder to refine in compliance with environmental regulations. Refiners who have converted a percentage of their capacity to sour/heavy-capable are able to purchase those oils at a discount and sell the refined products at the same price as if they came from premium oils. The US also maintains some refineries that are only able to process premium light-sweet crude oils. Because these refineries are more expensive to operate, they are only used when domestic refineries are operating near full utilization.

US refinery capacity is another issue to consider when evaluating this industry. US refineries often operate at over 95% capacity, so any unexpected interruption (hurricanes, refinery

Figure 7. Refined Products (gallons) from a Barrel of Crude Oil

12

fires, etc.) can cause price shocks. More refinery capacity is eventually needed, but government regulations have made it very difficult to build refineries on US soil. Refiners are continually expanding existing facilities, but even this is becoming more difficult due to new EPA regulations.

Building refineries offshore is also not a good solution—it generally makes sense to site refineries close to consumers rather than wellheads. If refineries were built overseas, then many smaller transport ships would be needed to carry the refined products to market; shipping bulk crude oil utilizes the economies of scale of large tankers. Refineries situated close to the retail market can also modify their output to match seasonal surges in local demand for specific products. Lastly, governments are imposing an increasing number of restrictions on the quality of refined products. A refiner operating overseas might find that their products are not marketable in several large retail markets. With a few exceptions (Valero’s refining operations in the Caribbean are one exception) most refined products sold in the US are produced on US soil. The US will be facing a refinery capacity problem for some time to come. This means more volatility in the price of refined products, but also assures refiners of strong margins and good profits.

Company Analysis Sustainable Competitive Advantage?

The Energy sector is highly competitive and highly cyclical. Companies must make massive CapEx outlays, endure operational, regulatory, exchange rate and geopolitical risk, and still have their quarterly earnings largely dependent on crude oil prices and other factors over which they have no control. Even though this may seem to be a difficult and unattractive industry, I have identified a few key points that I believe give Valero a lasting competitive advantage:

The US refinery capacity is tight. Barriers to entry in the refinery business are extremely high. Capital outlays of at least a billion dollars would be needed to build a new refinery10. Current Federal regulations are so restrictive that it is essentially impossible to build a new refinery. So, the pool of available refineries is fixed, and Valero has expanded their capacity the only way possible—through timely acquisitions. Valero is currently the largest US refiner and holds nearly 20% of US capacity.

Valero has converted a large proportion of their capacity to sour/heavy capable. This allows them to capture significant additional profits due to the spread between heavy and light crude prices. However, I do not believe this is a sustainable competitive advantage. Other refiners are already making the same changes and within 5 years most of the industry will have the same capability Valero currently does.

Valero is integrated with a large midstream pipeline partner (Valero LP). This partnership, aside from cost savings, also eliminates possibility of holdup and assures their refined products a path to market. Shipments can be more tightly managed leading to increased efficiency.

Valero also has a large retail footprint. Retail margins are significantly less volatile than refining margins. The presence of a large retail operation has the effect of smoothing earnings.

Economies of scale count for something in this business. The giant Integrateds (Exxon, BP) dominate the industry through their economies of scale and scope. Valero is poised to develop similar strength in the refining industry through additional acquisitions.

Valero has an exceptionally experienced and able management team. Management has demonstrated good fiscal discipline and a commitment to adding value through acquisitions by being willing to walk away from projects when bidding wars develop. Valero has become an industry leader through a combination of organic projects and these well-managed acquisitions.

Financial Statements Analysis Valero’s 10-K reports present an exceptionally transparent set of financial statements (see Appendix 2) that

make it very easy to judge quality of earnings. In recent years, the story is a simple one. Two factors are driving Valero’s rising earnings: the spread between grades of crude oil and strong refinery margins. Valero has already converted a large percentage of their capacity to sour/heavy crude capable. These difficult to refine grades of crude trade at lower prices than light, sweet crude, so Valero is often purchasing and using oil $7 to $15 cheaper than the quoted WTI price. (Page 27 of the 2005 Company 10-K gives specific price differentials11.) The products refined

10 Based on conversations with Company IR representatives. 11 Available from http://www.valero.com/Investor+Relations/Financial+Reports+and+SEC+Filings/Form10-Ks/.

13

from those cheaper grades of crude are equivalent in all respects (though yields may be slightly different) and sell for the same price as products from more expensive crudes, so this savings passes directly to Operating Income. The spread between grades of crude oil shows a strong connection to price levels—cheaper grades of crude oil rise and fall in price more slowly than premium grades. It is reasonable to assume this spread will remain wide as long as oil prices are high.

Figure 8. Regression of West Texas Refinery Margins and WTI

Results of multiple regression for refinery margins

Summary measuresR-Square 0.7338Adj R-Square 0.7181StErr of Est 2.0741

ANOVA TableSource df SS MS F p-valueExplained 1 201.58 201.58 46.86 0.0000Unexplained 17 73.13 4.30

Regression coefficientsCoefficient Std Err t-value p-value Lower limit Upper limit

Constant -3.2898 1.4461 -2.2750 0.0361 -6.3407 -0.2389Crude Oil 0.2515 0.0367 6.8455 0.0000 0.1740 0.3290

Refinery margins in general have been strong as oil prices have risen. Average margin per barrel was $11.14

in 2005, up from $7.44 in 200412. Regression and correlation analysis shows that refinery margins have tracked crude oil quite closely. (See Figure 8 for a regression of WTI and West Texas refining margins which shows that approximately 72% of the variation in margins can be explained by variations in crude oil price.) As I modeled the future performance of Valero, I assumed strong refinery margins through the period of rising oil costs and reduced margins appropriately as prices began to fall in the forecast model.

Figure 9. DuPont Ratio Analysis for VLO

2001 2002 2003 2004 2005Profit Margin (Net Income ÷ Revenues) 3.76% 0.31% 1.64% 3.31% 4.37%Total Asset Turnover (Revenues ÷ Average Total Assets) 1.6x 2.01x 2.52x 3.12x 3.15xReturn On Invesment (PM * TAT) 6.03% 0.63% 4.13% 10.30% 13.76%

Equity Multiplier (Average Total Assets ÷ Average Total Equity) 3.3x 3.4x 3.x 2.6x 2.3x

Return on Equity (ROI * EM) 19.67% 2.15% 12.38% 26.69% 31.40% DuPont analysis is a useful tool that focuses attention on the three critical elements of good financial

management: operating management, asset management, and capital structure management. Figure 9 gives a complete DuPont analysis for 5 years of Valero’s financial statements. Profit Margin (Net Income ÷ Revenues) is a quick measure of operating management. If this ratio is rising across time, as Valero’s is, then management is controlling costs well while producing new revenues. The fiscal year 2002 numbers show a downward “blip” by most measures. Management’s claim at the time was that Valero sacrificed some short term gains in that year, took a loss on some divestments, and made some financing adjustments to prepare for stronger growth and new acquisitions in the coming years. At the time this might have seemed like a dubious claim, but the excellent performance in following years substantiates that claim.

Total Asset Turnover (Revenues ÷ Average Total Assets) is a measure of asset management, or what level of assets is needed to produce a fixed level of sales. If this ratio is rising, the firm is producing more sales from a given level of assets. However, all ratio-based performance measures are subject to manipulation, and extremely high TAT levels may indicate that a firm is not replacing assets when it should. This would be a sign of very poor asset management. Valero in some sense has no peer group because it is the largest independent US refiner. To make peer group comparisons with companies refining on the scale that Valero does, it was necessary to go to the big Integrateds and to separate their refining numbers from the other businesses in their statements. This analysis, 12 Valero 2005 10-K, pg. 25.

14

performed on 6 similar companies, showed TAT ratios ranging from 1.5x to 3.5x, so Valero seems to be within industry standards on Total Asset Turnover. Return on Investment is an intermediary measure of the profitability of the assets used by the firm. It should be rising over time. With the exception of 2002, Valero’s ROI shows excellent growth over the past 5 years.

The Equity Multiplier is a quick check on debt levels. It is the only DuPont ratio that should not be rising over time because a high EM can indicate excessively high debt and all the costs associated with high debt levels. Industrial firms in general seem to try to maintain Equity Multiples at 3 or below, so it seems Valero may have reached an acceptable capital structure after the 2002 restructuring.

