Statergy mgmt

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Implementation of Risk Management Strategies

Organizing and motivating employees to take prudent risks

– Developing incentives consistent with a risky environment.

– Decentralization and the risk of “gambler’s ruin”.

Evaluating risk attitudes

– Systematically assessing utility functions.

– Applying utility functions to real world problems.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Incentives for Risky Decisions

Middle management may be conservative (risk averse) because they use their own outcomes rather than the company’s outcomes as the basis for decisions.

Sure Thing

Risky Alternative

Success .5

Failure .5

Company’s Outcomes

$1,000,000

-$100,000

$100,000

Manager’sOutcomes

Promotion

Fired

Pat on Back

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Decentralization and “Gambler’s Ruin” Decentralization has the advantage of making the

most knowledgeable individuals responsible for decisions.

In a risky environment, decision makers may become too conservative because of the fear of “gambler’s ruin”.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Example: Suppose in Algeria there are 100 prospects with the following description:

Success (0.2)

Failure (0.8)

$10,000,000

-$1,000,000

EV = $1,200,000

Suppose Algeria is decentralized into 20 fields, each with a drilling budget of $5,000,000.

If a manager decides to spend his budget drilling 5 of these prospects in a year, the P(no discovery) is 0.805 =0.33.

Compare this to the P(no discovery) in the centralized firm, that is, 0.8020 =0.01

Decentralization requires the implementation of one of the two alternative personnel evaluation plans described below to avoid conservative decision making.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Establishing Appropriate Incentives Alternative 1: Managers must be given the opportunity to

develop a track record over a large number of risky decisions.

Alternative 2: Managers must be evaluated on the basis of their decisions rather than on the basis of the outcomes.

– Making the distinction between decision and outcome allows us to separate action from consequence - and hence improve the quality of action.

– Requires a more sophisticated personnel evaluation system.

– Encourages documentation of the basis of decisions at the time they are made, and before the outcomes are known.

– Encourages more group decision making, and the responsibility for risky decisions is shared.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Limitations of Expected Value

The Firm Does not Possess an Unlimited Pool of Exploration Capital

The Firm is Not Risk Neutral

EMV Fails to Provide Guidance on Limiting the Downside Exposure.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

EMV - Unlimited Pool of Capital?

Firm has an Exploration Budget of $20 Million and the Opportunity to Invest in the Following Four Drilling Prospects:

Prospect Outcome Value Probability EMV

1 Success $40mm 0.20 Dry Hole -$5mm 0.80 $4mm

2 Success $15mm 0.10 Dry Hole -$5mm 0.90 -$3mm

3 Success $20mm 0.50 Dry Hole -$8mm 0.50 $6mm

4 Success $80mm 0.25 Dry Hole -$20mm 0.75 $5mm

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Unlimited Pool of Capital? EMV Decision Rule: Invest in Prospects 1, 3 & 4.

Total Required Capital: $33 million

Total Exploration Budget: $20 million

Deficiency $13 million

How do we Choose Among (Rank) Prospects with Positive Net Present Values?

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

EMV - The Firm is Risk Neutral? Consider the Following Decision Alternatives

Fair Coin Flip: Heads: Win $2

Tails: Lose $1

Would you accept this Gamble?

Your entire fortune is $10 million. You are offered the following fair coin flip:

Fair Coin Flip: Heads: Win $20 million

Tails: Lose $10 million

Would you accept this Gamble? Most people say “YES” to the First Gamble and “NO” to the Second.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

EV - Failure to Provide Guidance on Limiting Downside Exposure

Consider the Following Two Drilling Ventures:

Expected Value of A = Expected Value of B?

EMV does not Consider the Magnitude of Money Exposed to the Chance of Loss.

0.500.500.800.80

$200M$200M

-$40M-$40M

$88M$88M

-$20M-$20M

Prospect BProspect BProspect AProspect A

0.200.20 0.500.50

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk Methods Used in Making Decisions by Energy Companies

Method Number Percent

Alter the required rate of return on a project aftercalculating a risk measure.

