Consider the numbered lines below:1)def price(PMT, IY, g): 2) return PMT / (IY – g) 3) 4)g = np.linspace(0, 0.09, 21) 5)IY = 0.1 6)PMT = 10 7)PV = np.zeros_like(g) 8)for i in range(len(g)) 9) PV[i] = price(PMT, IY, g[i]) 10)plt.plot(g, PV) 11)plt.xlabel(‘Growth Rate’) 12)plt.ylabel(‘Perpetuity with Growth Price’);If we execute the code above, we receive an error. In which line lies the error?
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I was late and keep chatting with my classmates during class…
I was late and keep chatting with my classmates during class time,
If I want to make an audio or a video recording during class…
If I want to make an audio or a video recording during class,
If I missed test 1, test 2 and my final exam score is 85,
If I missed test 1, test 2 and my final exam score is 85,
If I missed test 1 and my final exam score is 85,
If I missed test 1 and my final exam score is 85,
Consider the function h = lambda x: x**2 + 4*x – 5 / x If we…
Consider the function h = lambda x: x**2 + 4*x – 5 / x If we use fsolve from scipy.optimize to find the x where h(x) = 0, with a starting guess of x0=0.01, what is the output we obtain?
Consider the pseudo code below to obtain the efficient portf…
Consider the pseudo code below to obtain the efficient portfolios:from scipy.optimize import minimize f = lambda w: TO BE FILLED mu = np.linspace(15, 30, 31) sd_optimal = np.zeros_like(mu) w_optimal = np.zeros([31, 5]) for i in range(len(mu)): # Optimization Constraints cons = ({‘type’:’eq’, ‘fun’: lambda w: np.sum(w) – 1}, {‘type’:’eq’, ‘fun’: lambda w: w @ ER * 252 * 100 – mu[i]}) result = minimize(f, np.zeros(5), constraints=cons) w_optimal[i, :] = result.x sd_optimal[i] = np.sqrt(result.fun)Assuming that ER are Cov given, what should we substitute TO BE FILLED for in order to get the desired result?
What is the output of the following code? newlist = np.zeros…
What is the output of the following code? newlist = np.zeros(4) for i in range(len(newlist)): newlist[i] = i + newlist[i] print(newlist)
Consider a portfolio with the following weights w, expected…
Consider a portfolio with the following weights w, expected return on each risky asset ER, and covariance matrix Cov below. w = np.array([0.05, 0.03]) ER = np.array([0.10, 0.02])Cov = np.cov([[0.004, 0.0156], [0.0156, 0.009]]) Which of the following expressions represents the portfolio volatility in Python?
How many atoms are in a face centered cubic lattice?
How many atoms are in a face centered cubic lattice?