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?
Read DetailsConsider the code below with numbered lines:1)def h(x): 2) r…
Consider the code below with numbered lines:1)def h(x): 2) return np.exp(-x**2 / 2) / np.sqrt(2 * np.pi) 3) 4)x = np.linspace(-4, 4, 51) 5)y = np.zeros(x) 6) 7)for i in range(len(y)-1): 8) y[i] = h(x[i]) 9)plt.plot(x, y) If we run the code above, we will receive an error. In which line lies the error?
Read DetailsAssume we live in a world where the CAPM holds and it is giv…
Assume we live in a world where the CAPM holds and it is given by ER = lambda beta: beta * 0.05 + 0.02If you know this linear relationship between beta and ER, you can compute the ER for a given beta.What is the ER on a stock with beta = 0.5?
Read DetailsAssume we download the stock price of Tesla and compute its…
Assume we download the stock price of Tesla and compute its return using the command startdate = ‘2019-01-01’ enddate = ‘2021-01-01’ tesla = web.get_data_yahoo(“TSLA”, startdate, enddate)R_tesla = tesla[‘Adj Close’].pct_change().dropna() Which of the following commands is used to compute the volatility of Tesla returns?
Read DetailsConsider an economy with three possible states: bad, normal,…
Consider an economy with three possible states: bad, normal, and good. The probability of each state is given in the array of probabilities “p” below. The payoff of a risky stock in each state is given in the array R. p = np.array([0.1, 0.6, 0.3]) R = np.array([[0.05], [0.03], [-0.02]]) If we want to compute the expected return on this risky asset, what is the command line we should execute in Python?
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