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CS7646 - ML4T > Midterm Exam Study Questions > Flashcards

Midterm Exam Study Questions Flashcards

1
Q 
What	is	the	output	of	the	following	Python	session?
>>>	def	func(x	=	2):
...					b	=	2
...					return	x	*	b
...	
>>>	x	=	3
>>>	b	=	3
>>>	print	func()
A) 2
B) 6
C) 4
D) 9
A

C

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2
Q 
What	is	the	output	of	the	following	Python	session?
>>> a = 3
>>> b = a
>>> a = 2
>>> print b * a
A) 4
B) 6
C) 3
D) 2
A

B

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3
Q 
Consider	the	following	Python	session	and	its	output.	What	should	you	replace	XXXX	
with	in	order	to	get	the	following	output?
>>> a = np.random.uniform(size=(3,2))
>>> b = a/a[1,:]
>>> print XXXX
1.0
A) b[0,1]
B) b[1,1]
C) a[0,1]
D) a[1,1]
A

B

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4
Q

Consider the following data:
COL_1 COL_2 COL_3
100.00 0.00 0.00
101.00 0.01 0.01
102.00 0.02 0.01
100.00 0.00 -0.02
102.00 0.02 0.02
What might the data in each of the columns represent (from left to right)?
A) Cumulative return, portfolio value, daily return
B) Daily return, portfolio value, cumulative return
C) Cumulative return, daily return, portfolio value
D) Portfolio value, cumulative return, daily return

A

D

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5
Q 
Which	code	snippet	below	would	correctly	calculate	the	Sharpe	ratio	for	time	series	
daily_rets	that	represents	60	days	of	daily	returns?	The	risk	free	rate	is	represented	by	
rfr
#	snippet	A
sharpe	=	math.sqrt(60.0)	*	np.mean(daily_rets	– rfr)	/	np.std(daily_rets)
#snippet	B
sharpe	=	math.sqrt(60.0)	*	np.std(daily_rets	– rfr)	/	np.mean(daily_rets)
#	snippet	C
sharpe	=	math.sqrt(252.0)	*	np.mean(daily_rets	– rfr)	/	np.std(daily_rets)
#snippet	D
sharpe	=	math.sqrt(252.0)	*	np.std(daily_rets	– rfr)	/	np.mean(daily_rets)
A

C

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6
Q 
Consider	the	following	code	snippet.		What	code	could	you	replace	with	XXXX	to	cause	
the	following	output?
>>> a = np.random.uniform(size=(3,2))
>>> a
array([[ 0.9598058 , 0.30898308],
 [ 0.08671576, 0.83212644],
 [ 0.9701383 , 0.25618103]])
>>> b = np.random.uniform(size=(3,2))
>>> b
array([[ 0.363649 , 0.86394158],
 [ 0.89838762, 0.46682958],
 [ 0.76027507, 0.46149348]])
>>> XXXX
>>> a
array([[-1. , 0.30898308],
 [ 0.08671576, -1. ],
 [ 0.9701383 , -1. ]])
A) a[0,0]	=	-1
B) a[a<0.5]	=	-1
C) a	=	a/a[0,:]
D) a[b<0.5] = -1
A

D

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7
Q

Which statement is TRUE?
A) Mutual funds can be traded throughout the trading day.
B) Hedge fund holdings are fully transparent.
C) ETF managers earn 20% of the ETF’s profits.
D) ETFs can be traded throughout the trading day.

A

D

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8
Q

Which statement is FALSE?
A) Hedge fund managers typically charge 2% of profits and 20% of AUM as fees.
B) Mutual fund managers typically charge 0.25% to 2.0% of AUM as fees.
C) ETF managers typically charge 0.1% to 1.0% of AUM as fees.
D) Hedge fund managers typically charge 2% of AUM and 20% of profits as fees.

A

A

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9
Q

Consider two hedge funds. Both of them have provided equivalent positive cumulative
returns. Which of the following might be a valid reason for choosing HF1 over HF2?
A) HF1 has a lower Sharpe ratio than it’s benchmark, but HF2 has a higher Sharpe that its
benchmark.
B) HF1 has a higher standard deviation of daily returns than HF2.
C) HF1 has a lower standard deviation of daily returns than HF2.
D) HF1 has a higher Bollinger value than HF2.

A

C

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10
Q

According to the 60 minutes video “Is the stock market rigged?” which strategies have
high frequency traders used to exploit market mechanics?
A) A dedicated fiber optic link between Silicon Valley and the exchanges in New York.
B) A dedicated fiber optic link between Chicago and the exchanges in New Jersey.
C) Front running orders by exploiting faster network connectivity.
D) B and C.

A

D

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11
Q

How does the IEX exchange defeat the high frequency traders investigated in the 60
minutes video?
A) Using dark pools.
B) Using 60 kilometers of fiber optic link to delay visibility of the order book.
C) By converting the market to a series of discrete auctions every 2 seconds.
D) By prohibiting limit orders.

