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Chapter 9 RISK AND RETURN    Centre for Financial Management , Bangalore
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RISK AND RETURN OF A SINGLE ASSET Rate of Return Rate of Return = Annual income  +  Ending price-Beginning price Beginning price  Beginning price  Current yield  Capital gains yield    Probability Distributions   Rate of Return (%)   State of the Probability of Bharat Foods Oriental Shipping Economy Occurrence Boom   0.30   25   50 Normal   0.50   20   20 Recession   0.20   15   -10    Centre for Financial Management , Bangalore
RISK AND RETURN OF A SINGLE ASSET Expected Rate of Return  n   E ( R ) =     p i   R i i =1 E ( R b ) = (0.3)(25%) +(0.50)(20%) + (0.20) (15%)= 20.5% Standard Deviation of Return   2  =     p i ( R i  -  E ( R )) 2    =      2 State of the Bharat Foods Stock        Economy   p i   R i   p i R i   R i - E ( R )  ( R i - E ( R ))2  p i (R i - E ( R ))2     1. Boom 0.30  25  7.5   4.5   20.25 6.075 2. Normal 0.50  20   10.0   -0.5   0.25 0.125 3. Recession 0.20 0.20  15  3.0   -5.5   30.25 6.050      p i R i  = 20.5  p i ( R i  –  E  ( R ))2 = 12.25     σ  =  [    p i  ( R i  -  E  ( R ))2]1/2  =  (12.25)1/2   =  3.5%    Centre for Financial Management , Bangalore
EXPECTED RETURN ON A PORTFOLIO E ( R p ) =     w i  E ( R i ) = 0.1 x 10 + 0.2 x 12 + 0.3 x 15 + 0.2 x 18 + 0.2 x 20  =  15.5 percent     Centre for Financial Management , Bangalore
DIVERSIFICATION AND PORTFOLIO RISK   Probability Distribution of Returns   State of the Probability Return on Return on   Return on  Econcmy Stock A Stock B Portfolio     1   0.20   15%   -5%   5% 2   0.20   -5%   15   5% 3   0.20   5   25   15% 4   0.20   35   5   20% 5   0.20   25   35   30%   Expected Return   Stock A :  0.2(15%) + 0.2(-5%) + 0.2(5%) +0.2(35%) + 0.2(25%)  = 15% Stock B :  0.2(-5%) + 0.2(15%) + 0.2(25%) + 0.2(5%) + 0.2(35%) = 15% Portfolio of A and B :  0.2(5%) + 0.2(5%) + 0.2(15%) + 0.2(20%) + 0.2(30%)  = 15%      Standard Deviation     Stock A  :  σ 2 A   = 0.2(15-15) 2  + 0.2(-5-15) 2  + 0.2(5-15) 2  + 0.2(35-15) 2  + 0.20 (25-15) 2   = 200 σ A   = (200) 1/2  = 14.14% Stock B  : σ 2 B   =  0.2(-5-15) 2  + 0.2(15-15) 2  + 0.2(25-15) 2  + 0.2(5-15) 2  + 0.2 (35-15) 2   =  200 σ B   =  (200) 1/2  = 14.14% Portfolio  : σ 2 ( A + B )  =  0.2(5-15) 2  + 0.2(5-15) 2  + 0.2(15-15) 2  + 0.2(20-15) 2   + 0.2(30-15) 2     = 90   σ A + B   = (90) 1/2  = 9.49%    Centre for Financial Management , Bangalore
RELATIONSHIP BETWEEN  DIVERSIFICATION AND RISK    Centre for Financial Management , Bangalore
MARKET RISK VS UNIQUE RISK   Total Risk = Unique risk + Market risk Unique risk  of a security represents that portion of its total risk which stems from company-specific factors. Market risk  of security represents that portion of its risk which is attributable to economy –wide factors.    Centre for Financial Management , Bangalore
PORTFOLIO RISK : 2-SECURITY CASE  p  = [ w 1 2    1 2  + w 2 2    2 2 +2 w 1 w 2    12    1    2 ] 1/2 Example w 1  = 0.6,  w 2 = 0.4,   1 = 0.10   2 = 0.16,   12 = 0.5  p  = [0.6 2  x 0.10 2  + 0.4 2 x 0.16 2  + 2x 0.6x 0.4x 0.5x 0.10 x 0.16] 1/2 = 10.7 percent     Centre for Financial Management , Bangalore
RISK OF AN N - ASSET PORTFOLIO    2 p   =        w i  w j    ij    i   j   n  x  n  MATRIX    Centre for Financial Management , Bangalore