Return on Equity is a measure of the profitability of the stakeholder’s investment in the firm, and should be as high as possible over time. However, ROE can be high for the wrong reasons (i.e. high Equity Multiple) so DuPont analysis cannot be simplified to only ROE. In this case, operating management is good (high PM), asset management is strong (high TAT), capital management is appropriate (appropriate EM), and ROE is high and rising. ROE can be assumed to be high for strong business reasons and the firm is judged to be in strong financial condition. Figure 10. Selected Financial Statement Ratios for VLO

2001 2002 2003 2004 2005Inventory Turnovers 8.8x 17.9x 20.1x 22.6x 22.6xDays in Inventory 42 20 18 16 16Accounts Receivable Turns 19.4x 24.9x 26.3x 34.5x 30.4xDave in Accounts Receivable 19 15 14 11 12Accounts Payable Turns 10.8x 18.1x 18.5x 20.8x 19.3xDays in Accounts Payable 34 20 20 18 19Operating Cycle (days) 60 35 32 27 28

A quick glance at some other ratios will confirm this assessment. Inventory turnover has increased greatly since 2001 and shows that Valero is making more revenue with fewer inventories. Days in Accounts Receivable is decreasing, showing that the Company is collecting its debts faster. Theoretically, we would like to also see an increase in Days in Accounts Payable, showing that Valero was able to pay its creditors a little more slowly and thereby hold the money within the firm longer. However, this may not be possible, and Valero’s increase in Accounts Payable turnover is not out of line with Accounts Receivable turnover. The bottom line to this analysis is that the Operating Cycle, a measure of how quickly the firm is able to convert assets to cash in hand, is decreasing across time. This is another indication of excellent management.

In all the financial statements, there are no unusual items or red flags. I did an extensive analysis of all tables and notes in the 10-K and also considered the effect of off-balance sheet items. None of these analyses had a material impact on the financial picture. The financial statements show strong growth, both organically and through acquisitions, and increased revenues driven by strong margins and economies of scale. Valero is a model of financial health and managerial excellence within the industry.

Equity Valuation: Multiples There are several difficulties with applying multiples valuations to Energy sector stocks at this time.

Table 2 shows common multiples applied to the 2008 values projected by the DCF model for Valero. The

entire energy sector is currently trading at low P/E multiples (currently 9.7x, 10 year average 15.1x, and 10 year high 41.9x). Since current figures may not be a useful guideline, I used the historical sector average P/E multiple in the valuation for VLO. Price/Book and Price/Free Cash Flow may not be particularly useful valuations for Energy stocks, but reasonable multiples applied to the asset growth predicted by the DCF model produce stock prices consistent with the DCF valuation itself. Price/Sales and Price/EBITDA are probably the most useful multiples for Energy sector valuations, and carrying forward the current multiples to projected 1998 numbers on those metrics also results in stock prices significantly above the current price.

15

Table 2. Relative Multiples Valuations for VLO (2008 projected numbers)

High Low Mean Current Target Multiple

Target (E,S,B, etc) per share

Target Price

P/Forward E n/a 2.60 7.10 7.80 15.0x $6.60 $99.00 P/Sales 0.51 0.10 0.19 0.47 .47x 201.7 $94.80 P/Book 3.60 0.60 1.30 2.70 2.0x 55.3 $110.60

P/EBITDA n/a 1.50 5.10 6.00 6.0x 16.1 $96.60 P/FCF 17.40 2.70 7.10 8.30 12.0x 7.8 $93.60

Multiples are an admittedly imprecise valuation shortcut, but this exercise has shown that reasonable

multiples estimates, applied to the revenue growth implied by the Crude Oil Regression model and the asset accrual calculated by the DCF model, give stock values that are in the range I am predicting. No sensitivity analysis has been done on these valuations because the predictions are obviously extremely sensitive to changes in either input. Again, rather than using multiples to justify an investment, I suggest using them as a “common sense” double check. In this case, they support the valuation implied by the other models.

Equity Valuation: Dividend Discount Model

Figure 11. Dividend Discount Model for VLO Terminal

Stage 1: High Growth Phase Stage 2: Low Growth Phase Value

Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016t= 1 2 3 4 5 6 7 8 9 10 11

Current Dividend $0.24 $0.30 $0.38 $0.47 $0.59 $0.73 $0.75 $0.78 $0.80 $0.82 $0.82k= 9.8% 9.8% 10.3% 10.5% 11.0% 11.3% 11.5% 11.8% 12.3% 12.5% 9.5%

Dividend Growth Rate 25.0% 25.0% 25.0% 25.0% 25.0% 3.0% 3.0% 3.0% 3.0% 3.0% 9.2%PV of Cash Flows $0.22 $0.25 $0.28 $0.31 $0.35 $0.39 $0.35 $0.32 $0.28 $0.25

PV of Terminal Value $101.26NPV $104.26

The Dividend Discount Model (DDM) is another common valuation technique used in the industry.

Finance theory says that a stock’s intrinsic value (“what it’s really worth”) is the present value of the future cash flows (dividends) from the stock. If it were possible to predict future dividends accurately, and to calculate the proper associated discount rates for each time period, it would be a trivial exercise to calculate intrinsic value. This is certainly a viable technique, but it is important to understand some of the difficulties involved in applying this method to Valero.

Predicting dividend payouts is not easy because companies may make dividend decisions based on many criteria. In some industries (Energy is one of them), there is no clear link between dividend policy and any income statement line. (I had several conversations with Valero’s Investor Relations department, who would not discuss specific issues of dividend policy beyond saying that the company has a general commitment to return value to shareholders.) In recent quarters, Valero has increased dividends with earnings, but it is difficult to say whether this represents ongoing payout policy, is intended as a signal to the market, or some combination of the two.

For the DDM, I predicted three stages of dividend growth and made the following assumptions: During the “oil boom” years predicted by the Crude Oil Regression model, Valero increases dividends 25% each year. This may seem high on a percentage basis, but is a reasonable dividend rate, basis the projected DCF Income Statement figures. The actual dollar amounts of the dividends are small because Valero’s 2005 dividend was only $0.19. (Note that the DCF model’s predicted dividend payouts are not a useful guide here because they reflect neither management’s attempts to target a specific payout rate nor management’s reluctance to reduce dividends in lean years.) During the “price collapse” years following 2010, Valero increases dividends 3% each year to keep pace with inflation. The company might, in fact, reduce dividends during these years, but I made the assumption that management would not reduce dividends in this environment. At any rate, the model is extremely insensitive to assumptions at this stage.

16

Figure 12. k Calculation for VLO DDM Explicit Forecast Terminal

Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016risk-free rate 5.25% 5.25% 5.50% 5.75% 6.00% 6.00% 6.00% 5.75% 5.75% 5.50% 5.25%

+ risk premium 4.50% 4.50% 4.75% 4.75% 5.00% 5.25% 5.50% 6.00% 6.50% 7.00% 4.25%= k 9.75% 9.75% 10.25% 10.50% 11.00% 11.25% 11.50% 11.75% 12.25% 12.50% 9.50%

In the DDM, the k value represents the return investors require to hold the stock and is equivalent to the

discount rate in a NPV calculation. It is a combination of the risk free rate (the rate on long-term US government debt) and a “risk premium” to compensate investors for the risk of holding the stock. I made the following assumptions in this model: the Fed has shown a proclivity in the past to keep rates high during times of high oil prices. There is no clear evidence (no correlation between Fed Funds Rate and oil prices) that the Fed takes specific action to reduce the inflationary impact of high oil prices, but they have exhibited a “pro cyclical” policy of only cutting rates when oil prices fall. Therefore, I predicted an increase in the risk free rate through the forecast period from 5.25% to 6%, only dropping the risk free rate after several years of declining oil prices. I assumed a baseline equity risk premium of 4.5% (based on what many I-banks are using in their models) and a baseline βVLO =1. As oil prices rise, the model assumes a small increase in the risk premium and only reduces it after several years of declining oil prices. Whether or not these are realistic assumptions, the model is nearly completely insensitive to these assumptions.

