Case Study
Beta Management Company
Raman	
  Dhiman	
  
INDIAN	
  INSTITUTE	
  OF	
  MANAGEMENT	
  (IIM),	
  SHILLONG	
  
F...
Company Background
• 
• 

Beta Management Company was founded in 1988
Ms. Wolfe considered herself a market strategist, an...
Analysis & Way forward

Month	
  

Vanguard	
  	
  
California	
  REIT	
  
Index	
  500	
  Trust	
  

Brown	
  
Group	
  
...
Results of Regression – California & Vanguard
SUMMARY	
  OUTPUT	
  
Regression	
  Sta-s-cs	
  
MulZple	
  R	
  

0.0735316...
Results of Regression – Brown & Vanguard
SUMMARY	
  OUTPUT	
  
Regression	
  Sta-s-cs	
  
MulZple	
  R	
  
0.656169766	
  ...
Weighted Average Portfolio Risks
Weighted	
  Average	
  Risk	
  in	
  a	
  porKolio	
  of	
  Vanguard	
  &	
  California	
...
Rate of returns from Capital Asset Pricing Model

R=rf +β(rm -rf )
Rf – Taken a 6% (RBI Rate of Return). Value may be take...
Thank You …
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Beta management company solution HBS Case Study

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Financial Markets - Investments, Solution for Beta Management Company Solutions. May not be 100 % accurate, but identifies an important point in case study.