CORRELATION   Covariance (x, y) Coefficient of correlation (x,y) =   Standard    Standard    deviation of x  deviation  of y    xy    xy   =    x  .   y   • • • • • • • • • x y Positive correlation • • • • • • x y x y Perfect positive correlation x y Zero correlation • • • • • • • • Negative correlation x y Perfect negative correlation • • • • • • • X    Centre for Financial Management , Bangalore
MEASUREMENT OF MARKET RISK THE SENSITIVITY OF  A SECURITY TO MARKET MOVEMENTS IS CALLED BETA .  BETA REFLECTS THE SLOPE OF A THE LINEAR REGRESSION RELATIONSHIP BETWEEN THE RETURN ON THE SECURITY AND THE RETURN ON THE PORTFOLIO Relationship between Security Return and Market Return    Security  Return          Market   return    Centre for Financial Management , Bangalore
CALCULATION OF BETA For calculating the beta of a security, the following market model is employed: R jt   =   j  +   j R     e j where R jt = return of security  j  in period  t  j = intercept term alpha  j = regression coefficient, beta R  = return on market portfolio in period  t e j = random error term  Beta reflects the slope of the above regression relationship. It is equal to: Cov ( R j  ,  R M ) ρ jM   ρ j   σ M   ρ j M   σ j  j   =    =   =   σ 2 M   σ 2 M   σ M where Cov = covariance between the return on security  j  and the return on  market portfolio  M . It is equal to:   n   _  _   R jt  –  R j )( R Mt  –  R M )/( n -1)   i =1    Centre for Financial Management , Bangalore
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CHARACTERISTIC LINE FOR SECURITY  j •   •   •   • 5  10  15  20  25  30 –  10  – 5  –  10  –  5  5 10 15 20 25 30 R j R M •   •   •   • • •    Centre for Financial Management , Bangalore
RECAPITULATION OF THE STORY SO FAR •  Securities are risky because their returns are variable. •  The most commonly used measure of risk or variability in  finance is standard deviation. •   The risk of a security can be split into two parts: unique risk  and market risk. •   Unique risk stems from firm-specific factors, whereas market  risk emanates from economy-wide factors. •   Portfolio diversification washes away unique risk, but not  market risk. Hence, the risk of a fully diversified portfolio is its  market risk. •   The contribution of a security to the risk of a fully diversified  portfolio is measured by its beta, which reflects its sensitivity to  the general market movements.    Centre for Financial Management , Bangalore
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SECURITY MARKET LINE EXPECTED   •  P  RETURN  SML   14% 8%   •  0   ALPHA = EXPECTED  - FAIR   RETURN  RETURN   1.0   β i
Rate of Return C  Risk premium for an aggressive  17.5  B  security  15.0  A 12.5  Risk premium for a neutral security  R f  = 10  Risk premium for a defensive security  0.5  1.0  1.5  2.0  Beta BETA (MARKET RISK) & EXPECTED RATE OF RETURN    Centre for Financial Management , Bangalore
Increase in anticipated inflation Inflation premium Real required rate of return Rate of  return Risk (Beta) SML2 SML1 SECURITY MARKET LINE CAUSED BY AN INCREASE IN INFLATION    Centre for Financial Management , Bangalore
SECURITY MARKET LINE CAUSED BY A DECREASE IN RISK AVERSION Rate of  return Risk (Beta) New market risk premium SML1 SML2 Original market risk premium    Centre for Financial Management , Bangalore