17 7.2

Alter the required rate of return on a project usingsome non-quantitative risk-adjustment method.

73 30.3

Calculate expected cash flows as part of aprobability distribution of possible outcomes.

Make a subjective adjustment to estimated cashflows.

35 14.8

Change the required payback period for the project. 20 8.4

Use sensitivity analysis to assess possibleoutcomes.

68 28.7

Use other risk adjustment methods. 11 4.6

Totals 237 100

(J. Battle, 1986)

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

A Comment on Risk-Adjusted Discount Rates No separation between risk discounting and time value of money

discounting.

– Time and risk are logically separate variables.

– Combining the variables into one risk-adjusted discount rate (RAD) can bias the valuation results.

Inconsistencies with respect to risk and valuation where projects have different durations.

– Management may be biased against long-term projects.

– Uncertainty must be resolved at a constant rate over time.

Arbitrary methodologies for determination of RAD.

– The firm’s cost of capital does not represent a single project risk or even a specific class of projects.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk-adjusted discount rate - An Example

Long Life Venture

.2

.8

-10 - 100/(1+i)3 + 500/(1+i)10

-10

($MM)Short Life Venture

.2

.8

-10 + 60/1+i

-10

($MM)

Short Life Long Life Discount Rate NPV if Success NPV if Success

10% $44.5 MM $107.0 MM

20% $40.0 MM $ 12.8 MM

Valuation bias caused by combining risk discounting and time value of money discounting.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Preference or Expected Utility Theory

Dominant approach to the theory of decision making in both economics and finance.

Establishes the process of modeling an individual or firm’s risk propensity.

Enables decision maker to incorporate risk attitudes into the decision process.

Provides the firm a technique for determining the appropriate level of diversification.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Attitudes Toward Risk Most researchers believe that if certain basic behavioral

assumptions hold, people are expected utility maximizers - that is, they choose the alternative with the largest expected utility.

An individual’s utility function is a mathematical function that transforms monetary values - payoffs and costs - into utility values.

Essentially an individual’s utility function specifies the individual’s preferences for various monetary payoffs and costs and, in doing so, it automatically encodes the individual’s attitudes toward risk.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Attitudes Toward Risk -- continued Most individuals are risk averse, which means intuitively that

they are willing to sacrifice some EMV to avoid risky gambles.

Utility functions are said to be increasing and concave. This means they go uphill and they increase at a decreasing rate.

There are two problems in implementing utility maximization in a real decision analysis:

– The first is obtaining an individual's utility function.

– The second is using the resulting utility function to find the best decision.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Assessing a Utility Function

To estimate a person’s utility function we present the person with a choice between the following two options:

– Option 1: Obtain a certain payoff of z (really a loss if z is negative) .

– Option 2: Obtain a payoff of either x or y, depending on the flip of a fair coin.

We ask the person to select the monetary value of z so that he or she is indifferent. This value is known as the indifference value.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

The Session

Susan first asks John for the largest loss and largest gain he can imagine.

He answers with values $200,000 and $300,000, so she assigns values U(-200000) = 0 and U(300000) = 1 as anchors for the utility function.

She presents John with the choice of two options:

– Option 1: Obtain a payoff of z (really a loss if z is negative)

– Option 2: Obtain a loss of $200,000 or a payoff of $300,000, depending on the flip of a fair coin.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

The Session -- continued

Susan reminds John that the EMV of option 2 is $50,000 (halfway between $200,000 and $300,000).

He realizes this but since he is risk averse he would far rather have $50,000 for certain than take the risk in Option 2. Therefore the indifference value of z must be less than $50,000.

Susan then poses several values of z to John:

– Would he rather have $10,000 for sure or Option2?

• He said he would take the $10,000.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

The Session -- continued– Would he rather pay $5,000 for sure or take Option 2.

• He says he would take Option 2.

By this time we know the indifference value is less than $10,000 and greater than -$5,000.

