Assessment Information for Exam in 24-hour timed window

Module name: MSIN0105                                    

Module code: Financial Econometrics

Module leader names: Toru Kitagawa and Rui Silva

Academic year: 2020-21

Term 1, 2 or 3: 1

Type of assessment: 24-hour timed Online Exam

Nature of assessment – individual or group: Individual

Content of this Assessment Brief

Section	Content
A	Core information
B	Requirements
C	Module learning outcomes covered in this assessment
D	Assessment criteria
E	Groupwork instructions (if applicable)
F	Additional information from module leader (if applicable)

 

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Section A: Core information

This assessment is marked out of:	100 ma	rks
% weighting of this assessment within total module mark	60%
Time allowed for
completion of this assessment	•	This assessment should take approximately 2 hours to complete. You may take longer to complete it if you wish to.
	•	You have a window of 24 hours from release to submission to complete it.
	•	In addition to answering/responding to the questions/requirements, this 24-hour period provides enough time for you to prepare your document for submission (including, as appropriate, copying, pasting, saving electronically) and loading to Moodle.
	•	If you have a SORA which allows for additional writing time for examinations/tests, this has been factored into the 24hour window and no additional time in addition to the 24hour period is available.
Word count/number of pages - maximum	Answers should not exceed 8 (eight) pages.
Determining word count impacted by Turnitin	After submission to Turnitin, the Turnitin recorded word count is usually higher than the word count in a Word document. Where the assessment brief specifies a maximum word count, on the front cover of your submission record the number of words as recorded in your Word document. It is the Word document word count which will be taken account of in marking, NOT the Turnitin word count.
Footnotes, appendices, tables, figures, diagrams, charts included in/excluded from word count/page length?	INCLUDED Any footnotes, appendices are included in the page limit.
Bibliographies, reference lists included in/excluded from word count?	Title page, table of contents, any bibliography are included in the page limit.
Penalty for exceeding specified word count/page length?	Where there is a specified word count/page length and this is exceeded, yes there is a penalty: 10  percentage points deduction, capped at 40% for Levels 4,5, 6, and 50% for Level 7. Refer to Academic Manual Section 3: Module Assessment - 3.13 Word Counts. Where there is no specified word count/page length no penalty applies.
Requirements for/use of references	? This assessment is an ‘open book’ exam/test which you attempt at home, at UCL, or indeed in any other location. It is not invigilated. In principle it should take no longer than the

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	time specified above to complete. However, you have a 24hour timed window in which to download the assessment, to complete it, and to submit it to Moodle. In responding to the demands of this assessment, you may draw upon course materials – lecture slides, notes, handouts, readings, textbook(s) - you engaged with in your studying of this module. You are not expected or required to find and use new materials. In a formal ‘sit-down’ invigilated exam/test you would not be able to find and draw upon new materials – you would draw upon what you learned from your studying of the module. You may refer to such course materials but you should not be copying word for word from lecture slides, notes, handouts, readings, textbook(s) you engaged with in your studying of this module. You should capture, articulate and communicate your views, thoughts and learning in your own words. If you do provide quotes from any lecture slides, notes, handouts, readings, textbook(s) you should cite them and provide references in the usual way. Be aware that a number of academic misconduct checks, including the use of Turnitin, are available to your module leader. If required/where appropriate UCL Academic Misconduct penalties may be applied (see immediately below).
Academic misconduct (including plagiarism)	Academic integrity is paramount. It is expected that your submission and content will be your own work with no academic misconduct. Academic Misconduct is defined as any action or attempted action, including collusion with other students, that may result in a student obtaining an unfair academic advantage. There are severe penalties for Academic Misconduct, including, where appropriate and required, exclusion from UCL. Refer to Academic Manual Section 9: Student Academic Misconduct Procedure - 9.2 Definitions.
Submission date	Tuesday 15th December 2020
Submission time	11am (UK time)
Penalty for late submission?	Yes. Standard UCL penalties apply. Students should refer to https://www.ucl.ac.uk/academic-manual/chapters/chapter-4assessment-framework-taught-programmes/section-3-moduleassessment#3.12
Submitting your assignment	The assignment MUST be submitted to the module submission link located within this module’s Moodle ‘Submissions’ tab by the specified deadline.
Anonymity of identity. Normally, all submissions	Anonymity is required.   Your name should NOT appear anywhere on your submission.

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are anonymous unless the nature of the submission is such that anonymity is not appropriate, illustratively as in presentations or where minutes of group meetings are required as part of a group work submission
Return and status of marked assignments	?	At the latest this will be within 4 weeks from the date of submission as per UCL guidelines, but we will endeavour to return it earlier than this.
	?	Assessments are subject to appropriate double marking/scrutiny, and internal quality inspection by a nominated School of Management internal assessor. All results when first published are provisional until confirmed by the relevant External Examiner and the Examination Board.
	?	No appeals regarding your published mark are available until after confirmation by that Examination Board. UCL regulations specify that academic judgment applied within the marking process cannot be challenged.