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EMPIRICAL EVIDENCE ON CAPM 1. SET UP THE SAMPLE DATA   R it  ,  R Mt  ,  R ft 2. ESTIMATE THE SECURITY CHARACTER-    -ISTIC LINES   R it  -   R ft  =  a i  +   b i  (R Mt  -   R ft ) + e it 3. ESTIMATE THE SECURITY MARKET LINE   R i  =   0  +   1   b i  + e i ,  i  = 1, … 75    Centre for Financial Management , Bangalore
EVIDENCE IF CAPM HOLDS •   THE RELATION … LINEAR .. TERMS LIKE  b i 2  .. NO    EXPLANATORY POWER   •      0  ≃   R f •      1  ≃   R M  -   R f •   NO OTHER FACTORS, SUCH AS COMPANY SIZE    OR TOTAL VARIANCE, SHOULD AFFECT  R i •   THE MODEL SHOULD EXPLAIN A SIGNIFICANT    PORTION OF VARIATION IN RETURNS AMONG    SECURITIES    Centre for Financial Management , Bangalore
  GENERAL FINDINGS • THE RELATION … APPEARS .. LINEAR •      0  >   R f •      1  <   R M  -   R f •  IN ADDITION TO BETA, SOME OTHER FACTORS,    SUCH AS STANDARD DEVIATION OF RETURNS    AND COMPANY SIZE, TOO HAVE A BEARING ON    RETURN •  BETA DOES NOT EXPLAIN A VERY HIGH    PERCENTAGE OF THE VARIANCE IN RETURN    Centre for Financial Management , Bangalore
CONCLUSIONS PROBLEMS •  STUDIES USE HISTORICAL RETURNS AS PROXIES    FOR EXPECTATIONS • STUDIES USE A MARKET INDEX AS A PROXY POPULARITY •  SOME OBJECTIVE ESTIMATE OF RISK PREMIUM    .. BETTER THAN A COMPLETELY SUBJECTIVE    ESTIMATE • BASIC MESSAGE .. ACCEPTED BY ALL • NO CONSENSUS ON ALTERNATIVE    Centre for Financial Management , Bangalore
ARBITRAGE - PRICING THEORY RETURN GENERATING PROCESS R i  =  a i  +   b i  1   I 1   + b i 2  I 2   …+   b ij  I 1  +  e i EQUILIBRIUM RISK - RETURN  RELATIONSHIP E ( R i )  =   0   +  b i 1   1   +  b i 2   2   +  …  b ij    j    j   =  RISK PREMIUM FOR THE TYPE OF  RISK ASSOCIATED WITH FACTOR  j    Centre for Financial Management , Bangalore
SUMMING UP •  Variance (a measure of dispersion) or its square root, the standard  deviation, is commonly used to reflect risk •   The variance is defined as the average squared deviation of each  possible return from its expected value. •   Diversification reduces risk, but at a diminishing  rate •   According to the modern portfolio theory: •   The unique risk of a security represents that portion of its total  risk which stems from firm-specific factors. •   The market risk of a security represents that portion of its risk  which is attributable to economy wide factors. •   The variance of the return of a two-security portfolio is:  p 2  =  w 1 2  1 2  +  w 2 2  2 2  + 2 w 1 w 2  12  1  2    Centre for Financial Management , Bangalore
•   Portfolio diversification washes away unique risk, but not market  risk.  Hence the risk of a fully diversified portfolio is its market  risk. •   The contribution of a security to the risk of a fully diversified  portfolio is measured by its beta, which reflects its sensitivity to the  general market movements. •   According to the capital asset pricing model, risk and return are  related as follows: Expected rate  =  Risk-free rate    Expected return on  Risk-free     market portfolio   –  rate •   In a well-ordered market, investors are compensated primarily for  bearing market risk, but not unique risk.  To earn a higher  expected rate of return, one has to bear a higher degree of market  risk. + Beta of the security    Centre for Financial Management , Bangalore

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Chapter 9 risk & return

  • 1. Chapter 9 RISK AND RETURN  Centre for Financial Management , Bangalore
  • 2.
