Consider the pseudo code below to obtain the effient portfol…

Consider the pseudo code below to obtain the effient 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() 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}) result = minimize(f, np.zeros(5), constraints=cons) w_optimal = result.x sd_optimal = 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?

Consider the same pseudo code from the previous question to…

Consider the same pseudo code from the previous question to compute 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() 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}) result = minimize(f, np.zeros(5), constraints=cons) w_optimal = result.x sd_optimal = np.sqrt(result.fun)For any given iteration i, what is the shape of the array w_optimal?

Suppose that you want to create a function that receives the…

Suppose that you want to create a function that receives the weights, the expected return on risky assets, and the covariance matrix between the assets, and returns the annualized portfolio volatility and expected return.  def ER_SD(TO BE FILLED): ERp = w @ ER * 100 * 252 SDp = np.array(np.sqrt(w @ Cov @ w)) * 100 * np.sqrt(252) return SDp, ERpWhat should we substitute TO BE FILLED for in order to achieve the desired result?

Consider the following code to identify outliers:1)from skle…

Consider the following code to identify outliers:1)from sklearn.ensemble import IsolationForest 2)iforest = IsolationForest(random_state=0, contamination=0.05).fit(x) 3)y_iforest = iforest.predict(x) 4)idx = (y_iforest==1) 5)x_no_outliers = x 6)y_no_outliers = y 7)print(f’Total Number of Observations: {len(y)}’) 8)print(f’Total Number of Outliers: {len(y) – len(y_no_outliers)}’)Which line has the label without outliers?