 

Academic Support with this Assessment  

Given the nature of this assessment, during the 24-hour window no questions should be directed to the Module Leader/Module Team. If you have doubts about wording or requirements etc., state your assumptions. If they are appropriate they will be taken into consideration in marking.

Uploading your submission

• Unless specifically instructed otherwise in the assessment document, please upload your work as a single file via the submission link on Moodle.
  • Wherever possible you should type/use Excel for (as appropriate) your answers and follow instructions later in this assessment document.
  • If you do have to include any elements that are not typed/computer generated (e.g.

figures, diagrams, equations etc.), or you are unable to type your answers for any reason, please follow the advice for submitting handwritten answers for any submission that requires scanning documents (the webpage refers to 24-hour timed exams but is applicable to all online submissions including this one).

• • If for any reason you are not able to use the app recommended by ISD at the link above, you can consult the following resources for advice about preparing your submission:
    • Submitting handwritten assignments to Moodle using mobile or tablet Devices - Device Camera
    • Submitting handwritten assignments to Moodle using mobile or tablet devices - MS One Drive App
• Please DOUBLE CHECK that the file you are uploading is the correct one and is complete (with all pages visible).Resubmission will not be permitted.

Technical Problems

If you encounter difficulties downloading or submitting your assessment via Moodle, then please immediately notify (by email) Magali Sainte-Luce at mgmt.finance-admin@ucl.ac.uk (Programme Administrators ONLY), explaining the problem and including a copy of the work you are trying to submit. ONLY use this approach if you can show that you have tried to download from/upload to Moodle and encountered technical difficulties.

Advice and other support

? Student Support and Wellbeing

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Section B: Assessment Requirements

See exam paper attached at the end of the brief.

 

 Section C: Module Learning Outcomes covered in this Assessment

This assignment contributes towards the achievement of the module Learning Outcomes stated in the course syllabus.

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Section D: Assessment criteria

Within each section of this coursework you may be assessed on the following aspects, as applicable and appropriate to this particular assessment, and should thus consider these aspects when fulfilling the requirements of each section: 

• The accuracy of any calculations;
• The strengths and quality of your overall analysis and evaluation;
• Appropriate use of relevant theoretical models, concepts and frameworks;
• The rationale and evidence that you provide in support of your arguments;
• The credibility and viability of the evidenced conclusions/recommendations/plans of action you put forward;
• Structure and coherence of your considerations and reports;
• As and where required, relevant and appropriate, any references should use either the Harvard OR Vancouver referencing system (see References, Citations and Avoiding Plagiarism)
• Academic judgement regarding the blend of scope, thrust and communication of ideas, contentions, evidence, knowledge, arguments, conclusions.
• Each part has requirements with allocated marks, maximum word count limits/page limits and where applicable, templates that are required to be used.

 

You are advised to refer to the UCL Assessment Criteria Guidelines, located at https://www.ucl.ac.uk/teaching-learning/sites/teaching-learning/files/migratedfiles/UCL_Assessment_Criteria_Guide.pdf   

 

Section E: Groupwork Instructions 

• Not applicable as this is an individual assessment

 

 

Section F: Additional information from module leaders

 

N/A

Examination Paper 2020/21

MSIN0105: Financial Econometrics

TIME ALLOWANCE: 24 hours

There is ONE (1) section to the examination paper, which consists of four (4) compulsory questions. The allocations of the marks are indicated in the brackets. Each of the four questions has multiple subquestions.

MSIN0105       TURN OVER

Answer all questions. The value of each question is provided in square brackets.

Q1. [20]. Judge if each statement given below is correct or incorrect, providing your reasoning. In these statements, (y_i,x_i), i = 1,...,n, are iid observations of a dependent variable y_i and a vector of regressors x_i = (1,x_1i,...,x_Ki)⁰.

1. Consider a linear model

   

   with

   

   ) = 0. This specification implies that the conditional expectation of y_i given

   

     .
2. The ordinary least square estimator for a linear probability model

   

   with y_i ∈ {0,1} is inconsistent due to heteroskedasticity of the errors, i.e.,

   

   ) depends on x_i.
3. In weighted least square estimation for linear regression model with heteroskedasticity, an observation whose error variance is larger receives a higher weight in the estimation.
4. Consider a linear regression model with a regressor vector x_i that includes an intercept and two dummy (binary) variables d_1i ∈ {0,1} and d_2i ∈ {0,1}, where all the units in the data have either one of d_1i or d_2i equal to 1. That is d_1i + d_2i = 1 holds for all i. In this case, we cannot estimate the coefficients of d_1i and d_2i by OLS due to multicollinearity.

Q2. [25].

As a consultant working for a commercial bank, you would like to develop an econometric model that assists bank’s decision for approving loan applications. Suppose you have access to a database of the past borrowers containing binary Y_i ∈ {0,1} that indicates if borrower i defaults (Y_i = 1) or not (Y_i = 0), together with the borrower’s characteristics including the value of collateral V_i and the interest rate R_i of i’s borrowing. Including an intercept, we denote other observable characteristics of borrower i by vector X_i. Denote the set of regressors by

.

