Suppose you are using one of the minimizing optimizers from Scipy. You are using it to optimize your portfolio for MAXIMUM volatility, and port_vals are the daily total values of the portfolio for a particular allocation. Which of the following would be the best way to compute the objective function for the optimizer?

Consider the following order book. Bid size Price Ask size 55.90 400 55.85 300 55.75 300 100 55.45 75 55.35 200 55.25 At what average price would a market order to SELL 75 shares be executed?

Consider the following valuation factors of a company: It owns 1000 cars valued at $30,000 each It holds patents worth $5,000,000 It owes $5,000,000 in loans It pays $3.00 per year per share in dividends starting in one year The stock price is $60.00 per share There are 1,000,000 shares outstanding The discount rate is 5% Suppose you believe that over a period of a few weeks, the price of the stock will converge to book value + 10%.  What should you do to profit from this expectation?

Suppose you are using one of the minimizing optimizers from Scipy. You are using it to optimize your portfolio to MINIMIZE the cumulative return, and port_vals are the daily total values of the portfolio for a particular allocation. Which of the following would be the best way to compute the objective function for the optimizer?

According to the 60 minutes video “Is the stock market rigged?” which of the following was true for the Katsuyama’s team in 2008?

Consider the following Python session and its output. >>> import numpy as np>>> a = np.random.uniform(size=(7, 6)) >>> b = a/a[1, :] >>> print(XXXX) 1.0 What should you replace XXXX with in order to get the following output?

What is the output of the following Python session? >>> a = 7 >>> b = a >>> a = 2 >>> print(b * a)

Which of the following is NOT typically used as a means of assessing a learning algorithm?

Consider the following valuation factors of a company: It owns 1000 cars valued at $20,000 each It holds patents worth $5,000,000 It owes $5,000,000 in loans It pays $1.00 per year per share in dividends starting in one year The stock price is $60.00 per share There are 1,000,000 shares outstanding The discount rate is 5% The risk free rate is 0% What is the intrinsic value of the company?

Consider the following Python session and its output. >>> import numpy as np >>> a = np.random.uniform(size=(4, 8)) >>> b = a/a[2, :] >>> print(XXXX) 1.0 What should you replace XXXX with in order to get the following output?