The problem with this DDM is that over 97% of the stock’s value resides in its terminal value. Thus, the model is extremely sensitive to very small changes in terminal value assumptions and extremely insensitive to assumptions in the explicit forecast period. In fact, the entire explicit forecast period could be zeroed out and the model would still give a stock price over $100. Table 3. Sensitivity Analysis of Terminal Assumptions in VLO's DDM

Terminal Dividend Growth Rate8.9% 9.0% 9.1% 9.2% 9.3% 9.4%

9.00% $322.47 n/a ($316.46) ($156.73) ($103.48) ($76.86)9.25% $92.01 $127.61 $210.68 $626.03 ($620.02) ($204.67)9.50% $53.63 $63.76 $78.95 $104.26 $154.89 $306.789.75% $37.86 $42.50 $48.58 $56.87 $68.84 $87.65

10.00% $29.27 $31.90 $35.11 $39.12 $44.28 $51.1610.25% $23.88 $25.55 $27.51 $29.84 $32.67 $36.16Te

rmin

al k

val

ue

Table 3 shows a sensitivity analysis of the terminal assumptions in the DDM. Finance theory also tells us

that competitive forces will tend to cause a firm’s long-term profits to revert to the mean (no firm can earn above-normal profits in the long run.) Because of this, the terminal growth rate cannot exceed the growth rate of the economy as a whole (long term inflation rate (3%-5%) + long term real GDP growth (2%-3%)) by more than a small amount. (In the case of an international company, world GDP is used rather than domestic GDP, resulting in final growth rates about a percent higher. Thus, the long-term growth rate window for international firms is 7%-10%.) I used a terminal growth rate of 9.2% and terminal discount of 9.5% which are reasonable assumptions by these criteria.

In the end, the DDM is probably not a very useful tool for Valero, and this should be viewed more as an academic exercise than a valid estimate of intrinsic value. DDM gives most accurate valuations in the case of firms which have stable or predictable growth rates, stable leverage, and which already pay out high dividends which approximate FCFE. Energy sector stocks currently violate all of those assumptions—earnings are anything but stable and predictable, leverage is difficult to predict because of very large required CapEx, and many energy companies pay out very small dividends. Certainly, most of the “problems” associated with the terminal value in this DDM come from the very small $0.19 starting dividend payment. Using this valuation as another reality check, we find again that the predicted stock price is consistent with the DCF model and that only reasonable terminal growth assumptions are required to support the predicted stock price.

17

Equity Valuation: Discounted Cash Flow The best intrinsic value assessment for Valero comes from the Discounted Cash Flow Model (DCF)

presented in Appendix 4. The model itself is a fairly standard DCF, but some of inputs were derived through examination of historical data, peer group data or regression modeling. Accounts from the Company’s financial statements were combined and, in some cases, re-categorized to facilitate comparisons to other Energy sector companies. (Complete DCF valuations like this one were run on 12 Energy stocks.) The general procedure followed was:

The Crude Oil Price Forecast regression model in Appendix 1 was created and tested. Appropriate inputs for regional supply and demand growth (blue text on yellow background in the model) were chosen and a forecast for crude oil price to 2015 was created (see Figure 2).

Regression analysis was done on VLO quarterly earnings and crude oil price. Expectations were that changes in crude price, rather than the absolute level, would have been more significant, but the regression showed a strong link between actual nominal crude oil price level and revenues. Quarterly and annual data were both used in this process—the quarterly to give more resolution and the annual to give more breadth. The resulting Revenue Regression Model is in Appendix 2.

The forecast crude price was then used as the input to the Revenue Regression Model. This produced a forecast revenue stream for VLO. The DCF model allows for multiple revenue cases and modifications, so the EIA cases were used as secondary case inputs. Peer group assessment and comparison to consensus13 were used as a check at this stage.

Figure 13. Schematic: Deriving the Revenue Forecast

Crude Oil Regression Model Crude Oil Forecast

Supply/Demand Estimates

VLO Revenue Regression Model

Peer Group(12 companies)

Revenue Regression Model

Output to DCF Model Revenue Projection

DCF Modeling Assumptions: Income Statement o Revenues: Regression Model. o CoGS: Based on peer group (group of 12 refiners) observation and regression of CoGS against

revenues. o SGA: Set as % of Revenues. Modeled moving average of last 3 years. o Depreciation: Modeled in a separate DCF module. Based on a percentage of prior year’s net PPE

balance and also with depreciation as a percent of revenue. o Interest Expense: Also a DCF sub-module. Company 10-K was analyzed for debt structure and

associated interest rates. Cash and Equivalents were assumed to be interest-earning. Actual interest expense/income calculated by model.

o Income Tax Expense: Assumed 34.2% tax rate. The model is insensitive to changes in corporate tax rate within reason.

o Dividend payout set as an average of last 3 years’ rate (% of net income). o Other income statement items were modeled based on extrapolations from past levels.

13 StockVal data were used.

18

DCF Modeling Assumptions: Balance Sheet o Surplus Funds: Reconciling item. Not interest-earning, and not included in working capital. o Cash: Set as % of revenues. o Receivables: Set as average of last 3 years’ Days Receivables. o Inventory: Modeled as percent of revenue based on peer group study. o CapEx: A major case input. CapEx historically had been 2.4% of revenues. Used this level as a

baseline going forward and only adjusted upward in strong earnings years. o Net PPE: Calculated dynamically as net of prior year’s PPE, CapEx and Depreciation. o Goodwill: Difficult to model without making assumptions about new acquisitions and impairment.

Model is completely insensitive to Goodwill assumptions so a gentle curve was used in the model. o Necessary to Finance: The balancing item for Surplus Funds plug. No interest cost associated. o Accounts Payable: Modeled as average of last 3 years’ Days Accounts Payable. o Long-term debt: Another major case input. Assumed less borrowing in good earnings years and more

in lean years. This seemed to be the pattern followed by the peer group as well. The companies did not finance CapEx during good years with debt and, in fact, paid off debt in good years. These tendencies were modeled in the DCF case.

o APIC: Held constant as percent of total asset value. o Other Equity Accounts: Assumed historical structure would carry forward unchanged. o Other Balance Sheet Accounts not listed: Modeled as % of revenues.

Free Cash Flow to the Firm was calculated and discounted at WACC which adjusted dynamically to changes in capital structure each year. Discount rate of 9.51% was suggested by CAPM and was accepted as reasonable. 5% terminal growth assumed. Implied terminal EBITDA multiple is 11.1x, which is reasonable for this industry.

Project EPS is out of the low end of consensus for 2006 and 2007, and near the middle of the range for 2008. The reason for this may be that the Crude Oil model is predicting lower prices at the end of 2006 than analysts expect. However, the model also predicts a string of years with strong revenue surges (2008: 56%, 2009: 16%, 2010: 19%). This is not out of line with recent history (2002: 94%, 2004: 44%, 2005: 50%).

Unlevered Free Cash Flow growth is volatile but consistent with VLO and peer group history. Figure 14. Unlevered Free Cash Flow YOY Growth as predicted by DCF

Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015UFCF YOY growth 53% (57%) 150% (41%) 76% (62%) 7% (50%) 78% 125%

The model gives an intrinsic value of $100.16/share, which is a 51.3% upside. Based on these assumptions and this model’s valuation, this stock is a strong BUY.

Using the EIA High Oil Price Case as the revenue driver, the model gives an intrinsic value of $105.72/share, which is a 59.7% upside. Based on these assumptions and this model’s valuation, this stock is a strong BUY.

Using the EIA Reference Oil Price Case as the revenue driver, the model gives an intrinsic value of $70.788/share, which is a 7.1% upside. Based on this oil price projection the stock is currently fairly valued and would be a HOLD.

19

Technical Position and Assessment

From a technical perspective, VLO appears to be in an extremely strong trend that is showing no signs of climax or overheat. This trend appears to be overdue for a retracement, but any downside should probably be considered a pullback in a healthy trend. $70.75 (the all-time high) provides resistance overhead and $55.50 should be an area of support.

Figure 15 is a monthly (log scale) chart of VLO with the following indicators: 20 period exponential moving average (XMA) in red surrounded by Keltner Channels at 2.5 average true ranges (20 period average) above and below the XMA. The XMA provides a rough baseline of what should be considered the mean price, and the Keltner channels are used to quantify “strong impulse” moves. The Keltners, set where they are, contain approximately 95% of the market action, so a market that spends an extended period of time against one of the bands, as VLO has, is in an extremely strong trend.

The 14-period ADX (orange line, bottom panel) shows a value above 50, though it is currently declining. This indicator is best understood to show the strength of the trend, with values above 30 indicating a strong trend. As the market pulls back, ADX will naturally fall, so this is not to be taken as a sign of impending trend change. The monthly chart shows an extended trend without any significant pullback to the XMA since mid 2003. This is unusually strong trending action, but we can safely say the market is overdue for a pullback. Notice also that recent activity (since mid 2005) is forming a gently rounding top, also indicating that the immediate move may be losing steam.

Figure 16 is a weekly chart of VLO that highlights some significant support and resistance points. A small double bottom was put in around $55.50 (mid May 2006 and early June 2006) and this area should provide support. This is also consistent with expectations from the monthly chart which would expect to see support around the 20 period XMA on an initial pullback. That average is currently below $54 but will move up every month. To the upside, $70.75 is the

all-time high put in on 4/25/06. An extremely ominous sign would be a brief excursion above this level and then a close below. Such a “failure test” at new highs can be a warning of serious price weakness and even possible trend change.