After a few more questions John finally decides on z=$5000 as his indifference value.

John is giving up $45,000 in EMV because of his risk aversion. The EMV of Option 2 is $50,000 and his willing to accept a sure $5000 in its place.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

The Session -- continued

The process continues until she helps John assess enough utility values to approximate a continuous utility curve.

As this example illustrate utility assessment is tedious and can even be more complicated for a company than for an individual because of the different attitudes of the executives.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Comments on Preference Assessment

Choice among preference assessment procedures should be based on ease of use by the decision maker.

Assess preferences on outcomes that represent realistic ranges of outcomes for the decision maker.

Individuals are not perfectly consistent and since some risks are more meaningful than others, it makes sense to use the range that corresponds to the problem at hand.

Check for consistency of preferences.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Win $4000 with probability of 0.40

Win $2000 with probability of 0.20

Win $0 with probability of 0.15

Lose $2000 with probability of 0.25

Step 1. Find the Expected Utility

EU = 0.4U($4000) + 0.2U($2000) + 0.15U($0) + 0.25U(-$2000

= 0.4(1) + .2(.81) + .15(.65) + .25(.4)

= 0.76

Step 2. Find the certainty equivalent.

Approximately $900

Step 3. Find the expected value.

EV = $1500

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-3000 -2000 -1000 0 1000 2000 3000 4000

Wealth

Uti

lity

Consider the following utility function and gamble. . .

Step 4. Find the risk premium.

Risk Premium = EV - CEQ

$600 = $1500 - $900

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

What is the dominant choice, given the decision maker’s utility function?

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 2000 4000 6000 8000 10000

Wealth

Uti

lity

Consider the following investment choices. . .

A

B

.5

.7

.1

.4

.3

$10,000

$4,000

$0

$8,000

$2,000

EV = $6600

EV = $6200

Example 6.9

Incorporating Attitudes Toward Risk

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Background Information

Venture Limited is a company with net sales of $30 million.

The company currently must decide whether to enter one of two risky ventures or do nothing.

The possible outcomes of the less risky venture are a $0.5 million loss, a $0.1 million gain, and a $1 million gain.

The probabilities of these outcomes are 0.25, 0.50, and 0.25.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Background Information -- continued The possible outcomes of the more risky venture are

a $1 million loss, a $1 million gain, and a $3 million gain.

The probabilities of these outcomes are 035, 0.60, and 0.05.

If Venture Limited can enter at most one of the two risky ventures, what should they do?

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk Aversion - Functional Forms Utility functions might be specified in terms of a graph or utility

curve.

Alternatively, utility functions may be expressed in terms of a mathematical form.

Three general categories of risk aversion and their mathematical form:

– Decreasing Risk Aversion (Log) u(x) = log (x + c)

– Increasing Risk Aversion (Power) u(x) = xc

– Constant Risk Aversion (Exponential) u(x) = -e-cx

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Constant Risk Aversion

– Condition which implies that the risk premium is the same for gambles that are identical except for adding the same constant to each payoff.

– The risk premium does not depend on the initial amount of wealth held by the decision maker.

Preference Function

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-10000 0 10000 20000 30000 40000 50000

Wealth ($)

Uti

lity

p = 0.5

1 - p = 0.5

$20,000

-$10,000

Expected Value = $5,000Expected Utility = 0.32CEQ = $2,800Risk Premium = $2,200

where,

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Now consider again the case when we add a constant to each of the payoffs in the lottery. . .

p = 0.5

1 - p = 0.5

$20,000

-$10,000

(A)

$30,000

$0

(B)

$40,000

$10,000

(C)

$50,000

$20,000

(D)

Expected Value:

Expected Utility:

Certainty Equivalent:

Risk Premium:

$5,000

0.32

$2,800

$2,200

$15,000

0.52

$12,800

$2,200

$25,000

0.68

$22,800

$2,200

$35,000

0.82

$32,800

$2,200

If we know the DM’s CEQ of only one lottery, we can easily determine the CEQ of any other lottery over the range.

