Create a GBM function in Python.

Q4 Create an GBM function that takes the following parameters: n := number of paths to be simulated m:= number of discretization points per path SO := initial starting point dIn(S.) = (x - -)dt + odW Then convert it to S: Program the function by using two nested "for loops" In [ ]: def GBM(n,m, 50,mu, sigma, dt): np.random.seed (999) arr = # arr[] = for i in: for j in : arr[i, j] = #convert Ins_t into Sut return arr part b) run GBM function with the following parameters and plot the results ABM(n=1000,m=20,50=100, mu=0,sigma=0.001,dt=1) Q4 Create an GBM function that takes the following parameters: n := number of paths to be simulated m:= number of discretization points per path SO := initial starting point dIn(S.) = (x - -)dt + odW Then convert it to S: Program the function by using two nested "for loops" In [ ]: def GBM(n,m, 50,mu, sigma, dt): np.random.seed (999) arr = # arr[] = for i in: for j in : arr[i, j] = #convert Ins_t into Sut return arr part b) run GBM function with the following parameters and plot the results ABM(n=1000,m=20,50=100, mu=0,sigma=0.001,dt=1)