Bottom line technical forecast: expect that the next few months (6-8) could see price weakness in VLO. (The entire Energy sector and even crude oil futures prices are showing similar patterns.) This pullback, if it occurs, should be seen as an opportunity to add to longs. Look to $55.50 to provide first support to the downside, though a move that carried even into the $49-$50 range would not be cause for concern. Extended price action (either time or price level) below $48 would be a bad sign for integrity of the uptrend. To the upside, watch for $70.75 to provide initial resistance. If the market tests and fails at that level, I would suggest lightening long positions. Several

Figure 15. VLO Monthly Bars

Figure 16. VLO Weekly Bars

20

closes above this level would be confirmation of the resumption of the uptrend, though then we would have to be mindful of potential momentum divergences. Market geometry and structural ratios support the possibility of a price advance to $100.

Summary Strengths and Opportunities

Largest US refiner commanding 19% of total US refinery capacity. US refinery utilization is near full capacity and is unlikely to grow anytime in the foreseeable future. Economies of scope and scale apply in this industry—bigger players are able to extract more value in the form of earnings. The list of potential acquisition candidates is shrinking, so the Valero should be able to maintain its leadership position within the industry.

A large portion of Valero’s capacity is heavy/sour crude capable and Valero is continuing to convert existing capacity. While not a sustainable competitive advantage (other refiners lag behind Valero, but are in the process of making the same conversions), this does offer Valero increased earnings power in the short-term.

Valero seems to have found the ideal degree of integration into a midstream pipeline system. International exposure is limited. Company financials point to strong, well-managed growth and show good prospects for future growth.

There are no unusual items or red flags on the published financial statements. Future performance will be tightly correlated to energy prices. It seems reasonable to expect higher

energy prices at least through the end of the current decade and Energy sector returns should be above average.

Comprehensive DCF valuation suggests an intrinsic value far above the current stock price. The technical price structure of VLO also supports the possibility of a large price advance. The probabilities appear to be strongly in favor of a price advance to at least $95.

Risks and Concerns Future performance will be tightly correlated to energy prices. In the unlikely event that energy prices

fall dramatically, Valero’s earnings and stock price could be adversely affected. International growth potential is limited. Refinery margins and earnings are extremely volatile, even quarter to quarter. Refiners in general face large risks: operational risks (shutdowns, refinery fires, labor disputes),

regulatory risks (EPA and other Federal, State and local regulations), and increased taxes. These risks translate into above-average potential risk in the stock prices.

Some traditional valuation methods (DDM, multiples) do not apply well to energy stocks in the current environment. This may make it difficult to do a comprehensive valuation. However, it is my opinion that the DCF valuation is thorough and comprehensive enough to support a position in Valero at this time.

Conclusions The benefits clearly outweigh the potential risks for this stock. I am recommending Valero Energy

Corporation as an immediate BUY and am assigning a two year price target of $95. Extended price action below $48, a shift in the fundamentals of the underlying Energy markets, or a substantial change in Management would be cause to reassess this recommendation. The opinions and information contained herein have been obtained or derived from sources believed to be reliable, but the Fisher College of Business makes no representation as to their timeliness, accuracy or completeness or for their fitness for any particular purpose. This report is not an offer to sell or a solicitation of

an offer to buy any security. The information and material presented in this report are for general information only and do not specifically address individual investment objectives, financial situations or the particular needs of any specific person who may receive this report. Investing in any security or investment

strategies discussed may not be suitable for you and it is recommended that you consult an independent investment advisor. Nothing in this report constitutes individual investment, legal or tax advice.

21

Table of Figures Figure 1. WTI $/bbl (Inflation-adjusted)................................................................................................................................... 5 Figure 2. Brent Crude Oil US$ / bbl (predicted by regression)............................................................................................ 8 Figure 3. NYMEX Light Sweet Crude Futures, Monthly Bars.............................................................................................. 8 Figure 4. The Business Cycle in the Petroleum Industry ...................................................................................................... 10 Figure 5. Scatterplot of Cumulative Log Change Energy Index and WTI price.............................................................. 10 Figure 6. Valuations for S&P Energy Sector........................................................................................................................... 11 Figure 7. Refined Products (gallons)......................................................................................................................................... 11 Figure 8. Regression of West Texas Refinery Margins and WTI......................................................................................... 13 Figure 9. DuPont Ratio Analysis for VLO.............................................................................................................................. 13 Figure 10. Selected Financial Statement Ratios for VLO...................................................................................................... 14 Figure 11. Dividend Discount Model for VLO...................................................................................................................... 15 Figure 12. k Calculation for VLO DDM................................................................................................................................. 16 Figure 13. Schematic: Deriving the Revenue Forecast .......................................................................................................... 17 Figure 14. Unlevered Free Cash Flow YOY Growth as predicted by DCF...................................................................... 18 Figure 15. VLO Monthly Bars................................................................................................................................................... 19 Figure 16. VLO Weekly Bars ..................................................................................................................................................... 19 Table 1. NYMEX Light Sweet Crude Oil Futures................................................................................................................... 9 Table 2. Relative Multiples Valuations for VLO (2008 projected numbers) ..................................................................... 15 Table 3. Sensitivity Analysis of Terminal Assumptions in VLO's DDM........................................................................... 16

22

Appendix 1 Brent Crude Oil Price Forecast Results of multiple regression for Brent_Crude price

Summary measuresMultiple R 0.9997R-Square 0.9994Adj R-Square 0.9972StErr of Est 0.6222

ANOVA TableSource df SS MS F p-valueExplained 8 1378.4159 172.3020 445.0405 0.0022Unexplained 2 0.7743 0.3872

Regression coefficientsCoefficient Std Err t-value p-value Lower limit Upper limit

Constant 8040.5 613.3 13.1 0.0 5401.8 10679.2North_America -0.0173 0.0014 -12.4639 0.0064 -0.0233 -0.0114Cent_America 0.0070 0.0028 2.4640 0.1327 -0.0052 0.0193Europe 0.0036 0.0010 3.5947 0.0694 -0.0007 0.0078Middle_East 0.0019 0.0005 3.8176 0.0623 -0.0002 0.0040Africa 0.0175 0.0025 6.8861 0.0204 0.0066 0.0285Americas -298.9486 65.7456 -4.5471 0.0451 -581.8290 -16.0682Eurpoe -588.6594 51.5029 -11.4296 0.0076 -810.2586 -367.0601Asia_Pacific 83.1807 38.8649 2.1403 0.1657 -84.0413 250.4027

YOY Growth Rates For Regression Inputs

Date N_America C-America Europe Middle_East Africa Americas Europe Asia_Pac1995 n/a n/a n/a n/a n/a n/a n/a n/a1996 1.91% 6.51% 1.30% 2.01% 4.62% 3.19% (0.75%) 4.37%1997 1.53% 5.43% 1.61% 5.47% 4.40% 2.76% 0.94% 5.60%1998 (0.60%) 6.39% (0.27%) 5.71% (1.60%) 2.03% 0.45% (2.14%)1999 (3.55%) (3.02%) 1.98% (3.02%) (0.50%) 2.33% (0.43%) 4.12%2000 1.65% 1.71% 3.25% 5.36% 3.14% 0.69% (0.90%) 2.62%2001 0.01% (1.35%) 3.35% (2.68%) 0.95% 0.45% 0.91% 0.76%2002 1.17% (1.21%) 5.43% (6.12%) 1.31% 0.15% (0.08%) 3.07%2003 0.88% (4.11%) 4.20% 8.50% 5.19% 0.83% 0.90% 3.30%2004 (0.39%) (2.00%) 3.58% 5.55% 9.81% 3.28% 1.47% 5.49%2005 (3.54%) 0.00% (0.21%) 2.16% 6.14% 0.43% 0.77% 1.57%2006 1.00% 2.00% 1.00% 1.50% 2.00% 0.40% 0.50% 1.25%2007 (0.50%) 2.00% (0.50%) 2.00% 4.00% 0.40% 0.50% 3.00%2008 (1.00%) 2.50% 3.00% 3.00% 6.00% 0.40% 0.50% 2.50%2009 0.50% 2.50% 2.50% 4.00% 5.00% 0.40% 0.50% 1.50%2010 (1.00%) 4.00% 4.50% 4.00% 4.00% 0.40% 0.50% 1.00%2011 2.00% (1.50%) (0.50%) 2.00% 3.00% 1.00% 1.25% 2.00%2012 2.50% 1.00% 1.00% 2.00% 2.00% 1.00% 1.25% 2.50%2013 2.50% (2.00%) 2.00% 1.00% 3.50% 1.00% 1.25% 3.00%2014 3.50% 2.00% 1.50% (2.00%) 2.00% 1.00% 1.25% 3.50%2015 2.00% 1.00% 1.00% 3.00% 1.00% 1.00% 1.25% 4.00%