  • 3. RISK AND RETURN OF A SINGLE ASSET Rate of Return Rate of Return = Annual income + Ending price-Beginning price Beginning price Beginning price Current yield Capital gains yield Probability Distributions Rate of Return (%)   State of the Probability of Bharat Foods Oriental Shipping Economy Occurrence Boom 0.30 25 50 Normal 0.50 20 20 Recession 0.20 15 -10  Centre for Financial Management , Bangalore
  • 4. RISK AND RETURN OF A SINGLE ASSET Expected Rate of Return n E ( R ) =  p i R i i =1 E ( R b ) = (0.3)(25%) +(0.50)(20%) + (0.20) (15%)= 20.5% Standard Deviation of Return  2 =  p i ( R i - E ( R )) 2  =   2 State of the Bharat Foods Stock Economy p i R i p i R i R i - E ( R ) ( R i - E ( R ))2 p i (R i - E ( R ))2   1. Boom 0.30 25 7.5 4.5 20.25 6.075 2. Normal 0.50 20 10.0 -0.5 0.25 0.125 3. Recession 0.20 0.20 15 3.0 -5.5 30.25 6.050  p i R i = 20.5  p i ( R i – E ( R ))2 = 12.25 σ = [  p i ( R i - E ( R ))2]1/2 = (12.25)1/2 = 3.5%  Centre for Financial Management , Bangalore
  • 5. EXPECTED RETURN ON A PORTFOLIO E ( R p ) =  w i E ( R i ) = 0.1 x 10 + 0.2 x 12 + 0.3 x 15 + 0.2 x 18 + 0.2 x 20 = 15.5 percent  Centre for Financial Management , Bangalore
  • 6. DIVERSIFICATION AND PORTFOLIO RISK Probability Distribution of Returns   State of the Probability Return on Return on Return on Econcmy Stock A Stock B Portfolio   1 0.20 15% -5% 5% 2 0.20 -5% 15 5% 3 0.20 5 25 15% 4 0.20 35 5 20% 5 0.20 25 35 30% Expected Return   Stock A : 0.2(15%) + 0.2(-5%) + 0.2(5%) +0.2(35%) + 0.2(25%) = 15% Stock B : 0.2(-5%) + 0.2(15%) + 0.2(25%) + 0.2(5%) + 0.2(35%) = 15% Portfolio of A and B : 0.2(5%) + 0.2(5%) + 0.2(15%) + 0.2(20%) + 0.2(30%) = 15%   Standard Deviation   Stock A : σ 2 A = 0.2(15-15) 2 + 0.2(-5-15) 2 + 0.2(5-15) 2 + 0.2(35-15) 2 + 0.20 (25-15) 2 = 200 σ A = (200) 1/2 = 14.14% Stock B : σ 2 B = 0.2(-5-15) 2 + 0.2(15-15) 2 + 0.2(25-15) 2 + 0.2(5-15) 2 + 0.2 (35-15) 2 = 200 σ B = (200) 1/2 = 14.14% Portfolio : σ 2 ( A + B ) = 0.2(5-15) 2 + 0.2(5-15) 2 + 0.2(15-15) 2 + 0.2(20-15) 2 + 0.2(30-15) 2 = 90 σ A + B = (90) 1/2 = 9.49%  Centre for Financial Management , Bangalore
  • 7. RELATIONSHIP BETWEEN DIVERSIFICATION AND RISK  Centre for Financial Management , Bangalore
  • 8. MARKET RISK VS UNIQUE RISK Total Risk = Unique risk + Market risk Unique risk of a security represents that portion of its total risk which stems from company-specific factors. Market risk of security represents that portion of its risk which is attributable to economy –wide factors.  Centre for Financial Management , Bangalore
  • 9. PORTFOLIO RISK : 2-SECURITY CASE  p = [ w 1 2  1 2 + w 2 2  2 2 +2 w 1 w 2  12  1  2 ] 1/2 Example w 1 = 0.6, w 2 = 0.4,  1 = 0.10  2 = 0.16,  12 = 0.5  p = [0.6 2 x 0.10 2 + 0.4 2 x 0.16 2 + 2x 0.6x 0.4x 0.5x 0.10 x 0.16] 1/2 = 10.7 percent  Centre for Financial Management , Bangalore
  • 10. RISK OF AN N - ASSET PORTFOLIO  2 p =   w i w j  ij  i  j n x n MATRIX  Centre for Financial Management , Bangalore
