Machine Learning with Applications in Finance
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Main Examination Period
ECOM135 Machine Learning with Applications in Finance Duration: 3 hours
ANSWER FOUR QUESTIONS
The first four questions that you submit will be marked. Cross out or
delete any answers that you do not wish to be marked.
COMPLETED PAPERS SHOULD BE SUBMITTED VIA QMPLUS AND ALSO E-MAILED TO
[email protected].
THIS IS AN OPEN BOOK EXAMINATION TO BE CONDUCTED ONLINE. YOU MAY REFER TO
ANY OF THE COURSE MATERIALS, OR ANY OTHER SOURCE OF INFORMATION. YOU MAY
ALSO USE A SPREADSHEET OR CALCULATOR.
THE SHARING OF THIS EXAMINATION PAPER IS AN EXAMINATION OFFENCE.
YOU ARE REQUIRED TO TYPE YOUR ANSWERS, HANDWRITTEN ANSWERS ARE NOT
PERMITTED.
PLEASE ENSURE THAT YOUR WORKING IS CLEARLY SHOWN WITH ALL STEPS OF YOUR
CALCULATION INCLUDED IN YOUR ANSWER DOCUMENT, INCLUDING ANY FORMULA USED.
When writing formulas, please note the following:
· It is acceptable to use the standard alphabet in place of Greek letters. The following are
recommended: a for ↵, b for , d for , D for , l (lowercase l) for , m for µ, v for ⌫ (to avoid
confusion with n), s for , S for ⌃.
· Use + for addition, - for subtraction, * for multiplication and / for division.
· Where appropriate use an underscore to indicate a subscript, e.g. x i for xi.
· Use the ˆ character for power, e.g. x^2 for x2, x^0.5 for px.
· When referring to the following functions use log(x) or ln(x) for loge x, logb(x) for logb x,
exp(x) for ex, cos(x) for cos x.
· Use infty for 1.
· Use Sum to denote summation of terms, e.g. Sum (i=1)^n x i for Pni=1 xi.
· Use Prod to denote product of terms, e.g. Prod (i=1)^n x i for Qni=1 xi.
Guidance continued on the next page
Page 2 ECOM135 (2020)
· Use D for derivative, e.g. D(x^2) = 2x.
· Use Int for integral, e.g. Int a^b (x) dx for R ba x dx.
· Use cap for \ and cup for [ when referring to sets.
· Where it is not obvious that an estimate is implied then state this in full, e.g. ‘a suitable
estimate of b is 0.125’ or more simply (and equally acceptable) ‘est.b = 0.125’.
· Use brackets as necessary. To make your answer clearer use di↵erent types of bracket pairs where
appropriate, e.g. (), [], {}.
Use obvious choices for any other mathematical symbols not listed above that you may require.
Examiner: Dr R.A. Saldanha
c Queen Mary University of London, 2020
ECOM135 (2020) Page 3
Question 1
a) What is a na¨ıve Bayes classifier? Explain the probability model and the decision rule.
[10 marks]
b) Consider the following training dataset which gives selected firm type, size, UK domicile and
whether or not the firm has been granted a margin trading account.
Type Size UK Margin
Hedge Fund Medium no yes
Asset Manager Large yes yes
Investment Bank Medium no no
Asset Manager Small yes yes
Investment Bank Medium no no
How would a na¨ıve Bayes classifier determine whether a new hedge fund that is small in size and
domiciled in the UK would be given a margin trading account?
[8 marks]
c) You work in the credit risk department of a prime broker. A potential hedge fund client appears to
have a poor credit score. However, such a score is quite prevalent, around four out of five hedge
funds have much the same score. You also know that historically the probability of such a score
given observed defaults is also high at around 40%. The actual probability of hedge fund default is,
however, much lower around 7%. Your firm only accepts clients who have less than a 5% risk of
default. Based on the available evidence, do you recommend giving this client a trading account?
[7 marks]
Turn over
Page 4 ECOM135 (2020)
Question 2
The Poisson distribution with parameter has density
P (X = x) =
xe
x!
for x = 0, 1, . . .
a) Explain generally how this particular statistical distribution arises.
[4 marks]
b) i. Under what conditions does the Poisson distribution serve as an approximation to the
binomial distribution?
ii. Under what conditions does the normal distribution serve as an approximation to the Poisson
distribution?
[4 marks]
c) High-frequency algorithmic trading errors for a particular hedge fund occur on only two trading
desks. The first desk experiences an average of one error every five weeks. The second desk
experiences an average of one error every eight weeks.
i. What would be a suitable combined probability model for these data?
ii. Calculate the probability of three or more high-frequency algorithmic trading errors occurring
for the hedge fund during a particular week.
[8 marks]
d) A particular stock exchange experiences the following monthly main hardware computer failures
over a period of 20 years:
Number of Number of
failures months
0 169
1 62
2 7
3 2
4+ 0
Do these computer failures appear to occur randomly in time? Explain your assumptions,
calculations and conclusion carefully.
[9 marks]