It is reasonable to use the exponential utility function as an approximation in modeling preferences and risk attitudes.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Exponential Utility

One important class is exponential utility, which has only one adjustable numerical parameter, and there are straightforward ways to discover the most appropriate value of this parameter for an individual or company.

An exponential utility function has the following form:U(x) = 1 - e-x/R

x is the monetary value, U(x) is the utility of this value and R>0 is an adjustable parameter called the risk tolerance.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Exponential Utility -- continued Risk tolerance measures how much risk the decision maker will

tolerate.

To assess a person’s exponential utility function, we need only to assess the value of R. A couple tips for doing this are:

– The first tip is that the risk tolerance is approximately equal to that dollar amount R such that the decision made is indifferent between the following two options:

• Option 1: Obtain no payoff at all.

• Option 2: Obtain a payoff of R dollars or a loss of R/2 dollars, depending on the flip of a fair coin.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Exponential Utility -- continued– The second tip is for finding R is based on empirical

evidence found by Ronald Howard. He found that R was approximately 6.4% of net sales, 12.4% of net income, and 15.7% of equity for the company.

• These percentages are just guidelines.

• They do indicate that larger companies have larger values of R.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Solution

We will assume Venture Limited has an exponential utility function.

Based on Howard’s guidelines, we will assume that the company’s risk tolerance is 6.4% of its net sales, or $1.92 million.

Using the exponential utility formulas we can find the utility of any monetary outcome.

– The gain for doing nothing is $0 and its utility is 0.

– The utility of a $1 million loss is -0.683.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

The Decision Tree

PrecisionTree takes care of all the details of building the decision tree.

We label it in the normal way and then we click on the name of the tree to open a dialog box.

We then fill in the utility function information - an exponential utility function with risk tolerance 1.92. It also indicates that we want expected utilities (as opposed to EMVs) to appear in the tree.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

VENTURE.XLS

This file contains the input values for the tree.

We build it in exactly the same way as usual and link probabilities and monetary values to its branches in the usual way.

However, the expected values shown in the tree (those shown in color) are expected utilities and the optimal decision is the one with the largest expected utility.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Interpretation

The optimal decision is to invest in the less risky venture.

From an EMV point of view, the more risky venture is definitely best.

However, venture Limited is sufficiently risk averse, and the monetary values are sufficiently large, that the company is willing to sacrifice the EMV to reduce its risk.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Interpretation -- continued How sensitive is the optimal decision to the key parameter, the

risk tolerance?

We can answer this by changing the risk tolerance and watching how the decision tree changes.

– When the risk tolerance increases to approximately $2.075 million the company is more risk tolerant.

– When the risk tolerance decreases the “do nothing” decision becomes optimal.

Thus we can see that the optimal decision depends heavily on the attitudes toward risk of Venture Limited’s top management.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Certainty Equivalents

Now suppose Venture only had two options, enter the less risky venture or receive a certain dollar amount x and avoid the gamble altogether.

– If it enters the risky venture, its expected utility is 0.0525, calculated previously.

– If it receives x dollars for certain, its expected) utility is approximately $0.104 million.

This value is called the certainty equivalent of the risky venture.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Decision Tree with Certainty Equivalents

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk Sharing - An Investment Example

Project B

Project A

.4

.1

.3

.2

$700,000

$100,000

-$50,000

-$450,000

.4

.1

.3

.2

$800,000

$200,000

-$100,000

-$500,000

$0

Invest

Do not Invest

EV = $210,000 at 100%

EV(B) = $185,000

EV(A) = $210,000

Share vs. Expected Value

0

50

100

150

200

250

020406080100

Project Share (%)

$M

Project A

Project B

• Risk neutral evaluation indicates a linear relationship between share and expected value of each alternative.

• Project A dominates in all cases.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Now suppose we use the following utility function. . .

