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Managerial Goals

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2nd square the difference. 3rd multiply each squared difference by its probability ... 5th take square root. Standard Deviation. Beef cattle ... – PowerPoint PPT presentation

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Title: Managerial Goals


1
Managerial Goals
2
Goal of Financial Management
  • Profitability
  • Risk
  • Liquidity
  • Taken together, these elements determine the
    well-being of the firm
  • Decisions on investments, financing, growth
    rates, and capital structure are evaluated
    according to these criteria

3
Goal Identification
  • Increase Profitability
  • Reduce Risk
  • Provide Liquidity

4
Profitability
  • Profit difference between value of goods and
    services produced by the firm and the cost of
    resources used in production
  • Perfectly competitive markets MAX profit
  • MVP MIC
  • MR MC

5
Effects of Time
  • Want to grow profit over time
  • May mean sacrificing profit now for future profit
  • Measure profit over time
  • Static measure not adequate
  • Present Value summing annual projected cash
    flows and appropriately discounted for time

6
Risk
  • CANNOT IGNORE RISK
  • Risk attitudes
  • Risk Averse
  • Risk Neutral (normal profit MAX)
  • Risk Preferring

7
Risk Aversion
  • Risk aversion does not mean you will not take
    risks
  • Does mean that you must be compensated for taking
    risks and the required compensation must increase
    as the risk increases
  • Risk aversion levels influenced by wealth,
    experience,etc.

8
Risk Premium
  • Risk Premium increase in required returns to be
    indifferent between a investments with different
    risk levels
  • Ex U.S. government bond (low risk) and beef cow
    enterprise

9
Risk Dominance
  • Trade-off between risk and expected profit
  • Plot investments risk with risk on horizontal
    axis, profit on vertical axis

10
Risk Dominance
J
H
Profit
G
D
F
E
A
B
I
C
Risk
11
Risk Profit Curve
  • Investments with higher expected profits also
    have higher risk
  • Increase in risk is faster than increase in
    profits
  • Investment with MAX expected profit is at the top
    if the dominating set (investment J)
  • Profit MAX investments is most risky of the
    dominating investments
  • The dominating set becomes large with many
    investments Risk profit curve
  • Optimal investment cannot be determined without
    knowing risk-return preferences (level of risk
    aversion)

12
Risk Measures
  • Risk is due to unanticipated changes
    (variability)
  • Ex Investor considering beef cow and hog
    investment
  • 1st forecast rates of return and probabilities
    of returns under several states of nature
    optimistic, most likely, and pessimistic

13
Probability Distribution for two Investments
Beef Cattle Hogs ____ Forecast Profit
Rate Probability Profit Rate Profitability_ Opt
imistic 0.15 0.30 0.21 0.10 Most
Likely 0.12 0.40 0.15
0.60 Pessimistic 0.09 0.30 0.08 0.30
14
Calculate statistical measures
  • Expected Value (EV)
  • Standard Deviation (s)
  • Coefficient of Variation (CV)

15
Expected Value
  • Expected Value mean weighted average of the
    profit rates for the projected outcomes with the
    probabilities used as weights
  • E(V) SiPiVi
  • Where EV is expected value
  • S is the summation sign
  • Pi is the probability of forecast I
  • Vi is the profit projected for each forecast

16
Expected Value
  • E(V) beef cattle
  • (0.30)(0.15) (0.40)(0.12) (0.30)(0.09)
  • 0.12 or 12
  • E(V) hogs
  • (0.10)(0.21) (0.60)(0.15) (0.30)(0.08)
  • 0.135 or 13.5
  • E(V) hogs is larger, meaning the expected
    profitability is higher for the hog investment

17
Standard Deviation
  • Standard Deviation statistical measure of the
    amount of dispersion or variation of the
    projected outcomes about the expected value
  • Measure of risk (variability)
  • s Si (Pi)( Vi V)2
  • 1st find the difference between the E(V) and the
    projected outcome
  • 2nd square the difference
  • 3rd multiply each squared difference by its
    probability
  • 4th add up these products
  • 5th take square root

18
Standard Deviation
  • Beef cattle
  • s ((.30)(0.15-0.12)2 (0.40)(0.12-0.12) 2
    (0.30)(0.09-0.12) 2)½
  • 0.023 or 2.3
  • Hogs
  • s ((.10)(0.21-0.135)2 (0.60)(0.15-0.135) 2
    (0.30)(0.08-0.135) 2)½
  • 0.04 or 4.0

19
Standard Deviation
  • Hogs have the higher standard deviation, thus the
    larger risk
  • Hogs are more profitable and more risky
  • HOW DO WE COMPARE THE INVESTMENTS THEN?
  • COEFFICIENT OF VARIATION

20
Coefficient of Variation
  • Coefficient of Variation (CV) provides a
    relative measure of the amount of risk to the
    amount of expected return
  • CV s / E(V)
  • CV beef cattle 2.3 / 12 0.192
  • CV hogs 4.0 / 13.5 0.296
  • CV of hogs is larger, thus it is a more risky
    venture relative to the expected returns
  • The investor will make their decision based on
    risk preferences

21
Estimating Probabilities
  • Subjective probabilities are used when data is
    not available
  • Ex odds on athletic event
  • Objective probabilities are used when data is
    available
  • Ex to forecast your grade in here, you could
    look at grades from similar classes you took from
    same professor, your major, background, interest
    in the course, study habits

22
Liquidity
  • Liquidity refers to the ability to generate cash
    in order to meet cash demands as they occur and
    to provide for both anticipated and unanticipated
    events
  • Occurrence of risk is one need for liquidity
  • Liquidity can be generated by holding highly
    liquid, salable assets, or having the capacity to
    borrow funds quickly

23
Life Cycle of the Firm
  • Introduction
  • Wealth and liquidity low risk high family
    assistance important lease assets
  • Growth
  • Fully utilize management gain economic security
    competitive in industry
  • Consolidation
  • Stronger financial position continued growth
  • Transfer
  • Let other assume control of decisions attention
    to stable retirement funds management
    continuity production efficiency transferring
    funds to heirs cost efficiently

24
Statistical Relationship for Normal Variables
Statistical Relationship for Normal Variables
E(V)
25
Statistical Relationship for Normal Variables
68
95
E(V)
E(V)-2s
E(V)-s
E(V)s
E(V)2s
26
Example
  • State of Nature Profit Probability E(V)
  • Optimistic 400 .2 80
  • Most Likely 100 .6 60
  • Pessimistic -400 .2 -80
  • 60
  • s (.2(400-60)2 .6(100-60)2 .2(-400-60)2 )½
  • 258

27
Example
  • 68 chance profit
  • 60258318
  • 60-258-198
  • 95 chance profit
  • 602(258)576
  • 60-2(258)-456
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