some statistical concept

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5-1 Some statistical concepts & Risk and Rates of Return Ref: Financial Management: Eugene F. Brigham, Louis C. Gapenski & Michael C. Ehrhardt. Modern Investment Theory- R. A Haugen

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Investment Chapter 3 Some statistical Concept Lecture Slide

TRANSCRIPT

Page 1: Some Statistical Concept

5-1

Some statistical concepts &Risk and Rates of Return

Ref:Financial Management: Eugene F. Brigham, Louis C.

Gapenski & Michael C. Ehrhardt.Modern Investment Theory- R. A Haugen

Page 2: Some Statistical Concept

5-2

Investment returnsThe rate of return on an investment can be calculated as follows:

(Amount received – Amount invested)

Return = ________________________

Amount invested

For example, if $1,000 is invested and $1,100 is returned after one year, the rate of return for this investment is:

($1,100 - $1,000) / $1,000 = 10%.

Page 3: Some Statistical Concept

5-3

What is investment risk? Two types of investment risk

Stand-alone risk Portfolio risk

Investment risk is related to the probability of earning a low or negative actual return.

The greater the chance of lower than expected or negative returns, the riskier the investment.

Page 4: Some Statistical Concept

5-4

Probability distributions A listing of all possible outcomes, and the

probability of each occurrence. Can be shown graphically.

Expected Rate of Return

Rate ofReturn (%)100150-70

Firm X

Firm Y

Page 5: Some Statistical Concept

5-5

Why is the T-bill return independent of the economy? Do T-bills promise a completely risk-free return?

T-bills will return the promised 8%, regardless of the economy.

No, T-bills do not provide a risk-free return, as they are still exposed to inflation. Although, very little unexpected inflation is likely to occur over such a short period of time.

T-bills are also risky in terms of reinvestment rate risk.

T-bills are risk-free in the default sense of the word.

Page 6: Some Statistical Concept

5-6

Return: Calculating the expected return for each alternative

17.4% (0.1) (50%) (0.2) (35%) (0.4) (20%)

(0.2) (-2%) (0.1) (-22.%) k

P k k

return of rate expected k

HT^

n

1iii

^

^

Page 7: Some Statistical Concept

5-7

Risk: Calculating the standard deviation for each alternative

deviation Standard

2Variance

i2

n

1ii P)k̂k(

Page 8: Some Statistical Concept

5-8

Standard deviation calculation

15.3% 18.8% 20.0% 13.4% 0.0%

(0.1)8.0) - (8.0 (0.2)8.0) - (8.0 (0.4)8.0) - (8.0

(0.2)8.0) - (8.0 (0.1)8.0) - (8.0

P )k (k

M

USRHT

CollbillsT

2

22

22

billsT

n

1ii

2^i

21

Page 9: Some Statistical Concept

5-9

Comparing standard deviations

USR

Prob.T - bill

HT

0 8 13.8 17.4 Rate of Return (%)

Page 10: Some Statistical Concept

5-10

Comments on standard deviation as a measure of risk Standard deviation (σi) measures total, or

stand-alone, risk. The larger σi is, the lower the probability

that actual returns will be closer to expected returns.

Larger σi is associated with a wider probability distribution of returns.

Difficult to compare standard deviations, because return has not been accounted for.

Page 11: Some Statistical Concept

5-11

Comparing risk and returnSecurity Expected

returnRisk, σ

T-bills 8.0% 0.0%HT 17.4% 20.0%Coll 1.7% 13.4%USR 13.8% 18.8%Market 15.0% 15.3%

Page 12: Some Statistical Concept

5-12

Coefficient of Variation (CV)A standardized measure of dispersion about the expected value, that shows the risk per unit of return.

^k

Meandev Std CV

Page 13: Some Statistical Concept

5-13

Risk rankings, by coefficient of variation

CVT-bill 0.000HT 1.149Coll. 7.882USR 1.362Market 1.020

Collections has the highest degree of risk per unit of return.

HT, despite having the highest standard deviation of returns, has a relatively average CV.

Page 14: Some Statistical Concept

5-14

Illustrating the CV as a measure of relative risk

σA = σB , but A is riskier because of a larger probability of losses. In other words, the same amount of risk (as measured by σ) for less returns.

0

A B

Rate of Return (%)

Prob.

Page 15: Some Statistical Concept

5-15

Covariance & CorrelationMonth Stock A Stock B

1 .04 .022 -.02 .033 .08 .064 -.04 -.045 .04 .08

Covariance tells us about the direction of relationship and it is unbounded.

Covariance between A & B is .0017

Page 16: Some Statistical Concept

5-16

Covariance & Correlation The correlation coefficient can be

thought as a standardized covariance. It ranges between +1 to -1

Page 17: Some Statistical Concept

5-1717

Correlation pattern 1

Perfect positive correlation

rB

rA

Perfect negative correlation

rB

rA.

Page 18: Some Statistical Concept

5-1818

Correlation pattern 2

Imperfect positive correlation

rB

rA

}

Zero correlation

rB

rA

Page 19: Some Statistical Concept

5-19

The relationship between a stock and the market portfolio The market portfolio contains

every single risky security in the international economic system and it contains each asset in proportion to the total market value of that asset relative to the total value of all other asset.

Page 20: Some Statistical Concept

5-20

Characteristic line, Beta and residual variance The relationship between return a stock

and the return of the market portfolio is described by stock’s characteristic line. Since it is a straight line it can be described by slope and intercept

The slope of that line is beta. Measures a stock’s market risk, and shows

a stock’s volatility relative to the market. Indicates how risky a stock is if the stock

is held in a well-diversified portfolio.

Page 21: Some Statistical Concept

5-21

Calculating betas Run a regression of past returns of

a security against past returns on the market.

The slope of the regression line (sometimes called the security’s characteristic line) is defined as the beta coefficient for the security.

Page 22: Some Statistical Concept

5-22

Illustrating the calculation of beta

.

.

.ki

_

kM

_-5 0 5 10 15 20

20

15

10

5

-5

-10

Regression line:ki = -2.59 + 1.44 kM^ ^

Year kM ki 1 15% 18% 2 -5 -10 3 12 16

Page 23: Some Statistical Concept

5-23

A stock’s residual variance gives us an indication of the propensity of a stock’s return to deviate from its characteristic line.

The stock which is perfectly correlated with the market has residual variance equal to zero.

Page 24: Some Statistical Concept

5-24

For formula follow

Modern Investment Theory- R. A Haugen