  • 11. CORRELATION Covariance (x, y) Coefficient of correlation (x,y) = Standard Standard deviation of x deviation of y  xy  xy =  x .  y • • • • • • • • • x y Positive correlation • • • • • • x y x y Perfect positive correlation x y Zero correlation • • • • • • • • Negative correlation x y Perfect negative correlation • • • • • • • X  Centre for Financial Management , Bangalore
  • 12. MEASUREMENT OF MARKET RISK THE SENSITIVITY OF A SECURITY TO MARKET MOVEMENTS IS CALLED BETA . BETA REFLECTS THE SLOPE OF A THE LINEAR REGRESSION RELATIONSHIP BETWEEN THE RETURN ON THE SECURITY AND THE RETURN ON THE PORTFOLIO Relationship between Security Return and Market Return   Security Return          Market return  Centre for Financial Management , Bangalore
  • 13. CALCULATION OF BETA For calculating the beta of a security, the following market model is employed: R jt =  j +  j R   e j where R jt = return of security j in period t  j = intercept term alpha  j = regression coefficient, beta R  = return on market portfolio in period t e j = random error term Beta reflects the slope of the above regression relationship. It is equal to: Cov ( R j , R M ) ρ jM ρ j σ M ρ j M σ j  j = = = σ 2 M σ 2 M σ M where Cov = covariance between the return on security j and the return on market portfolio M . It is equal to: n _ _  R jt – R j )( R Mt – R M )/( n -1) i =1  Centre for Financial Management , Bangalore
  • 14.
  • 15. CHARACTERISTIC LINE FOR SECURITY j • • • • 5 10 15 20 25 30 – 10 – 5 – 10 – 5 5 10 15 20 25 30 R j R M • • • • • •  Centre for Financial Management , Bangalore
  • 16. RECAPITULATION OF THE STORY SO FAR • Securities are risky because their returns are variable. • The most commonly used measure of risk or variability in finance is standard deviation. • The risk of a security can be split into two parts: unique risk and market risk. • Unique risk stems from firm-specific factors, whereas market risk emanates from economy-wide factors. • Portfolio diversification washes away unique risk, but not market risk. Hence, the risk of a fully diversified portfolio is its market risk. • The contribution of a security to the risk of a fully diversified portfolio is measured by its beta, which reflects its sensitivity to the general market movements.  Centre for Financial Management , Bangalore
  • 17.
  • 18. SECURITY MARKET LINE EXPECTED • P RETURN SML 14% 8% • 0 ALPHA = EXPECTED - FAIR RETURN RETURN 1.0 β i
  • 19. Rate of Return C Risk premium for an aggressive 17.5 B security 15.0 A 12.5 Risk premium for a neutral security R f = 10 Risk premium for a defensive security 0.5 1.0 1.5 2.0 Beta BETA (MARKET RISK) & EXPECTED RATE OF RETURN  Centre for Financial Management , Bangalore
  • 20. Increase in anticipated inflation Inflation premium Real required rate of return Rate of return Risk (Beta) SML2 SML1 SECURITY MARKET LINE CAUSED BY AN INCREASE IN INFLATION  Centre for Financial Management , Bangalore
  • 21. SECURITY MARKET LINE CAUSED BY A DECREASE IN RISK AVERSION Rate of return Risk (Beta) New market risk premium SML1 SML2 Original market risk premium  Centre for Financial Management , Bangalore
  • 22.
