**Please Solve using Excel***

K = $28 o = 17% So = $28 r = 2% T = 1 year Answer: c = $2.168, p = $1.614 5) We will use a Monte Carlo simulation in this problem to estimate a Black-Scholes price as follows. Use the call option data in problem 1) a) Replace u with rin: In(Sy) = [In(So)+ (n - T, 027] to obtain: In(Sy) - + [In(50)+(r->)T, OPT] b) Let mean = In(So) +(rT sd = o * Sqrt(7) 1 c) Simulate In(St) 1000 times using = NORMINV(RANDO), mean, sd d) For each of the 1000 values of In(St), find St (use eln(x) = x) e) Calculate and average 1000 values of Maxco, ST - K) and discount the average using e-rt to obtain the call price Compare what you get to the Black-Scholes formula price. How accurate is the simulation? You can use the F9 key to obtain new simulation values. Does the call price change much? The more simulations you do, the more accurate the estimate. I was able to obtain errors of less than $0.01 using 1,000,000 simulations in a Python program. K = $28 o = 17% So = $28 r = 2% T = 1 year Answer: c = $2.168, p = $1.614 5) We will use a Monte Carlo simulation in this problem to estimate a Black-Scholes price as follows. Use the call option data in problem 1) a) Replace u with rin: In(Sy) = [In(So)+ (n - T, 027] to obtain: In(Sy) - + [In(50)+(r->)T, OPT] b) Let mean = In(So) +(rT sd = o * Sqrt(7) 1 c) Simulate In(St) 1000 times using = NORMINV(RANDO), mean, sd d) For each of the 1000 values of In(St), find St (use eln(x) = x) e) Calculate and average 1000 values of Maxco, ST - K) and discount the average using e-rt to obtain the call price Compare what you get to the Black-Scholes formula price. How accurate is the simulation? You can use the F9 key to obtain new simulation values. Does the call price change much? The more simulations you do, the more accurate the estimate. I was able to obtain errors of less than $0.01 using 1,000,000 simulations in a Python program