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  1. 1. Case Study Beta Management Company Raman  Dhiman   INDIAN  INSTITUTE  OF  MANAGEMENT  (IIM),  SHILLONG   For  any  queries  pl  contact:  raman.pgpex12@iimshillong.in  
  2. 2. Company Background •  •  Beta Management Company was founded in 1988 Ms. Wolfe considered herself a market strategist, and Beta Management's stated goals were to enhance returns but reduce risks for clients via market timing . She would keep a majority of Beta's funds in no-load, low-expense index funds (with the remainder in money market instruments), adjusting the level of market exposure between 50% and 99% of Beta's funds in an attempt to "time the market." •  Issue •  •  •  •  Mrs. Wolfe also decided to increase the proportion of Beta's assets in equities, since she felt the market was still a good value and that 1991 would be a good year. As a first step toward both of these goals, Ms. Wolfe was considering immediately increasing her equity exposure to 80% with the purchase of one of two stocks recommended by her newly hired analyst Both were small NYSE-listed companies whose stock price had eroded over the past two years to levels that seemed unreasonably low She noticed that these stocks both seemed to bounce around in price much more than the market (or the index fund), and she wondered if she was doing the right thing exposing her clients to these new risks
  3. 3. Analysis & Way forward Month   Vanguard     California  REIT   Index  500  Trust   Brown   Group   1989  -­‐  January   February   March   April   May   June   July   August   September   October   November   December   1090  -­‐  January   February   March   April   May   June   July   August   September   October   November   December   7.32 -2.47 2.26 5.18 4.04 -0.59 9.01 1.86 -0.4 -2.34 2.04 2.38 -6.72 1.27 2.61 -2.5 9.69 -0.69 -0.32 -9.03 -4.89 -0.41 6.44 2.72 -28.26 -3.03 8.75 -1.47 -1.49 -9.09 10.67 -9.38 10.34 -14.38 -14.81 -4.35 -5.45 5 9.52 -0.87 0 4.55 3.48 0 -13.04 0 1.5 -2.56 9.16 0.73 -0.29 2.21 -1.08 -0.65 2.22 0 1.88 -7.55 -12.84 -1.7 -15.21 7.61 1.11 -0.51 12.71 3.32 3.17 -14.72 -1.91 -12.5 17.26 -8.53 Average   1.1025   -­‐2.265416667   -­‐0.67125   Covariance & Beta Value Covariance  of   Beta  Value  for  California  Rate  of   California  REIT   2.996288542   Interest  w.r.t.  Vanguard  rate  of   0.14121179   w.r.t.  Vanguard   interest   Covariance  of   Beta  Value  for  Brown  Rate  of   Brown  Group  w.r.t.   23.65590313   Interest  w.r.t.  Vanguard  rate  of   1.114876744   Vanguard   interest   Standard Deviation & Beta Value Stock   Std  DeviaZon   Beta  Value   Vanguard   4.6     California   9.2   0.14121179   Brown     8.1   1.114876744   First cut analysis: •  Risk value of California stock & Brown stock is twice that of Vanguard. •  From the Beta Value, the Brown share is more riskier than California. ** Pl refer further analysis
  4. 4. Results of Regression – California & Vanguard SUMMARY  OUTPUT   Regression  Sta-s-cs   MulZple  R   0.07353166   R  Square   Adjusted  R   Square   Standard   Error   ObservaZon s   0.005406905   ANOVA     Regression   Residual   Total     Intercept   X  Variable  1   -­‐0.039801872   9.412643861   24   df   1   22   23   Coefficients   SS   MS   F   Significance  F   10.59617781   10.59617781   0.119598569   0.732755502   1949.153018   88.59786446   1959.749196               Standard  Error   t  Stat   P-­‐value   Lower  95%   Upper  95%   Lower  95.0%   Upper  95.0%   -­‐2.427871621   1.977939832   -­‐1.227474962   0.232616969   -­‐6.529867769   1.674124527   -­‐6.529867769   1.674124527   0.147351433   0.426080217   0.345830261   0.732755502   -­‐0.736284855   1.03098772   -­‐0.736284855   1.03098772   Take away: Since the value of “Significance F” is more than 0.05, so it means that the Probability that an equation used will not explain the similar relationship between the subject stocks is 27%. Therefore, we do not have a meaningful correlation Moreover the “P Value” is also more than 0.05, means that the variable X i.e. Vanguard do not really influences Brown.
  5. 5. Results of Regression – Brown & Vanguard SUMMARY  OUTPUT   Regression  Sta-s-cs   MulZple  R   0.656169766   R  Square   0.430558762   Adjusted  R  Square   0.40467507   Standard  Error   6.301260285   ObservaZons   24   ANOVA     Regression   Residual   Total     Intercept   X  Variable  1   df   SS   MS   F   Significance  F   1   660.4820765   660.4820765   16.6343639   0.000498022   22   873.529386   39.70588118   23   1534.011463               Coefficients   Standard  Error   t  Stat   P-­‐value   Lower  95%   Upper  95%   Lower  95.0%   Upper  95.0%   -­‐1.953842984   1.324124645   -­‐1.475573309   0.154228174   -­‐4.699909424   0.792223455  -­‐4.699909424   0.792223455   1.163349646   0.285237856   4.078524721   0.000498022   0.571802539   1.754896753   0.571802539   1.754896753   In this case the value of “significance F” is less than 0.05, So the correlation is meaningful. Moreover the “P Value” is also less than 0.05, means that the variable X i.e. Vanguard really influences Brown.
  6. 6. Weighted Average Portfolio Risks Weighted  Average  Risk  in  a  porKolio  of  Vanguard  &  California  (PorKolio  1)   Parameter   Weight   Std  Dev(Risk)   Average   Vabguard  Fund   0.98989899   4.606343688   4.559814964   California   0.01010101   9.230735982   0.093239757     Average  Risk  %   4.653054721   Weighted  Average  Risk  in  a  porKolio  of  Vanguard  &  Brown  (PorKolio  2)   Parameter   Weight   Std  Dev(Risk)   Average   Vabguard  Fund   0.98989899   4.606343688   4.559814964   California   0.01010101   8.166771121   0.082492638     Average  Risk  %   4.642307602   Take Away: From Weighted average calculations, Portfolio 1 is more risky than Portfolio 2 Note: We can not find here the risk through 2X2 matrix, as from regression analysis, the value of “Significance F” and “P Value” are more than 0.05. So the correlation between California & Vanguard fund is irrelevant. Weighted Average Portfolio Returns Weighted  Average  Returns  in  a  porKolio  of  Vanguard  &  California  (PorKolio1)   Parameter   Weight   Return   Average   Vabguard  Fund   0.98989899   1.1025   1.091363636   California   0.01010101   -­‐2.265416667   -­‐0.022882997     Average  Returns  %   1.06848064   Weighted  Average  Returns  in  a  porKolio  of  Vanguard  &  Brown  (PorKolio  2)   Parameter   Weight   Return   Average   Vabguard  Fund   0.98989899   1.1025   1.091363636   California   0.01010101   -­‐0.67125   -­‐0.006780303     Average  Returns  %   1.084583333   Take Away: From Weighted average calculations, Portfolio 2 is giving more returns than Portfolio 1
  7. 7. Rate of returns from Capital Asset Pricing Model R=rf +β(rm -rf ) Rf – Taken a 6% (RBI Rate of Return). Value may be taken as required. Poreolio   Poreolio  1   Poreolio  2   Rf   6   6   Beta  Value   0.14121179   1.114876744   Poreolio  Return   R  (Return  from  CAPM  method)   1.06848064   6.696388674   1.084583333   11.48008373   Take away: Portfolio 2 will provide us more return than Portfolio 1
  8. 8. Thank You …
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