Student Investment Management SIM Program

1

• Student Investment Management (SIM) Program

A Presentation to Ohio State Universitys
Alumni Leaders Conference, October 6,
2006 Professor Andrew Karolyi, SIM
Director Jeremy Sell, MBA 07, SIM Student
Manager Adam Grimes, MBA 07, SIM Student
2
What is SIM?

• SIM is a 21 million student-run stock portfolio
  administered by the Department of Finance in the
  Fisher College of Business and overseen by the
  OSU Treasurers office Board of Trustees
• It is the largest student-run portfolio in the
  U.S.
• As of today, over 1,750 students have graduated
  from the program since its inception in 1990,
  many have pursued careers in asset management

3
Outline

• Objectives of the Program
• Investment Philosophy
• Investment Process
• Performance Review Jeremy Sell
• Valero Energy Stock Report Adam Grimes

4
Objectives

• 1. To achieve a total return in excess of the
  Standard and Poors (SP) 500 Index
• 2. To preserve and maintain the real purchasing
  power of the fund
• 3. To enhance the educational experience of
  students
• Total classroom experience
• Exposure to latest market information technology
• Quarterly class trips to major financial centers

5
2006 Class Trip to Chicago
6
Outline

• Objectives of the Program
• Investment Philosophy
• Investment Process
• Performance Review Jeremy Sell
• Valero Energy Stock Report Adam Grimes

7
Investment Philosophy

• The market is frequently inefficient in the short
  run
• Inefficiencies can be identified through rigorous
  and timely fundamental analysis
• Qualitative factors
• Quantitative factors
• Diversification is a useful means to manage risk

8
Outline

• Objectives of the Program
• Investment Philosophy
• Investment Process
• Performance Review Jeremy Sell
• Valero Energy Stock Report Adam Grimes

9
Investment Process

• Investment process follows hybrid approach
• Top-Down analysis
• Current macroeconomic environment
• Sector analysis
• Bottom-Up stock selection
• Fundamental drivers
• Many valuation methods used

10
Investment Process

• Each student participates as a member of a sector
  team, an individual stock analyst and a member of
  overall investment committee
• Class is structured in three phases
• Macroeconomic Analysis
• Develop projections for economic growth, monetary
  policy and interest rates and inflationary
  environment in U.S. and globally
• Sector Analysis
• Relative valuation of sectors in the current
  market cycle
• Overweight/underweight decision voted on by class
• Stock Analysis
• Model and review current holdings and new
  possible holdings.
• Stock analysts present to the class and vote on
  decision.

11
Investment Process Cont.

• Students have revealed value-oriented style
  recently
• Key investment factors they tend to address
• Has the company recently run into trouble and is
  in a turnaround?
• Is the macroeconomic environment set to make
  earning profits easier for this company or its
  sector?
• Is the company poised to develop a new product?
• Has management changed with new ideas flowing
  into the company?
• Has the company been ignored by investors?

12
Outline

• Objectives of the Program
• Investment Philosophy
• Investment Process
• Performance Review Jeremy Sell
• Valero Energy Stock Report Adam Grimes

13
Performance of the Fund
Period ending June 30, 2006
14
Performance of the Fund Cont.
15
Performance of the Fund Cont.
16
Portfolio Overview
Period ending September 29, 2006
17
Overview Sector Allocation

• Overweight Health Care, Telecom, and Technology
• Underweight Utilities, Consumer Staples,
  Consumer Discretionary

18
Recent Sector Changes
19
Top 10 Holdings Changes YOY
20
Recent SP Performance
Period ending Sept 29, 2006
21
Outline

• Objectives of the Program
• Investment Philosophy
• Investment Process
• Performance Review Jeremy Sell
• Valero Energy Stock Report Adam Grimes

22

• Adam Grimes
• Fisher College of Business

23
Sector Returns vs. Price of Oil

• Conventional wisdom says Energy sector companies
  make more money when oil prices are high.
• But is this true? And does this equal higher
  stock prices?
• Created an equal-weighted annual log change index
  of the Energy sector dating back to 1988.