Supply Demand

proj

ecte

dhi

stor

ical

supp

lyde

man

d

23

Appendix 2 Valero Financial Statements from Company 10-K

Valero Energy Corporation

INCOME STATEMENT 2001 2002 2003 2004 2005

Revenues 14,988 29,048 37,969 54,619 82,162CoGS 12,745 25,863 33,587 47,797 71,673Refining Operating Expenses 846 1,332 1,656 2,141 2,926Retail Selling Expenses 6 675 694 705 771Administrative expenses 153 258 299 379 458EBITDA 1,239 920 1,733 3,597 6,334EBITDA Margin 8.3% 3.2% 4.6% 6.6% 7.7%

Depreciation 238 449 511 618 875EBIT 1,001 471 1,222 2,979 5,459EBIT Margin 6.7% 1.6% 3.2% 5.5% 6.6%

Equity& Min int: Valero LP 0 (14) 27 41 39Dist pref sec of subsid. Trusts (13) (30) (17) 0 0Interest and debt expense, net (89) (286) (261) (260) (266)Other income (expense), net (5) 9 15 (48) 52EBT 895 150 987 2712 5284EBT Margin 6.0% 0.5% 2.6% 5.0% 6.4%

Income tax expense 331.3 58.2 365.1 906.0 1,697.0Net Income 563.6 91.5 621.5 1,806.0 3,587.0Net Margin 3.8% 0.3% 1.6% 3.3% 4.4%

Dividends 0.0 0.0 4.3 13.0 13.0Net to ret'd earnings 563.6 91.5 617.2 1,793.0 3,574.0

24

Valero Energy Corporation

BALANCE SHEET 2001 2002 2003 2004 2005ASSETSSurplus funds 0 0 0 0 0Cash 269 379 369 864 436Restricted Cash 77 30 44 25 30Accounts receivable, net 771 1,558 1,328 1,839 3,564Inventories 1,453 1,436 1,913 2,318 4,039Deferred income tax assets 177 95 119 175 142Other current assets 1,389 38 45 45 65Current Assets 4,136 3,536 3,817 5,265 8,276

Net PPE 7,217 7,412 8,195 10,317 17,856Investment in Valero LP 0 0 265 265 327Intangibles 334 341 320 311 298Goodwill 2,211 2,580 2,402 2,401 4,926Deferred charges & other assets 502 596 665 833 1,045Total assets 14,400 14,465 15,664 19,392 32,728

LIABILITIESShort-term, current L/T, CLO 2,561 477 0 412 222Accounts Payable 1,390 1,825 2,288 2,963 5,563Accrued expenses 421 294 356 519 581Taxes, other than Income Taxes 320 368 365 480 595Income taxes payable 61 43 56 160 344Current Liabilities 4,753 3,007 3,064 4,534 7,305

Necessary to finance 0 0 0 0 0Long-term debt, less current 2,517 4,494 4,239 3,893 5,109Deferred income tax liabilities 1,388 1,301 1,605 2,011 3,615Cap. lease obligations 288 0 6 8 47Oblig. pref. sec of subsidiary trust 373 373 0 0 0Minority interest 116 116 0 0 0Other long-term liabilities 763 867 1,015 1,148 1,602Total Liabilities 10,197 10,157 9,929 11,594 17,678

SHAREHOLDER'S EQUITYPreferred stock 0 0 201 208 68Common stock 1 1 2 3 6APIC 3,469 3,437 3,921 4,358 8,164Treasury stock, at cost (150) (42) (41) (199) (196)Retained earnings 864 914 1,483 3,200 6,673Other equity 0 0 0 0 0Total SH equity 4,203 4,308 5,735 7,798 15,050Total Liabilities & SH equity 14,400 14,465 15,664 19,392 32,728

25

STATEMENT OF CASH FLOWS 2001 2002 2003 2004 2005Net Income $564 $92 $622 $1,804 $3,590Cash flows from operating activities Adjustments to reconcile net income to net cash provided by operating activities Depreciation and Amortization Expense 238 449 511 618 875 Gain on sale of investment in Javelina - - - - (55) Impairment of investment in Clear Lake Methanol Partners - - - 57 - Distributions in excess of (less than) equity in earnings of Valero LP - - (4) 1 4 Minority interest in net income of Valero LP - 14 2 - - Noncash interest expense and other income, net 15 (23) 2 10 27 Deferred income tax expense 271 2 287 345 255 Changes in current assets and current liabilities (153) (209) 429 203 1,082 Changes in deferred charges and credits and other, net (28) (53) (96) (80) 21 Net cash provided by operating activities 906 272 1,753 2,958 5,799

Cash flows from investing activities Capital expenditures (394) (628) (976) (1,292) (2,133) Deferred turnaround and catalyst costs (142) (152) (136) (304) (441) Buyout of assets under structured lease arrangements - - (275) (567) - Premcor Acquisition, net of cash acquired - - - - (2,343) Aruba Acquisition, net of cash acquired - - - (541) - St Charles Acquisition - - (309) - - Proceeds from sales of assets to Valero LP - - 380 - - Proceeds from sales of Tesoro notes - - 90 - - Proceeds from sale of the Denver Refinery - - - - 45 Proceeds from liquidation of investment in Diamond-Koch - 301 - - - Proceeds from disposition of the Golden Eagle Business - 925 - - - CapEx & other CF related to Golden Eagle Business - (184) - - - Proceeds from sale of investment in Javelina - - - - 78 General partner contribution to Valero LP - - (1) - (29) Contingent payments in connection with acquisitions (55) (24) (51) (53) (85) Other acuisitions, net of cash (2,717) - - - - (Investment) return of investment in Cameron Highway Oil Pipeline Project - - (106) (36) 38 Proceeds from dispositions of PPE and certain home heating oil operations 8 16 94 108 30 Minor acquisitions and other investing activities, net (1) (7) (41) - (60) Net cash used in investing activities (3,302) 249 (1,331) (2,685) (4,900)

Cash flows from financing activities Cash payment to UDS shareholders in connection with UDS acq. - (2,055) - - - Financing required to fund cash portion of UDS acquisiton 2,053 - - - - Decrease in short-term debt, net 173 (47) (153) - - Repayment of capital lease obligations - - (289) (1) (2) Long-term debt borrowings, net of issuance costs 543 4,517 4,014 3,782 1,537 Long-term debt repayments (19) (2,828) (3,943) (3,718) (2,414) Proceeds from cash settlement of PEPS Unit purchase contracts - - 14 - - Redemption of company-obligated preferred securities of subsidiary trust - - (200) - - Proceeds from issuance of common units by Valero LO, net of issuance costs - - 200 - - Cash distributions to minority interest in Valero LP - (14) (4) - - Proceeds from the sale of common stock, net of issuance costs - - 250 406 - Issuance of common stock in connection with employee benefit plans 78 102 99 135 227 Common and preferred stock dividends (21) (42) (51) (79) (106) Purchase of treasury stock (157) (46) (73) (318) (571) Other - - - - (2) Net cash provided by (used in) financing activities 2,651 (412) (136) 207 (1,331)Valero LP's cash balance as of the date that we ceased consolation of Valero LP - - (336) - - Effect of foreign exchange rate changes in cash - 1 40 15 4Net increase (decrease) in cash and temporary cash investments 255 110 (10) 495 (428)Cash and temporary cash investments at beginning of year 15 269 379 369 864Cash and temporary cash investments at end of year 269 379 369 864 436

26

Appendix 3 Valero Revenue Regression Model and Inputs

Results of simple regression for Smoothed Quarterly Earnings

Summary measuresMultiple R 0.9791R-Square 0.9586StErr of Est 1411.4739

ANOVA tableSource df SS MS F p-valueExplained 1 830728797 830728797 417 0.0000Unexplained 18 35860655 1992259

Regression coefficientsCoefficient Std Err t-value p-value Lower limit Upper limit

Constant -5324.37 916.01 -5.81 0.00 -7248.85 -3399.90Crude_Oil 443.04 21.70 20.42 0.00 397.46 488.63