A

B

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12
Q 
Consider	the	following	order	book.	At	what	average	price	would	a	limit	order	to	BUY	100	
shares	at	100.05	be	executed	at?
Bid	size Price Ask	size
                100.10 300
                100.05 300
                100.00 200
100 99.95
50 99.90
100 99.85
A) 100.00
B) 100.025
C) 100.05
D) 100.10
A

A

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13
Q 
Consider	the	following	order	book.	At	what	average	price	would	a	market	order	to	SELL	
250	shares	be	executed	at?
Bid	size Price Ask	size
                 100.10 300
                 100.05 300
                 100.00 200
100 99.95
50 99.90
100 99.85
A) 99,95
B) 99.90
C) 99.85
D) None	of	the	above
A

B

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14
Q 
Consider	the	following	order	book.	How	would	you	expect	the	price	to	change	over	the	
next	few	minutes?
Bid	size Price Ask	size
               100.10 100
               100.05 100
               100.00 200
1000 99.95
500 99.90
500 99.85
A) The	price	will	go	up	because	there	is	buying	pressure.
B) The	price	will	go	down	because	there	is	selling	pressure.
C) The	price	will	stay	about	the	same.
D) The	price	will	remain	fixed	at	99.95
A

A

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15
Q 
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	2%
What	is	the	book	value	of	the	company?
A) $25,000,000
B) $20,000,000
C) $15,000,000
D) $30,000,000
A

C

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16
Q 
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	2%
What	is	the	intrinsic	value	of	the	company?
A) $25,000,000
B) $20,000,000
C) $15,000,000
D) $50,000,000
A

D

17
Q 
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	2%
Assume	the	price	of	the	stock	should	settle	to	book	value	+	10%.	What	would	you	expect	to	
happen	to	the	price	in	the	future?
A) The	price	should	stay	about	the	same.
B) The	price	should	go	up.
C) The	price	should	go	down.
D) A	shrubbery.
A

C

18
Q

According to the CAPM, which statement(s) are true regarding Alpha and Beta? Assume
the market has gone up 1% in the last day.
A) If a stock’s Alpha is 2% and the Beta is 1.0, the stock should go up 2%
B) If a stock’s Alpha is 1% and the Beta is 2.0, the stock should go up 2%
C) If a stock’s Alpha is 1% and the Beta is 1.0, the stock should go up 2%
D) If a stock’s Alpha is 2% and the Beta is 2.0, the stock should go up 3%

A

C

19
Q 
According	to	the	CAPM,	which	statement(s)	are true	regarding	Alpha	and	Beta?
A) The	expected	value	of	Beta	is	0.0.
B) The	expected	value	of	Alpha	is	0.0.
C) We	expect	Beta	=	Alpha
D) We	expect	Alpha	>	Beta
A

B

20
Q

If the weak form of the EMH is true, which sorts of trading advantage(s) would be
eliminated?
A) Insider information only.
B) Fundamental information only.
C) Technical information only.
D) All advantages including: Insider, Fundamental and Technical.

A

C

21
Q

Suppose a stock has split (1 share becomes 2 shares) 4 times between 2010 and 2016
and that you use a historical price service that adjusts prices for splits and dividends. If
the actual market close price for the stock on July 1, 2009 was $100.00 and on July 1
2017 it was $200, what would you expect the adjusted close to be on those two dates
respectively?
A) $6.25 in July 2009, and $200.00 in July 2017.
B) $100.00 in July 2009, and $3200.00 in July 2017.
C) $100.00 in July 2009, and $200.00 in July 2017.
D) $400.00 in July 2009, and $800.00 in July 2017.

A

A

22
Q

Suppose you have historical stock price data with data missing on some days in history
(the values are NaN). You still want to use the data in backtesting and calculation of
technical factors. Which of the following options are recommended (in the book)?
A) Replace the NaNs with zeros.
B) Fill the data back only.
C) Replace the NaNs with the average price.
D) Fill forward, then fill back.

A

D

23
Q

Consider kNN, linear regression (LR), and Decision tree (DT) learning (using correlation
for splitting). Which option correctly lists the methods from fastest to slowest in training
time?
A) kNN, LR, DT
B) LR, kNN, DT
C) DT, LR, kNN
D) LR, DT, kNN

A

A

24
Q

Consider kNN, linear regression (LR), and Decision tree (DT) learning (using correlation
for splitting). Which option correctly lists the methods from fastest to slowest in query
time?
A) kNN, LR, DT
B) LR, kNN, DT
C) DT, LR, kNN
D) LR, DT, kNN

A

D

25
Q

Consider two decision trees trained on the exact same data. DT was trained using
correlation for splitting, RT was trained using splits determined randomly. Both trees
were trained with leaf_size = 1. Which option below correctly describes (in order): The
fastest to train, the fastest to query, the highest accuracy on in-sample data?
A) DT, DT, DT
B) RT, about the same, about the same
C) RT, RT, about the same
D) DT, RT, about the same

A

B

26
Q

Consider overfitting when using kNN and decision trees. When overfitting occurs with
these two methods, in which “direction” does it occur?
A) As k increases; As leaf_size increases
B) As k increases; As leaf_size decreases
C) As k decreases; As leaf_size decreases
D) As k decreases; As leaf_size increases

A

C

27
Q

Which of the following is NOT an advantage of ensemble learners?
A) Less susceptibility to overfitting.
B) Reduction in RMSE when using weak learners.
C) Improved computational speed compared to individual weak learners.
D) Can work with many types of weak learners

A

C

28
Q

Which of the following is NOT typically used as a means of assessing a learning
algorithm?
A) The standard deviation of predicted values.
B) Compute time for training.
C) Compute time for querying.
D) Correlation of predicted values with known correct values.

A

A

29
Q

Consider a data set composed of 1000 samples where X is drawn randomly uniformly
from -2PI to +2PI, and Y = sin(X) (two full sine wave cycles). Consider kNN, decision
trees, random trees and linear regression. Which statement is true regarding in-sample
RMSE?
A) Linear regression will perform best.
B) kNN, decision trees and random trees will all do better than linear regression.
C) kNN and linear regression will perform about the same.
D) Decision trees will perform significantly better than random trees.

A

B

30
Q

Suppose you are using one of the minimizing optimizers from ScikitLearn. You are using
it to optimize your portfolio for MAXIMUM 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?
A) objective = port_vals.max()
B) objective = - port_vals.max()
C) objective = port_vals[-1]/port_vals[0]
D) objective = - port_vals[-1]/port_vals[0]

A

D

CS7646 - ML4T (2 decks)

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