Preference Function

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-500 0 500 1000 1500

Wealth ($)

Uti

lity

Project B

Project A

.4

.1

.3

.2

$700,000

$100,000

-$50,000

-$450,000

.4

.1

.3

.2

$800,000

$200,000

-$100,000

-$500,000

$0

Invest

Do not Invest

CEQ = $0Do not Invest

CEQ(B) = -$30,000

CEQ (A) = -$85,000

...and analyze our investment problemon the basis of certainty equivalents.

With no risk-sharing, do not take either project, since Project A has a CEQ of -$85,000 and Project B has a CEQ of -$30,000.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Now consider the CEQ evaluation at different project shares using our utility function. . .

Share vs. Certainty Equivalent

-100

-75

-50

-25

0

25

50

020406080100

Project Share (%) CEQ ($M)

Project A

Project B

Project A

Project B

With a 50-50 partnership, take Project “A” since it has a CEQ of $$50,000 and is better than Project “B” at that level of risk-sharing.

Provides valuable insights concerning firm’s optimal share in individual, as well as groups of, risky projects.

Willingness to participate in risky projects can be systematically incorporated into project evaluation.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Measuring Risk Tolerance

Suppose the Firm Rejects Expected Monetary Value as the Basis for Making Risky Decisions. What do we do?

Our Goal is to Construct a Preference Scale that:

– Encodes the Firm’s Attitude Towards Financial Risk

– Can be Used with Probabilities to Compute Certainty Equivalents (CEQ)

A Number of Practical Approaches for Measuring Risk Tolerance are Available

– Industry-specific Questionnaires

– Analysis of Prior Decisions

– Industry Empirical Analysis

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

SSG Utility Function Worksheet Make Participation Choices Among a Set of Exploration Prospects as Part of Your

Annual Budget Process

Prospect Outcome Value Prob. Choice (W.I. Level)

1 Success $75mm 0.50 100% 75% 50% 25% 0% Dry Hole -$30mm 0.50

2 Success $45mm 0.15 100% 75% 50% 25% 0% Dry Hole -$3mm 0.85

3 Success $22mm 0.30 100% 75% 50% 25% 0% Dry Hole -$4mm 0.70

4 Success $16mm 0.80 100% 75% 50% 25% 0% Dry Hole -$9mm 0.20

5 Success $16mm 0.20 100% 75% 50% 25% 0% Dry Hole -$1.4mm 0.80

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

RT & Analysis of Past Decisions Proposition: Analysis of Recent Resource Allocation Decisions Represents

Firm’s Exhibited Risk Tolerance Level.

Study:

Offshore Bid Sale

Firm: BP Exploration, Inc.

Prospects: 60 Offshore Drilling Blocks

Decisions: Bid on 48 Blocks (8 at 100%)

Note: All Blocks Had Positive Expected NPV’s.

Findings: BP exhibited a risk tolerance (RT) level of between $30-$40 million. Firm maintained “consistent” risk attitude on about 50% of prospect decisions. Suggests firm was either highly inconsistent in its risk preferences or that other considerations influenced the bids.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk Tolerance & Financial Measures

Howard (1988) suggest that the firm’s RT (1/c) can be closely related to financial measures such as sales, net income and equity.

Cursory study of oil and chemicals industry: Risk Tolerance/Sales 0.064 Risk Tolerance/Net Income 1.240 Risk Tolerance/Equity 0.157

Measure RatioAnnualReport

RiskTolerance RAL (c)

Net Sales 0.064 $3,500 MM $224 MM 0.005Net Income 1,240 $130 MM $161 MM 0.006

Equity 0.157 $1,700MM $267 MM 0.004

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk Tolerance (RT) And Firm Performance

There Exists an Abundance of Evidence that Firms Behave in a Risk-Averse Manner.

From a Business Policy Perspective We are Compelled to Ask:

– What is the appropriate risk tolerance level for the firm?

– What effect, if any, does corporate risk policy have on firm performance?