Date Oil VLO Revenue Oil VLO Revenue Oil VLO Revenue12/1/2015 47.79 63,395 66.41 96,392 76.30 113,91212/1/2014 46.90 61,821 73.34 108,681 73.31 108,62412/1/2013 47.37 62,659 83.94 127,458 70.67 103,93712/1/2012 47.65 63,142 89.27 136,896 67.64 98,57212/1/2011 47.34 62,604 96.78 150,208 64.99 93,87412/1/2010 47.29 62,503 103.85 162,747 62.65 89,73212/1/2009 50.14 67,567 89.47 137,263 61.12 87,02112/1/2008 52.30 71,390 78.95 118,611 59.87 84,79612/1/2007 55.62 77,269 63.08 90,497 59.26 83,72712/1/2006 59.10 83,438 54.90 75,996 59.10 83,43812/1/2005 59.43 82,162 59.43 82,162 59.43 82,16212/1/2004 43.33 54,619 43.33 54,619 43.33 54,61912/1/2003 32.15 37,969 32.15 37,969 32.15 37,96912/1/2002 29.42 26,976 29.42 26,976 29.42 26,97612/1/2001 19.33 14,988 19.33 14,988 19.33 14,98812/1/2000 28.46 14,671 28.46 14,671 28.46 14,67112/1/1999 26.08 7,961 26.08 7,961 26.08 7,96112/1/1998 11.28 5,539 11.28 5,539 11.28 5,53912/1/1997 18.32 5,756 18.32 5,756 18.32 5,75612/1/1996 25.39 4,991 25.39 4,991 25.39 4,991

LegendInputs

OutputsHistorical

His

toric

alPr

ojec

ted

Valero Energy Corporation Projected Annual Earnings, 3 Oil Price Cases

EIA Reference Case EIA High Case Regression Model Case

27

Sum

mar

y V

alua

tion

DC

F In

puts

Mar

ket

DC

FC

ase

Ass

umpt

ions

Sto

ck P

rice

$66.

20$1

00.1

6R

even

ue C

ase

5

Rev

enue

cas

e: B

rent

Reg

ress

ion

Dilu

ted

Sha

res

588.

058

8.0

CoG

S C

ase

2

CoG

S C

ase:

Cus

tom

Sce

nario

Equi

ty M

arke

t Val

ue38

,926

58,8

92C

apE

x C

ase

4

Cap

Ex c

ase:

Cus

tom

Sce

nario

Net

Deb

t(3

89)

(389

)L/

T D

ebt C

ase

4

Long

-Ter

m D

ebt C

ase:

Cus

tom

Sce

nario

Ente

rpris

e Va

lue

38,5

3758

,503

Val

ue p

er S

hare

10.8

x16

.4x

Pro

j EP

SD

CF

assu

mpt

ions

Ent

erpr

ise

Val

ue M

ultip

le6.

1x9.

2x E

BIT

DA

r (C

AP

M)

Impl

ied

Ups

ide

in D

CF

51.3

%O

ptio

ns0.

0ris

k-fre

e ra

te5.

05%

Avg

Stri

ke P

rice

0.0

risk

prem

ium

4.50

%Ta

x ra

te34

.2%

β (o

verri

de)

Ter

min

al V

alue

Gro

wth

5.0%

β (R

eute

rs)

0.99

Dis

coun

t Rat

e9.

51%

β (Y

ahoo

!)0.

9β

(Cal

cula

ted)

1.00

His

toric

alPr

ojec

ted

VALU

ATIO

N A

NAL

YSIS

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

t=-2

-10

12

34

56

78

910

Free

Cas

h Fl

ow C

alcu

latio

n E

BIT

1,22

22,

979

5,45

95,

458

4,09

89,

491

6,81

49,

928

5,89

65,

057

3,20

03,

429

5,89

7

+ D

epre

ciat

ion

511

618

875

1,35

81,

345

1,43

51,

579

1,72

91,

859

1,98

92,

099

2,17

42,

203

EBIT

DA

1,73

33,

597

6,33

46,

816

5,44

410

,926

8,39

311

,658

7,75

57,

046

5,29

95,

603

8,10

0 -

Cap

Ex

(976

)(1

,292

)(2

,133

)(1

,809

)(1

,990

)(2

,964

)(3

,430

)(3

,873

)(3

,575

)(3

,258

)(3

,033

)(2

,586

)(2

,294

)EB

ITD

A le

ss C

apEx

757

2,30

54,

201

5,00

73,

454

7,96

24,

963

7,78

44,

181

3,78

82,

266

3,01

75,

806

- ta

xes

on E

BIT

(418

)(1

,018

)(1

,866

)(1

,866

)(1

,401

)(3

,244

)(2

,329

)(3

,394

)(2

,015

)(1

,728

)(1

,094

)(1

,172

)(2

,016

) -

Cha

nges

in W

orki

ng C

apita

l(2

44)

(105

)47

81,

165

(208

)(1

10)

7336

3(3

63)

(130

)(2

04)

(123

)77

Unl

ever

ed fr

ee c

ash

flow

961,

182

2,81

34,

307

1,84

64,

608

2,70

64,

753

1,80

21,

929

968

1,72

23,

867

17.8

6%18

.24%

35.3

5%46

.21%

66.4

8%10

0.00

%92

.50%

92.5

0%14

4.36

%16

7.06

%19

8.08

%18

2.82

%16

6.62

%D

CF

Ente

rpris

e Va

lue

Cal

cula

tion

Term

inal

val

ue c

alcu

latio

n P

roje

cted

Fre

e C

ash

Flow

4,06

0 T

erm

inal

Ent

erpr

ise

Val

ue90

,130

Im

plie

d Te

rm. V

alue

EB

ITD

A M

ultip

le11

.1x

Deb

t / V

alue

Rat

io16

%17

%16

%17

%18

%23

%25

%27

%24

%24

%W

ACC

8.8%

8.7%

8.8%

8.8%

8.7%

8.5%

8.4%

8.3%

8.4%

8.4%

Cum

ulat

ive

Dis

coun

t Fac

tor

8.8%

18.3

%28

.7%

40.0

%52

.2%

65.1

%79

.0%

93.9

%11

0.2%

127.

9%

Dis

coun

ted

Cas

h Fl

ows

PV

of u

nlev

ered

free

cas

h flo

w2,

813

3,95

91,

560

3,58

01,

933

3,12

31,

091

1,07

849

981

91,

697

PV

of t

erm

inal

val

ue36

,352

Tot

al D

isco

unte

d C

ash

Flow

s2,

813

3,95

91,

560

3,58

01,

933

3,12

31,

091

1,07

849

981

938

,049

NPV

58,5

03

Appendix 4 Valero Discounted Cash Flow Model

28

I

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

2000 2002 2004 2006 2008 2010 2012 2014

Breakdown of Liability and Equity AcctsSHEOther Non-Cur LiabsLong Term DebtCurrent Liabilities

Capital Structure

0

50,000

100,000

150,000

200,000

250,000

2000 2002 2004 2006 2008 2010 2012 2014

total assetscurrent liabilitiesnoncurrent liabsshe

Debt/Equity Ratio

0%

25%

50%

75%

100%

2000 2004 2008 2012

value%debt%

Indexed Case Inputs (last historical year=100%)

0%

50%

100%

150%

200%

250%

1999 2001 2003 2005 2007 2009 2011 2013 2015

Rev

enue

Inde

x (B

lue)

CoG

S In

dex

(Red

)

-20%

-10%

0%

10%

20%

30%

40%

50%

Rev

enue

5 y

ear C

AG

R (g

reen

)

Margin and EPS Analysis

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

Gross Margin

OperatingMargin

EBT Margin

Net Margin

8% 9% 9%10

%11

%12

%12

%4.00%

4.67%

5.33%

6.00%-50%

0%

50%

100%

150%

200%

250%

Impl

ied

Ups

ide/

Dow

nsid

e

Discount Factor

Terminal Growth Rate

Sensitivity of Upside Downside to Discount Factor and Terminal Growth

Sensitivity of Implied Upside/Downside to Discount Factor and Terminal Growth Rate0.8%

51.3% 7.75% 8.50% 9.25% 10.00% 10.75% 11.50% 12.25%4.00% 91.5% 61.1% 39.6% 23.5% 11.1% 1.2% 6.8%4.33% 104.7% 69.6% 45.4% 27.6% 14.1% 3.5% 5.0%4.67% 120.8% 79.5% 52.0% 32.3% 17.5% 6.1% 3.1%5.00% 140.7% 91.4% 59.6% 37.5% 21.3% 8.9% 0.9%5.33% 166.2% 105.7% 68.6% 43.6% 25.5% 12.0% 1.4%5.67% 199.7% 123.4% 79.3% 50.5% 30.3% 15.4% 4.0%6.00% 246.1% 145.9% 92.1% 58.6% 35.8% 19.3% 6.8%

Sensitivity of Implied Upside/Downside to Beta (top) and Tax Rate (side)51.3% 0.3 0.7 1.0 1.3 1.6 2.0

30% 352.3% 135.3% 60.6% 24.7% 6.4% 11.5%32% 338.7% 128.1% 55.5% 20.6% 2.9% 14.5%34% 325.2% 120.8% 50.4% 16.6% 0.6% 17.4%36% 311.6% 113.5% 45.3% 12.5% 4.1% 20.4%38% 298.1% 106.2% 40.2% 8.5% 7.6% 23.4%

29

VLO

Vale

ro E

nerg

y C

orp.