 

Consider a probit model

Pr(

,   (1)

 

where Φ(·) is the cumulative distribution function of the standard normal random variable.

1. [5]. Explain how you estimate the coefficient parameters in the probit model.
2. [5]. Derive the marginal effect of the probability of default with respect to interest rate R_i, i.e.,

   

   ). Does the sign of this marginal effect depend on the conditioning variables, Z_i = (V_i,R_i,X_i⁰)⁰? Explain
3. [5]. To examine a trade-off between the interest rate and the amount of collateral for the borrower’s default probability, consider the marginal rate of substitution (MRS) of the interest rate relative to the value of collateral. Here, MRS is defined by the quantity measuring how much the interest rate has to adjust in response to a unit increase of the value of collateral to keep the probability of default constant, i.e.,

 

 Does the marginal rate of substitution depend on the bor-

 

rower’s observable characteristics Z_i? Discuss.

4. [5]. You want to develop a prediction rule for who will default on the basis of applicant’s characteristics X_i, collateral to be requested V_i and offered interest rate R_i. A prediction rule is a function δ (Z) ∈ {0,1}, i.e., δ(·) = 1 predicts default and δ(·) = 0 predicts repayment. The criterion used to evaluate the performance of prediction rule δ(X) is the probability of correct predictions,

Pr(δ(Z) = Y ) = E [Y δ(Z) + (1 − Y )(1 − δ(Z))].

 

Show that the prediction rule that maximizes the probability of correct prediction is given by

 

, if Pr(Y = 1|Z) ≥ 1/2 ,

 

if Pr(Y = 1|Z) < 1/2.

5. [5]. Would you recommend the prediction rule δ^∗(·) obtained in part (d) to the bank as a way to automate loan approval decisions? Explain your answer.

Q3. [20]. Suppose we are interested in empirically assessing how firm’s debt from the financial sector affects its competitiveness in a product market. We consider the following linear structural model

 

 

where y_i denotes the change in the within-industry sales share of firm i after financing the debt of amount x_1i, w_i is a vector of observable characteristics (including an intercept) of firm i that may directly affect firm’s sales, and u_i is unobserved heterogeneity. Assume that the sample consists of iid observations of (

.

 

1. [5]. In the current example, we should view x_1i as an endogenous variable. Explain why.
2. [5]. Assuming x_1i is an endogenous variable, explain why the OLS estimator for β_x fails to consistently estimate the causal effect of x_1i on y_i. Explain your answer.
3. [5]. Suppose we can measure the resale value of firm i’s tangible assets when the debt was financed. To obtain the two-stage least square (2SLS) estimator, consider using this measure as an instrumental variable. Argue if the exclusion and the rank conditions are credible or not with this choice of instrument?
4. [5]. Can we assess validity of the exclusion and rank conditions based on the data?

Explain your answer.

Q4. [35] After finishing your program at UCL you are offered a job at your favourite investment bank. Your first client is a firm that is planning on pursuing a merger and your first task is to do analysis on the value of mergers.

Part I: The value of mergers to target firms

The first question your client asked you is how much does an acquirer firm typically bid for a target firm in excess of the pre-merger price? In other words, if prior to the merger announcement the target firm’s stock price is £100 per share, what is the average percent change in post-announcement share price. To answer this question you decide to produce a graph of the evolution of the stock price of target firms in merger deals around the announcement date and present figure 1 below to your client.

 

 

Figure 1: Evolution of stock returns to target firms around M&A announcement days. Source: WRDS.

1. [5]. What is the name of this type of analysis?
2. [5]. Using this plot, what would you answer to your client?
3. [5]. Your client, who also attended UCL, knows that to interpret the estimated impact of mergers on the stock return of target firms one needs to pay attention to statistical significance. Please comment on the statistical significance of the estimated effect.

Part II: The value of mergers for acquiring firms

Your client also wants to know what is the impact of the merger on its own stock price. Therefore, the next task your client gives you is to estimate the impact of the planned merger on its own stock price. This time you analyze the change in stock prices of the acquiring, target, and combined firms around merger announcement dates (from 1 day before to one day after, and from 20 days before to the closing of the deal) and produce the following table

 

Figure 2: Evolution of stock returns to target and acquirer firms around M&A announcement days broken down by decade (1973-1998). Source: Andrade, Mitchell, and Stafford, 2001

4. [5]. What is the name of this type of analysis?
5. [5]. Using the information on this table, how would you answer your client? Please comment on both the economic and statistical significance of the effects.

Part III: Final issues and potential solutions

6. [5]. You realize that so far you have studied the evolution of the raw returns of target and acquirer firms, that is, returns that are not adjusted for the overall movement of the market. However, your client insists that the evolution of market adjusted returns would be more informative. Why do you think that might be? Is your client correct?