Widener University Financial Econometrics Paper


The goal of the project is to develop a statistical model for a specific business problem
and provide a thorough analysis of it.
Possible topics: prediction of prices for a specific
stock/bitcoin/commodity/futures/options; prediction of a country’s GDP level using
market indicators; prediction of auto sales; analysis of bonds liquidity, etc.
You should choose a topic that interests you, construct a solid multivariable regression
model by brainstorming which factors can be relevant to prediction, obtain data and use
R to carry out statistical analysis.
It is expected that you work with a sufficiently large data set originally to find which
factors are significant for the model (I expect 20-25 factors). Including categorical
variables along with continuous variables is strongly encouraged.
Check the assumptions of the model by carrying out residual analysis (see the R video
on that in particular) and provide recommendations if there are significant violations.
Test relevant hypotheses. Remove insignificant variables and analyze the new model
using R tools.
I can provide guidance and advice during the course of project, if needed. Please ask
your questions during class/office hours or email.
You will need to submit a report covering the background information (the topic of
research), the objective of your research, model description with following rigorous
statistical analysis and conclusions.
There is no requirement on the size of the final report but typically it should be 10-15
pages + Appendix with R code. Make sure to indicate all additional resources you use,
including the data sources, in the reference list. Include your R code in the Appendix of
the report, that is in the pdf file.
The cover page should contain your name, an abstract, and the statement:
“I have neither given nor received help (apart from the instructor) to complete this
assignment” with your signature.
An abstract is a concise summary of a research paper or entire thesis. It is an
original work, not an excerpted passage. An abstract must be fully self-contained and
make sense by itself, without further reference to outside sources or to the actual paper.
I require the abstract to be no more than 400 words. The abstract is essentially a short
presentation of our work that you can use, for example, during the job interview
Be very critical about all work you submit. Presentation counts!
Upload the files on Canvas (a pdf file with the final report and all necessary data
and .R files).
The instructor reserves a right to ask any student about the solution process and if it’s
clear that the student doesn’t understand the material, they will receive a grade 0 on the
Copying the solutions or parts of them from others/posting them online will
cause serious issues and will be reported to the Office of Academic Integrity.
——————————-The rubric:
Cover page: 1 pt
Abstract: 5 pts
Background information: 10 pts
Description of factors (20-25 requested): 10 pts
Discussion of the assumptions of the model backed up by graphs and analysis: 30 pts
Recommendations in case of violation of the assumptions: 10 pts
Statistical analysis (hypothesis testing): 25 pts
Proper citation and reference list: 5 pts
Presentable source files and code uploaded on Canvas: 4 pts
Project grade is the sum of the points above.
If there is no code in the Appendix/Canvas: grade = max{Project grade – 80, 0}

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