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Consider the following order book. Bid size Price Ask size 100.10 490 100.05 500 100.00 1000 2000 99.95 2000 99.90 1500 99.85 How would you expect the price to change over the next few minutes?

Consider the following valuation factors of a company: It owns 1000 cars valued at $20,000 each It holds patents worth $7,000,000 It owes $10,000,000 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 1% What is the book value of the company?

According to the 60 minutes video “Is the stock market rigged?” what did spread networks do?

Which of the following is true about bagging (without boosting)?

Consider the following order book. Bid size Price Ask size 200.80 300 200.75 200 200.50 100 200.25 200 100 199.95 200 199.90 100 199.85 At what average price would a limit order to SELL 400 shares at $199.85 be executed?

In CAPM, the returns resulting from investment skill are known as?

According to the CAPM, which statement is true regarding Alpha and Beta for a typical stock drawn from the market portfolio? Assume the market has gone up 1% in the last day.

Consider overfitting when using kNN and a polynomial parametric model. When overfitting occurs with these two methods, in which “direction” does it occur?

Consider kNN, linear regression (LR), Decision tree (DT) (using correlation for splitting), and Random tree. Which model has the slowest training time?

Consider the following code snippet.   >>> import numpy as np>>> a = np.random.uniform(size=(3, 3)) >>> a array([[0.51639863, 0.57066759, 0.02847423] [0.17152166, 0.68527698, 0.83389686] [0.30696622, 0.89361308, 0.72154386]]) >>> b = np.random.uniform(size=(3, 3)) >>> b array([[0.18993895, 0.55422759, 0.35213195] [0.1818924 , 0.78560176, 0.96548322] [0.23235366, 0.08356143, 0.60354842]]) >>> XXXX >>> a array([[1. , 1. , 1. ] [1. , 0.68527698, 0.83389686] [1. , 1. , 0.72154386]]) What code could you replace with XXXX to cause the following output?