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Quantitative Analysis of Finance I: ECON90033

Group Project 1:  Bubbles or not bubbles?

Aims.

Investigate statistical properties of a selected series on a price of an asset and write a report answering the question:

What fluctuations in the data one should expect in the next five periods?

Your aim is to characterise the future unknown values of these data  following  the  newest  available  observations.     Link  the documented data properties to interpret the forecasts.  Use the methods and models discussed during Lectures 1–5.  Use these basic methods and feel free to expand this set of tools if you find it useful.

Data.

Choose  a  financial  asset  from  stock  indices  (but  not  the  All Ordinaries  Index),  listed  companies,  exchange  rates  (but  not AUD/USD), or crypto currency.  Obtain 500 (daily, weekly, or monthly) most recent observations on its series from the portal finance.yahoo.com.   Download the data and transform  it to a series of log-levels.

In your analysis you are encouraged to use any other variables. They can  be  used as  long as they are  useful  in answering the main question of the assignment.  Please, be transparent on the specification of these variables, their sources and transformations.

Minimum requirements.

Your report must include the following types of analysis:

●  Provide extensive (model-based) characterisation of data

●  Perform model selection procedures

●  Report residual diagnostics for the models whose forecast you decide to report

● Characterise the forecasts using various statistical tools and forms of their presentation

●  Perform  subsample  analysis  of  the  financial  bubble(s) detection procedure.

● While using function ar() use the argument method=”ols” Your report should not be limited to the tools mentioned above.

General information.

● The assignment contributes 15% to your final grade

● Submission is due on Friday, 8 April, at 6 pm

● Submit your report via Canvas assignment submission tool: Canvas _ Assignments _ Group project 1

●  Late submissions are not accepted and are equivalent to receiving a zero grade for the assignment

Criteria of assessment.

● Clarity and coherence in the presentation of the empirical material

● Creativity in approaching the question

● Correctness  of  the  application  of  econometric  methods including their appropriate implementation in R

●  Interesting interpretations of results

● Quality of tabular and graphical presentation of results

Submission format.

1.  The submission consists of two files:  a pdf file containing your  report,  and  an  R  file  for  the  reproduction  of your results.

2.  Upload a pdf file with your report not exceeding 8 pages. The front page should include a 100 words abstract that concisely summarizes your main conclusions.

3.  Upload the R file that will allow for the exact reproduction of all of the empirical results from your report. The results that cannot be reproduced decrease the grade.

4.  The  word  count  should   be  around   1500  words  with a recommended deviation of not more than ·150 words. The content of the tables and figures should not be included in the word count.

5.  Each person in the group must send a confidential email with  their  assessment  of  the  contribution  of  each  of member of the group to the project.  For instance, if you value the contributions of your group members in a group of four  students  evenly,  then  send  an  email  stating  the contributions:   Name  1:  25%,  Name 2:  25%,  Name 3: 25%,  Name 4:  25%.   Please send this email to Tomasz Wo´zniak: [email protected].

6.  Prepare nice, readable, concise, and informative tables and figures. They should include only the elements that you are interpreting.  Do not just copy/paste or take screenshot of the outcomes from R. The quality of tabular and graphical representation is one of the criteria of assessment.

7.  The front page should include:  the title, the name of the group, names and student numbers of all of the members of the group, the abstract of your report describing the most important finding.