(Reu

ters

Dat

a)

His

toric

alPr

ojec

ted

INC

OM

E ST

ATEM

ENT

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Tota

l Rev

enue

14,6

7114

,988

29,0

4837

,969

54,6

1982

,162

75,9

9675

,997

118,

611

137,

263

162,

747

150,

208

136,

896

127,

458

108,

681

96,3

92C

ost o

f Rev

enue

, Tot

al13

,760

13,5

9127

,195

35,2

4349

,938

74,5

9967

,637

69,1

5810

5,56

412

6,28

214

8,10

013

9,69

312

7,31

411

9,81

110

1,07

386

,511

Gro

ss P

rofit

912

1,39

81,

853

2,72

64,

681

7,56

38,

360

6,84

013

,047

10,9

8114

,647

10,5

159,

583

7,64

77,

608

9,88

0 G

ross

Mar

gin

6.2%

9.3%

6.4%

7.2%

8.6%

9.2%

11.0

%9.

0%11

.0%

8.0%

9.0%

7.0%

7.0%

6.0%

7.0%

10.3

%

Sel

ling/

Gen

eral

/Adm

in. E

xpen

ses,

Tot

al12

715

993

399

31,

084

1,22

91,

544

1,39

62,

121

2,58

82,

990

2,75

92,

537

2,34

82,

004

1,78

0R

esea

rch

& D

evel

opm

ent

00

00

00

00

00

00

00

00

Dep

reci

atio

n/A

mor

tizat

ion

174

238

449

511

618

875

1,35

81,

345

1,43

51,

579

1,72

91,

859

1,98

92,

099

2,17

42,

203

Inte

rest

Exp

ense

(Inco

me)

- N

et O

pera

ting

00

00

00

00

00

00

00

00

Oth

er O

pera

ting

Exp

ense

s, T

otal

00

00

00

00

00

00

00

00

Ope

ratin

g In

com

e61

11,

001

471

1,22

22,

979

5,45

95,

458

4,09

89,

491

6,81

49,

928

5,89

65,

057

3,20

03,

429

5,89

7 O

pera

ting

Mar

gin

4.2%

6.7%

1.6%

3.2%

5.5%

6.6%

7.2%

5.4%

8.0%

5.0%

6.1%

3.9%

3.7%

2.5%

3.2%

6.1%

Inte

rest

Inco

me(

Exp

ense

), N

et N

on-O

per

(76)

(89)

(286

)(2

61)

(260

)(2

66)

(348

)(4

13)

(554

)(7

23)

(965

)(1

,443

)(1

,656

)(1

,864

)(1

,601

)(1

,629

)O

ther

, Net

(7)

(18)

(36)

26(9

)94

4239

8782

100

9785

8069

60EB

T52

889

515

098

72,

710

5,28

75,

152

3,72

49,

024

6,17

39,

063

4,55

13,

486

1,41

61,

896

4,32

9E

BT

Mar

gin

3.6%

6.0%

0.5%

2.6%

5.0%

6.4%

6.8%

4.9%

7.6%

4.5%

5.6%

3.0%

2.5%

1.1%

1.7%

4.5%

Inco

me

tax

expe

nse

189

331

5836

590

61,

697

1,76

11,

273

3,08

52,

110

3,09

81,

556

1,19

148

464

81,

480

Equ

ity In

Affi

liate

s0

00

00

00

00

00

00

00

0M

inor

ity In

tere

st0

00

00

00

00

00

00

00

0N

et In

com

e B

efor

e Ex

tra.

Item

s33

956

492

622

1,80

43,

590

3,39

12,

451

5,94

04,

063

5,96

52,

995

2,29

493

21,

248

2,84

9

Acc

ount

ing

Cha

nge

00

00

00

Dis

cont

inue

d O

pera

tions

00

00

00

Ext

raor

dina

ry It

em0

00

00

0N

et In

com

e33

956

492

622

1,80

43,

590

3,39

12,

451

5,94

04,

063

5,96

52,

995

2,29

493

21,

248

2,84

9N

et M

argi

n2.

3%3.

8%0.

3%1.

6%3.

3%4.

4%4.

5%3.

2%5.

0%3.

0%3.

7%2.

0%1.

7%0.

7%1.

1%3.

0%

Div

iden

ds19

2344

4977

112

172

102

245

181

253

128

9940

5412

2N

et to

ret'd

ear

ning

s32

054

147

573

1,72

63,

478

3,21

92,

349

5,69

53,

882

5,71

22,

867

2,19

589

21,

195

2,72

7

Dilu

ted

Wei

ghte

d A

vera

ge S

hare

s24

2.1

255.

244

0.4

488.

055

2.2

588.

058

8.0

588.

058

8.0

588.

058

8.0

588.

058

8.0

588.

058

8.0

588.

0E

PS

$1.4

0$2

.21

$0.2

1$1

.27

$3.2

7$6

.11

$5.4

7$4

.00

$9.6

9$6

.60

$9.7

1$4

.88

$3.7

3$1

.52

$2.0

3$4

.64

30

His

toric

alPr

ojec

ted

BAL

ANC

E SH

EET

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

ASSE

TSS

urpl

us fu

nds

00

00

00

100

3,10

016

,604

23,7

7335

,380

46,5

8551

,324

55,2

6250

,426

53,5

33C

ash

& E

quiv

alen

ts15

269

379

369

864

436

684

950

1,77

92,

059

2,44

12,

253

2,05

31,

912

1,63

01,

446

Sho

rt Te

rm In

vest

men

ts0

00

00

00

00

00

00

00

0To

tal R

ecei

vabl

es, N

et58

694

81,

558

1,32

81,

839

3,56

42,

837

2,89

74,

699

5,26

56,

298

5,84

25,

291

4,93

94,

213

3,73

2To

tal I

nven

tory

540

1,45

31,

436

1,91

32,

318

4,03

94,

560

4,56

05,

931

6,86

38,

137

7,51

06,

845

6,37

35,

434

4,82

0P

repa

id E

xpen

ses

3986

3845

4565

152

114

170

226

248

230

215

196

168

150

Oth

er C

urre

nt A

sset

s, T

otal

106

1,38

012

616

220

017

238

027

242

255

660

756

852

748

341

436

8C

urre

nt A

sset

s1,

285

4,13

63,

536

3,81

75,

264

8,27

68,

713

11,8

9429

,604

38,7

4253

,112

62,9

8866

,255

69,1

6562

,284

64,0

48

Net

PP

E2,

677

7,21

77,

412

8,19

510

,317

17,8

5618

,307

18,9

5120

,480

22,3

3124

,475

26,1

9027

,459

28,3

9428

,806

28,8

97G

oodw

ill, N

et0

2,21

12,

580

2,40

22,

401

4,92

64,

926

5,20

04,

940

4,69

34,

458

4,23

54,

024

3,82

23,

631

3,45

0In

tang

ible

s, N

et59

334

341

320

311

298

760

570

835

1,12

31,

233

1,14

11,

066

975

835

743

Long

Ter

m In

vest

men

ts0

00

265

265

327

684

760

909

1,22

01,

440

1,27

21,

196

1,10

793

883

7O

ther

Lon

g Te

rm A

sset

s, T

otal

287

502

596

665

833

1,04

51,

520

1,90

02,

135

2,88

33,

472

3,02

12,

849

2,64

52,

234

1,99

6To

tal a

sset

s4,

308

14,4

0014

,465

15,6

6419

,392

32,7

2834

,910

39,2

7558

,902

70,9

9188

,190

98,8

4710

2,84

810

6,10

898

,728

99,9

71

LIAB

ILIT

IES

Not

es P

ayab

le/S

hort

Term

Deb

t27

506

477

00

00

00

00

00

00

0C

urre

nt P

ort.