  • 23. EMPIRICAL EVIDENCE ON CAPM 1. SET UP THE SAMPLE DATA R it , R Mt , R ft 2. ESTIMATE THE SECURITY CHARACTER- -ISTIC LINES R it - R ft = a i + b i (R Mt - R ft ) + e it 3. ESTIMATE THE SECURITY MARKET LINE R i =  0 +  1 b i + e i , i = 1, … 75  Centre for Financial Management , Bangalore
  • 24. EVIDENCE IF CAPM HOLDS • THE RELATION … LINEAR .. TERMS LIKE b i 2 .. NO EXPLANATORY POWER •  0 ≃ R f •  1 ≃ R M - R f • NO OTHER FACTORS, SUCH AS COMPANY SIZE OR TOTAL VARIANCE, SHOULD AFFECT R i • THE MODEL SHOULD EXPLAIN A SIGNIFICANT PORTION OF VARIATION IN RETURNS AMONG SECURITIES  Centre for Financial Management , Bangalore
  • 25. GENERAL FINDINGS • THE RELATION … APPEARS .. LINEAR •  0 > R f •  1 < R M - R f • IN ADDITION TO BETA, SOME OTHER FACTORS, SUCH AS STANDARD DEVIATION OF RETURNS AND COMPANY SIZE, TOO HAVE A BEARING ON RETURN • BETA DOES NOT EXPLAIN A VERY HIGH PERCENTAGE OF THE VARIANCE IN RETURN  Centre for Financial Management , Bangalore
  • 26. CONCLUSIONS PROBLEMS • STUDIES USE HISTORICAL RETURNS AS PROXIES FOR EXPECTATIONS • STUDIES USE A MARKET INDEX AS A PROXY POPULARITY • SOME OBJECTIVE ESTIMATE OF RISK PREMIUM .. BETTER THAN A COMPLETELY SUBJECTIVE ESTIMATE • BASIC MESSAGE .. ACCEPTED BY ALL • NO CONSENSUS ON ALTERNATIVE  Centre for Financial Management , Bangalore
  • 27. ARBITRAGE - PRICING THEORY RETURN GENERATING PROCESS R i = a i + b i 1 I 1 + b i 2 I 2 …+ b ij I 1 + e i EQUILIBRIUM RISK - RETURN RELATIONSHIP E ( R i ) =  0 + b i 1  1 + b i 2  2 + … b ij  j  j = RISK PREMIUM FOR THE TYPE OF RISK ASSOCIATED WITH FACTOR j  Centre for Financial Management , Bangalore
  • 28. SUMMING UP • Variance (a measure of dispersion) or its square root, the standard deviation, is commonly used to reflect risk • The variance is defined as the average squared deviation of each possible return from its expected value. • Diversification reduces risk, but at a diminishing rate • According to the modern portfolio theory: • The unique risk of a security represents that portion of its total risk which stems from firm-specific factors. • The market risk of a security represents that portion of its risk which is attributable to economy wide factors. • The variance of the return of a two-security portfolio is:  p 2 = w 1 2  1 2 + w 2 2  2 2 + 2 w 1 w 2  12  1  2  Centre for Financial Management , Bangalore
  • 29. Portfolio diversification washes away unique risk, but not market risk. Hence the risk of a fully diversified portfolio is its market risk. • The contribution of a security to the risk of a fully diversified portfolio is measured by its beta, which reflects its sensitivity to the general market movements. • According to the capital asset pricing model, risk and return are related as follows: Expected rate = Risk-free rate Expected return on Risk-free market portfolio – rate • In a well-ordered market, investors are compensated primarily for bearing market risk, but not unique risk. To earn a higher expected rate of return, one has to bear a higher degree of market risk. + Beta of the security  Centre for Financial Management , Bangalore