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estion: Calculate the weighted average cost of capital (WACC) for PDI. E/V80.00% Cost of equity9.40% Risk-free rate 3.00% Beta 1.28 Market equity risk premium 5.00%

estion:

Calculate the weighted average cost of capital (WACC) for PDI.

E/V80.00%

Cost of equity9.40%

Risk-free rate 3.00%

Beta 1.28

Market equity risk premium 5.00%

D/V20.00%

Cost of debt4.00%

Corporate tax rate40.00%

WACC 80% x 9.40%) + [20% x 4% x (1 - 40%)]= 8.00% WACC = (E/V x Re) + ((D/V x Rd) x (1 - T))

*Cost of equityRisk free rate of return + (Beta * Risk premium) = 3% + (1.28 x 5%) 0.094

Givend the above, I cannot get the following:

Sum of FCF PV =?

Terminal value =?

Present value of terminal value =?

Total value of PDI =?

Assumptions

Discount rate ?

Terminal value ?

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Which of the following is an advantage of multivariate correlational research over bivariate correlational research? O Bivariate correlational studies help address internal validity, whereas multivariate correlational studies do not. Multivariate correlational studies establish covariance, whereas bivariate correlational studies do not. O Some multivariate correlational studies help to address temporal precedence, whereas bivariate correlational studies do not. Multivariate correlational studies help to address external validity, whereas bivariate correlational studies do not.1. (a) Explain what is meant by the transition probability matrix of a homogeneous Markov chain. [5 marks] (b) Explain what is meant by the stationary distribution of a Markov chain? [5 marks] (c) A Markov chain has transition probability matrix, A, with entries Ouj; and stationary distribution . Write down an expression for the entries of the reverse Markov chain. [5 marks (d) Consider the following transition probability matrix of a homogo- neous Markov chain, with three states i,j and k (the TPM is in that order). If the stationary vector of the chain is (1/9, 2/9, 2/3), determine whether the Markov chain is reversible. 1 /0.2 0.2 0.6 0.1 0.6 0.3 4 \\0.1 0.1 0.8 [5 marks] (e) Let X1, X2, Xa be a sequence of random variables resulting from the above Markov chain. If X1 = i and Xs = j what is the probability that X2 = k? [5 marks]Consider a standard chessboard with an 8 x 8 grid of possible locations. We define a Markov chain by randomly moving a single chess piece on this board. The initial location Xo is sampled uniformly among the 82 = 64 squares. At time t, the piece then chooses Xt+1 by sampling uniformly from the set of legal moves given its current location Xt. For a description of legal chess moves, see: http://en. wikipedia. org/wiki/Rules_of_chess#Basic_moves. a) Suppose the chess piece is a king, which can move to any of the 8 adjacent squares. Is the Markov chain irreducible? Is the Markov chain aperiodic? b) Suppose the chess piece is a bishop. Is the Markov chain irreducible? Is the Markov chain aperiodic? c) Suppose the chess piece is a knight. Is the Markov chain irreducible? Is the Markov chain aperiodic

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