of L

T D

ebt/C

apita

l Le

00

00

412

222

259

346

422

527

648

570

530

495

418

373

Acc

ount

s P

ayab

le80

71,

390

1,82

52,

288

2,96

35,

563

4,48

34,

615

7,30

48,

512

10,0

389,

516

8,62

88,

134

6,86

65,

871

Acc

rued

Exp

ense

s10

442

129

435

651

958

165

763

995

41,

148

1,34

61,

236

1,13

51,

053

898

797

Oth

er C

urre

nt li

abili

ties,

Tot

al10

12,

436

411

421

639

939

867

875

1,35

81,

572

1,86

71,

721

1,56

91,

461

1,24

61,

105

Cur

rent

Lia

bilit

ies

1,03

94,

753

3,00

73,

064

4,53

47,

305

6,26

66,

475

10,0

3811

,759

13,8

9913

,043

11,8

6111

,143

9,42

78,

145

Nec

essa

ry to

fina

nce

00

00

00

00

00

00

00

00

Cap

ital L

ease

Obl

igat

ions

028

80

68

4747

4747

4747

4747

4747

47Lo

ng T

erm

Deb

t1,

215

2,89

04,

867

4,23

93,

893

5,10

95,

236

6,28

48,

835

11,3

5914

,992

21,7

4624

,684

27,5

8823

,695

23,9

93M

inor

ity In

tere

st0

116

116

00

00

00

00

00

00

0D

efer

red

Inco

me

Tax

407

1,38

81,

241

1,60

52,

011

3,61

53,

118

3,08

74,

968

5,65

26,

709

6,22

35,

650

5,26

54,

493

3,98

2O

ther

Lia

bilit

ies,

Tot

al12

076

392

71,

015

1,14

81,

602

1,70

31,

594

2,48

62,

944

3,43

93,

182

2,91

02,

701

2,30

52,

045

Tota

l Lia

bilit

ies

2,78

110

,197

10,1

579,

929

11,5

9417

,678

16,3

7117

,486

26,3

7431

,761

39,0

8644

,240

45,1

5246

,744

39,9

6638

,212

SHAR

EHO

LDER

'S E

QU

ITY

Red

eem

able

Pre

ferre

d S

tock

, Tot

a0

00

00

00

00

00

00

00

0P

refe

rred

Sto

ck -

Non

Red

eem

able

00

020

120

868

6868

6868

6868

6868

6868

Com

mon

Sto

ck, T

otal

11

12

36

66

66

66

66

66

Add

ition

al P

aid-

In C

apita

l1,

249

3,46

93,

437

3,92

14,

358

8,16

48,

431

9,36

914

,323

17,1

1421

,248

23,8

9424

,812

25,6

0423

,835

24,1

25Tr

easu

ry S

tock

- C

omm

on(4

4)(1

50)

(42)

(41)

(199

)(1

96)

(180

)(2

13)

(299

)(3

52)

(427

)(3

86)

(354

)(3

30)

(281

)(2

49)

Ret

aine

d E

arni

ngs

(Acc

umul

ated

D32

286

491

41,

483

3,20

06,

673

9,89

212

,241

17,9

3621

,818

27,5

3030

,397

32,5

9233

,485

34,6

7937

,406

Oth

er E

quity

, Tot

al0

18(1

)17

022

933

532

331

749

457

567

962

757

253

245

440

3To

tal S

H e

quity

1,52

74,

203

4,30

85,

735

7,79

815

,050

18,5

3921

,788

32,5

2839

,230

49,1

0454

,607

57,6

9659

,364

58,7

6261

,759

Tota

l Lia

bilit

ies

& S

H e

quity

4,30

814

,400

14,4

6515

,664

19,3

9232

,728

34,9

1039

,275

58,9

0270

,991

88,1

9098

,847

102,

848

106,

108

98,7

2899

,971

31

VLO

Vale

ro E

nerg

y C

orp.

(Reu

ters

Dat

a)

His

toric

alPr

ojec

ted

RAT

IO A

NAL

YSIS

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

DuP

ont A

naly

sis

Pro

fit M

argi

n2.

3%3.

8%0.

3%1.

6%3.

3%4.

4%4.

5%3.

2%5.

0%3.

0%3.

7%2.

0%1.

7%0.

7%1.

1%3.

0%To

tal A

sset

Tur

nove

r3.

4x1.

x2.

x2.

4x2.

8x2.

5x2.

2x1.

9x2.

x1.

9x1.

8x1.

5x1.

3x1.

2x1.

1x1.

xR

OI

7.9%

3.9%

0.6%

4.0%

9.3%

11.0

%9.

7%6.

2%10

.1%

5.7%

6.8%

3.0%

2.2%

0.9%

1.3%

2.9%

Equ

ity M

ultip

lier

2.8x

3.4x

3.4x

2.7x

2.5x

2.2x

1.9x

1.8x

1.8x

1.8x

1.8x

1.8x

1.8x

1.8x

1.7x

1.6x

RO

E22

.2%

13.4

%2.

1%10

.8%

23.1

%23

.9%

18.3

%11

.2%

18.3

%10

.4%

12.1

%5.

5%4.

0%1.

6%2.

1%4.

6%

Acc

ount

s R

ecei

vabl

e Tu

rnov

er25

.x19

.5x

23.2

x26

.3x

34.5

x30

.4x

23.7

x26

.5x

31.2

x27

.6x

28.1

x24

.7x

24.6

x24

.9x

23.8

x24

.3x

Acc

ount

s R

ecei

vabl

e in

Day

s14

.618

.715

.713

.910

.612

.015

.413

.811

.713

.213

.014

.714

.814

.615

.415

.0

Inve

ntor

y Tu

rnov

er25

.513

.618

.821

.023

.623

.515

.715

.220

.119

.719

.717

.917

.718

.117

.116

.9In

vent

ory

Day

s14

.326

.819

.417

.315

.515

.623

.224

.118

.118

.518

.520

.420

.620

.121

.321

.6

Acc

ount

s P

ayab

le T

urno

ver

17.1

12.4

16.9

17.1

19.0

17.5

13.5

15.2

17.7

16.0

16.0

14.3

14.0

14.3

13.5

13.6

Acc

ount

s P

ayab

le in

Day

s21

.429

.521

.621

.319

.220

.927

.124

.020

.622

.922

.925

.526

.025

.527

.126

.9

Ope

ratin

g C

ycle

7.5

15.9

13.6

9.9

6.8

6.7

11.5

13.8

9.2

8.9

8.6

9.6

9.4

9.2

9.6

9.8

Cur

rent

Rat

io1.

20.

91.

21.

21.

21.

11.

41.

82.

93.

33.

84.

85.

66.

26.

67.

9Q

uick

Rat

io0.

60.

30.

60.

60.

60.

50.

60.

60.

60.

60.

60.

60.

60.

60.

60.

6C

FO/C

urre

nt L

iabi

litie

s0.

60.

30.

10.

50.

81.

00.

00.

00.

00.

00.

00.

00.

00.

00.

00.

0

Sol

venc

y R

atio

sD

ebt t

o V

alue

0.6

0.7

0.7

0.6

0.6

0.5

0.5

0.4

0.4

0.4

0.4

0.4

0.4

0.4

0.4

0.4

Deb

t to

Equ

ity1.

82.

42.

41.

71.

51.

20.

90.

80.

80.

80.

80.

80.

80.

80.

70.

6In

tere

st C

over

age

Rat

io8.

011

.31.

64.

711

.520

.515

.79.

917

.19.

410

.34.

13.

11.

72.

13.

6

Wor

king

Cap

as

% o

f Rev

enue

s1.

8%(2

.5%

)2.

2%1.

0%0.

5%0.

9%2.

5%2.

3%1.

4%1.

2%1.

3%1.

1%1.

1%1.

1%1.

1%1.

3%C

apE

x as

% o

f Rev

enue

s1.

2%1.

6%1.

5%1.

3%1.

1%1.

1%1.

3%1.

3%1.

2%1.

2%1.

2%1.

3%1.

2%1.

2%1.

2%1.

2%C

apE

x as

% P

rior Y

ear P

PE

na8.

9%6.

2%6.

9%7.

5%8.

5%7.

6%7.

3%7.

6%7.

7%7.

7%7.

6%7.

6%7.

6%7.

7%7.

6%