24
Yes A strong correlation exists
25
The Oil Price Model Thesis

• Its all about oil.
• Goal was to make a limited-scale (large models
  have thousands of moving parts) supply/demand
  regression model for oil price.
• A complicated task
• relevant data not readily available.
• increased supply does not always mean lower price
  (because at some times and price ranges, supply
  is the dependent variable).
• If possible, would provide an apples to apples
  baseline across the sector.

26
World Demand

• Current (2006) world use is 86.8 million
  barrels/day.
• Projected to grow about 2.1 per year.
• Much of the new demand is from China and India.
  (China is the second largest world consumer of
  oil, and responsible for 40 of the world demand
  growth in the past four years.)
• Depletion of working fields is 4 mmb/d annually
  (and accelerating).
• Total new additions of 27.5 mmb/d are needed to
  meet demand to 2010.

27
Supply

• Realistic estimates for new additions are 6-8
  mmb/d.
• Even the most optimistic forecasts (CERA) are for
  11.5 mmb/d additions.
• Demand forecasts are 27.5 mmb/d

28
The Oil Price Model Assumptions

• Central America will continue supply growth
  linearly.
• Asia will continue to have problems getting its
  oil to world supply.
• Africa will do very well increasing supply.
• Middle East will increase 3/year, but will
  flood market after 2010.
• Demand not seriously constrained by higher prices
  (some roll-off above 80/bbl). Once prices fall,
  demand is robust.

29
The Oil Price Model Output
30
Valero Energy Corporation (NYSEVLO)

• Largest independent US refiner. Capacity of 3.3
  mbd (crude throughput) is 19 of total US
  capacity.
• High proportion of capacity is heavy/sour
  capable. This has allowed them to capture the
  spread between sweet/sour crude.
• Most new reserves are sour. Is this a
  sustainable competitive advantage?
• Extensive retail network allows them to capture
  retail margins which are less volatile than
  refining margins.
• Ideal level of integration into pipelines and
  distribution networks.

31
Valero Energy Corporation

• Management has demonstrated excellence in
  managing growth through organic projects and
  timely acquisitions.
• Refining margins should remain strong through
  2010
• Little to no excess capacity. No new refineries
  expected soon.
• Has also shown fiscal discipline by being willing
  to walk away from projects.

32
VLO Modeling Assumptions

• Revenue used Oil Price Model
• (R2.9586, p-value lt 710-16)
• CoGS depends on refining margins (which in
  themselves depend on the price of oil), but
  presence of retail operations smooth out
  fluctuations in margins.
• CapEx tracks revenues closely (based on
  historical data for VLO and examination of peer
  group). Will be no large CapEx outlay for new
  refineries. Expenditures will continue as in
  the past for upgrading refineries to heavy/sour
  and to comply with EPA restrictions.
• Capital Structure less borrowing in good
  years.
• Margins are very volatile through 2010. Refinery
  margins increase above historical highs (not
  above current 2006 numbers) for the
  supply-constrained periods. Margins get hit hard
  when new supply comes on-line after 2010.
• 9.51 discount rate. 5 terminal growth rate.

33
VLO DCF Case Analysis
34
VLO DCF Summary
35
VLO Sensitivity Analysis
36
VLO Summary of Strengths and Risks

• Strengths
• Largest independent US refiner.
• Large capacity for sour crude. Expanding that
  capacity.
• Good financials.
• Strong management.
• Performance will be tightly correlated to energy
  prices.

• Risks
• Operational risks fires, shutdowns.
• Regulator risks EPA.
• Highly volatile earnings.
• Performance will be tightly correlated to energy
  prices.

37
VLO Summary Recommendation

• Buy a large position. This is the major
  directional play for the sector.
• Not for the faint of heart. Possibility of 4-6
  month pull back and expect a wild ride!
• Potential for large gains outweigh the risks.
• Position size will be determined by sector
  weighting.

38
Questions?