FNCE6012 Financial Modeling

•   You are to form teams of 5 people to work on a project with multiple parts. All parts must contribute to a common theme for the project, and must satisfy both the modelling and analysis requirements as covered in the course.

•   These must appropriately use techniques covered in class (using the Excel spreadsheet) and, where needed, other Excel tools and add-ins.

•   All team members are expected to participate fully in the project. A peer evaluation will be administered if required.

• Group formation to submit to TA by 27th April.

• Project Title and Topic (i.e. Hypothesis/ Business Problem) to be send to TA by 27th April.

TA’s email: Athanasius LIAU <athanasiusl.2021@accountancy.smu.edu.sg>

• Assignment report and Presentation ppt due on the 10th June.

• In-Class presentation on 15th June 2024 (Week 9 class). Each group only 15min.

•   Maximum 15 pages for the report (exclude appendix and excel workbook). Submission must include the excel workbook and data   used for the assignment.

Two types of projects are accepted:

1. Exploratory modelling – it is used to discover problem questions and the needed data and analyses to prove or show a hypothesis, and the model structures are useful for what-if analyses, OR

2. Data analysis and decision optimization –  it is usually done in  management science, statistics or business subject courses. This kind of projects assumes a known problem question and  seeks the “best” solution approach and values.

Your final report should consist the following components:

1. Exploratory Modelling Project

a)  Literature Review

Provide the literature review which discuss published information in a particular subject area, and sometimes information in a  particular subject area within a certain time period. Provide a simple summary of the sources that combines both summary and synthesis.

b)  Theoretical construct & Hypothesis

State the theoretical framework or foundation from which the knowledge   is constructed (metaphorically and literally) for the research study you are working on. It serves as the structure and support  for the rationale for the study, the problem statement, the purpose, the significance, and the research questions.

Base on the theoretical construct, develop your hypothesis. A hypothesis is a precise, testable statement of what you predict will be the outcome of the study

c)  Modelling Methodology

Describe what type of modelling techniques you will be using to test your hypothesis. State clearly the rationale of any assumption(s) you are making. These must appropriately use techniques covered in class (using the Excel spreadsheet)  and, where needed, other Excel tools and add-ins.

d)  Data & Descriptive Statistics

Describe where are you data source(s) from and how you obtain them. Provide some descriptive statistics of your data, for example, trend plots, distribution plots, average, interquartile range, variances, corrections….etc.

e)  Modelling Results

Describe the outcome of your model results and whether it support your  hypothesis/ hypotheses.

f)    Conclusion

2. Data Analysis and Decision Optimisation Project

a)  Problem Statement & Decision Outcome

Articulate clearly the problem statement which is a concise description of the problem or issues a project seeks to address. The problem statement identifies the current state, the desired future state and any gaps between the two. State clearly the decision outcome that you need to make given the problem statement.

b)  Business Assumptions  & Rational

What are the absolute or relative measures of the problem that quantify that gap? What are the business assumptions  (including external assumptions  like economic or environmental) you will be making? State clearly the justification and rationale of the assumption(s) made.

c)  Modelling Methodology

Describe what type of modelling techniques you will be using to help you with the decision outcome. State clearly the rationale  of any model assumption(s) you are making. These must appropriately use techniques covered in class (using the Excel spreadsheet) and, where needed, other Excel tools and add-ins.

d)  Data & Descriptive Stats

Describe where are you data source(s) from and how you obtain them. Provide some descriptive statistics of your data, for example, trend plots, distribution plots, average, interquartile range, variances, corrections….etc.

e)  Modelling Results

Describe the outcome of your model results and how will it impact your decision.

f)    Conclusion

Sample ideas: