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stat 400 practice problems 8 stepanov uiuc dalpiaz solutions the following are a number of practice problems that may be helpful for completing the homework and will likely be very ...

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                STAT 400                        Practice Problems #8                                           Stepanov 
                UIUC                                                                                            Dalpiaz 
                                                        SOLUTIONS 
                                                                      
                The following are a number of practice problems that may be helpful for 
                completing the homework, and will likely be very useful for studying 
                for exams. 
                 
                1.      a)      Let  X  and  Y  be random variables with 
                                        E ( X ) = µ   = 20,     SD ( X ) = σ   = 7, 
                                                    X                         X
                                        E ( Y ) = µ   = 8,      SD ( Y ) = σ   = 2,     Corr ( X, Y ) = ρ = 0.60. 
                                                    Y                         Y
                                Find   E ( 3 X – 5 Y )  and  SD ( 3 X – 5 Y ). 
                 
                        E ( 3 X – 5 Y )  =  3 µ   – 5 µ    =  3 ⋅ 20 – 5 ⋅ 8  =  20. 
                                                X       Y
                 
                        Var ( 3 X – 5 Y )  =  Cov ( 3 X – 5 Y , 3 X – 5 Y ) 
                 
                                        =  Cov ( 3 X , 3 X ) – Cov ( 3 X , 5 Y ) – Cov ( 5 Y , 3 X ) + Cov ( 5 Y , 5 Y ) 
                 
                                        =  9 σ 2  – 30 σ       + 25 σ 2   =  9 σ 2  – 30 ρ σ   σ   + 25 σ 2  
                                                 X        XY           Y          X           X Y             Y
                                        =  9 ⋅ 7 2 – 30 ⋅ 0.6 ⋅ 7 ⋅ 2 + 25 ⋅ 2 2  =  289. 
                 
                        SD ( 3 X – 5 Y )  =      289   =  17. 
                 
                 
                        b)      Let  X  and  Y  be random variables with 
                                        SD ( X ) = σ   = 5,     SD ( Y ) = σ   = 7,     SD ( 3 X + 4 Y ) = 27. 
                                                      X                       Y
                                Find   Corr ( X, Y ) = ρ. 
                 
                        Var ( 3 X + 4 Y )  =  Cov ( 3 X + 4 Y , 3 X + 4 Y ) 
                 
                                        =  Cov ( 3 X , 3 X ) + Cov ( 3 X , 4 Y ) + Cov ( 4 Y , 3 X ) + Cov ( 4 Y , 4 Y ) 
                 
                                        =  9 σ 2  + 24 σ       + 16 σ 2   =  9 σ 2  + 24 ρ σ   σ   + 16 σ 2  
                                                                                                             Y
                                                 X        XY           Y          X           X Y             
                                        =  9 ⋅ 5 2 + 24 ⋅ ρ ⋅ 5 ⋅ 7 + 16 ⋅ 7 2  =  1009 + 840 ⋅ ρ  =  729  =  27 2. 
                 
                        ⇒       ρ  =  − 1 . 
                                         3
                 
                 
                2.      Suppose that you wish to invest in two stocks which both have a current price of $1. 
                        The values of these two stocks in one month are described by two random variables, 
                        say,  X 1  and  X 2 .  Suppose that the expected values and variances of  X 1  and  X 2 
                                          2          2
                        are  µ   ,  µ   ,  σ   ,  and  σ   ,  respectively.  We also assume that the correlation between 
                               1     2    1          2
                        the stocks is given by  ρ. 
                 
                        Let  c  denote your initial investment, which is to be invested in the stocks, and assume 
                        that shares can be bought up to any percentages.  Let  w  denote the percentage of your 
                        investment in stock 1.  Finally, let  P  denote the value of your portfolio (investment) 
                        after a month. Then we have that  P  =  c ( w X 1 + ( 1 – w ) X 2 ),  where  0 ≤ w ≤ 1. 
                 
                a)      Find an expression for the expected value of your investment after one month. 
                 
                                                                                                                         
                 
                b)      Find an expression for the variance of your investment after one month. 
                 
                                                                                                                         
                 
                c)      Find the weights that minimize the risk of your investment. 
                        ( Hint:   in the classical portfolio theory the risk is simply quantified by the variance. ) 
                 
                                                                                                                         
                 
                 
                                                                                                                               
                  
                  
                 d)       Find the correlation which minimizes the risk of the equally weighted portfolio 
                          ( i.e.,  w = 0.5 ). 
                  
                  
                                                                                                                               
                  
                  
                3.      In Anytown, the price of a gallon of milk ( X ) varies from day to day according to 
                        normal distribution with mean $3.00 and standard deviation $0.20.  The price of a 
                        package of Oreo cookies ( Y ) also varies from day to day according to normal 
                        distribution with mean $2.70 and standard deviation $0.15.  Assume the prices of 
                        a gallon of milk and a package of Oreo cookies are independent. 
                 
                a)      Find the probability that on a given day, the price of a package of Oreo cookies is  
                        higher than the price of a gallon of milk.  That is, find  P ( Y > X ). 
                 
                 
                 
                P ( Y > X )  =  P ( X – Y < 0 ). 
                 
                X – Y  has Normal distribution with mean   E ( X – Y )  =  3.00 – 2.70  =  $0.30 
                and variance   Var ( X – Y )  =  Var ( X ) + Var ( Y )  =  0.20 2 + 0.15 2  =  0.0625 
                ( standard deviation  =  $0.25 ). 
                 
                P ( X – Y < 0 )  =  PZ < 0−0.30  =  P ( Z < – 1.20 )  =  Φ ( – 1.20 )  =  0.1151. 
                                             0.25 
                                                    
                 
                 
                 
                 
                 
                b)      Alex is planning a Milk-and-Oreos party for his imaginary friends.  He buys 4 gallons 
                        of milk and 7 packages of Oreo cookies.  Find the probability that he paid less than $30. 
                        That is, find  P ( 4 X + 7 Y < 30 ). 
                 
                 
                 
                4 X + 7 Y  has Normal distribution with mean   E ( 4 X + 7 Y )  =  4 ⋅ 3.00 + 7 ⋅ 2.70  =  $30.90 
                                                                                                2            2
                and variance  Var ( 4 X + 7 Y )  =  16 ⋅ Var ( X ) + 49 ⋅ Var ( Y )  =  16 ⋅ 0.20   + 49 ⋅ 0.15    =  1.7425 
                ( standard deviation  ≈  $1.32 ). 
                 
                P ( 4 X + 7 Y < 30 )  =  PZ< 30 −30.90  =  P ( Z < – 0.68 )  =  Φ ( – 0.68 )  =  0.2483. 
                                                   1.32     
                                                            
                 
                 
                 
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