Use the function VanillaCall defined in the chapter to create a Data Table in which you can see the relation between the number of runs incorporated in the function and the Black-Scholes value of a call. Your result should look something like the following:

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В 1 MONTE CARLO PRICING OF PLAIN-VANILLA CALLS 2 S,, current stock price 3 |X, еxercisе price 4 r, interest rate 5 T, time 6 Ju, mean stock return 7J0, sigma--standard deviation of stock retum 50 44 10% 0.8 13% 30% 8 9 In, divisions of unit time 10 Runs 11 12 VanillaCall 13 150 <-- Try playing around with this 111 <- This is what's altered in the data table 13.0632 <-=vanillacall(B2,B3,B6,B7,B4,B5,B9,B10) 14 BS call 15 10.8948 <-- =BSCall(B2,B3,B5,B4,B7) 16 17 Data table: the effect of runs on the MC Vanilla call value Monte Carlo 13.0632 9.7749 11.3694 10.8217 10.9121 Black-Scholes 18 19 20 21 Runs 10.8948 11.5 100 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 6,500 10.8948 11.3 10.8948 10.8948 11.1 10.8948 10.9 22 23 24 25 26 10.9170 10.6694 10.8389 10.8948 10.7 10.8948 10.5 10.8948 10.3 27 28 29 10.8755 10.8451 11.1993 10.8948 10.1 10.8948 9.9 10.8948 9.7 10.8948 30 10.9505 10.8181 11.0687 10.7333 10.8948 10.8948 10.8948 9.5 31 1 2 3 4 5 6 8. 7 9. 10 11 12 13 14 32 33 Monte Carlo Black-Scholes 34