Empirical Setting and Analysis

– 66 of the Largest U.S. Based Oil & Gas Firms

– Period of Investigation: 1981-1990

– Risk Tolerance Model Development includes domestic/foreign budget allocations, leasehold, exploratory and development costs, success rates, reserve additions, etc.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Corporate RT - An Industry Look

CORPORATE RISK TOLERANCE ($MM)

Year Phillips Exxon Shell UTP Texaco1990 18.4 24.9 85.4 10.6 22..7

1989 21.0 18.9 62.7 13.2 281.3

1988 34.1 20.8 64.4 12.1 10.9

1987 27.4 16.5 37.5 10.9 12.0

1986 21.4 16.8 34.3 14.3 12.4

1985 19.1 16.1 43.4 9.6 10.2

1984 19.8 18.0 44.8 12.3 15.7

Risk Tolerance Measure Provides Valuable Insight into Risk Propensity of Industry Competition.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk Tolerance versus Firm Size

For the entire period 1983-1990, there exists a significant positive relationship between corporate risk tolerance and firm size.

7.6 8.0 8.4 8.8 9.2 9.6 10.0 10.4 10.8

Log (RT) vs. Log (SMCF)

Log (RT)

Year: 1983-19908.6

8.2

7.8

7.4

7.0

6.6

6.2

5.8

5.4

Regression Line Log (SMCF) Observed Data

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk Tolerance - Comparing Firms

Risk Tolerance Ratio (RTR) - A New Approach for Comparing Risk Tolerance Among Firms of Different Size.

RTR = RTi/RT’, where

– RTi is the Observed Risk Tolerance for Firm i in Period t and RT’ represents the Predicted Risk Tolerance of Firm i as a Function of Size.

RTR Provides Valuable Insight Concerning Competitor’s Relative Propensity to Take on Risk.

RTR Provides Guidance on Setting and Communicating an Appropriate Risk Policy.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Risk Tolerance Ratio

Firm X Firm Y Firm Z

SMCF (Size) $1000MM $100MM $10MM

RT’ (Predicted) $ 100MM $ 15MM $ 2MM

RTi (Actual) $ 50MM $ 20MM $ 2MM

RTR (RTi/RT’) 0.50 1.33 1.0

RTR>1.0 (<1.0) Implies a Stronger (Weaker) Propensity to Take on Risk Than Firms of Equivalent Size.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

RTR - A Relative Measure of Risk CORPORATE RISK TOLERANCE RATIO

Year Phillips Exxon Shell UTP Texaco

1990 1.16 0.62 3.46 1.15 0.93

1989 1.24 0.37 2.39 1.74 7.41

1988 2.58 0.71 3.39 1.78 0.56

1987 2.60 0.59 2.10 1.66 0.69

1986 2.03 0.73 2.19 2.21 0.72

1985 1.78 0.80 2.83 1.20 0.67

1984 1.58 0.79 2.60 1.50 0.85

RTR Measure Points to Firm’s Relative Risk Propensity Compared to Industry Competition.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

RTR - The Performance Implications

RETURN ON E&P ASSETS

Risk Tolerance Ratio

High Moderate Average Low(>2.5) (1.5 - 2.5) (0.5-1.5) (<0.5)

Mean 5.0% 9.1% 5.7% 5.3%

Stand. Dev. 2.5% 6.4% 5.0% 3.1%

Conf. Int. 3.3-6.9 8.1-10.7 5.6-7.7 3.8-7.2

E&P Firms Exhibiting Moderate Risk Tolerance Demonstrate Significantly Higher Returns than Firms Either More or Less Risk Tolerant.

6.2 | 6.3 | 6.4 | 6.5 | 6.6 | 6.7 | 6.8 | 6.9

Summary of Concepts Regarding the Estimation of a Risk Attitude Makes explicit a corporate attitude toward risk taking

Can assure a constant risk attitude in different divisions/regions of a company

May allow comparisons with the risk attitudes of other companies in the same industry

Can be used to rank prospects, to determine shares, and to select the “best” portfolio from efficient ones