= 100, Consider the Black-Scholes model and its European call option pricing formula. Fix So K...

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= 100, Consider the Black-Scholes model and its European call option pricing formula. Fix So K = 100, T = 1, r = 3%, and o = 20%. (a) Using a built-in normal random number generator in Matlab, find an estimate of the call price C = E [e-T (ST - K)+] based on n = 100,000 samples. (Start your Matlab code with rng (1); if Python, random. seed (1).) Also report the standard error. (b) Draw a graph of Ĉn and 95% confidence interval, that is, (1) graph of Ĉn, (2) graph of upper limit of 95% CI, (3) graph of lower limit of 95% CI, all as functions of n in a single panel. Do this for n = [104, 106] by appropriately selecting values for n for a good quality of information. (c) Compare your simulation results with the exact Black-Scholes price. = 100, Consider the Black-Scholes model and its European call option pricing formula. Fix So K = 100, T = 1, r = 3%, and o = 20%. (a) Using a built-in normal random number generator in Matlab, find an estimate of the call price C = E [e-T (ST - K)+] based on n = 100,000 samples. (Start your Matlab code with rng (1); if Python, random. seed (1).) Also report the standard error. (b) Draw a graph of Ĉn and 95% confidence interval, that is, (1) graph of Ĉn, (2) graph of upper limit of 95% CI, (3) graph of lower limit of 95% CI, all as functions of n in a single panel. Do this for n = [104, 106] by appropriately selecting values for n for a good quality of information. (c) Compare your simulation results with the exact Black-Scholes price.

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a Using a builtin normal random number generator in Matlab find an estimate of the call price C EeT ST K based on n 100000 samples Start your Matlab c... View the full answer