RFDP Case Study Analysis Help With Solution

RFDP Case Study Analysis Help With Solution

This is a study to predict the average volume of fixed deposit (FD) held by the public on a quarterly basis from different areas (metropolitan, city or town). The equation in the multiple regression is a demand relationship, and we would expect the dependent variable to depend on total personal wealth, on the interest rate that individuals receive when part of that wealth is invested in a fixed deposit, and so on. The primary interest rate on fixed deposit (RFDP) was therefore chosen as an explanatory variable. However fixed deposit must compare with other interest-bearing assets such as government bonds. Thus, the interest rates on government bonds (RGB) and are also explanatory variables; when this variable increase, the total demand for fixed deposit should decrease. Finally, the lagged dependent variable is also introduced to reflect lags.

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Since the volume of fixed deposit, as well as many other financial variables, displays a seasonal behavior, a set of seasonal dummy variables is introduced to explain as much of this seasonal behavior as possible. The seasonal variables take the form of quarterly dummy variables multiplied by personal income. Since the first seasonal variable takes on the value of 1 in first quarter and 0 otherwise, the first seasonal variable takes on the value of personal wealth in first quarter. There are a total of 4 seasonal variables in the model, and the constant term should be drop to eliminate the collinearity problem.
Being a consultant of Ministry of Finance, you are required to perform some data analysis on the demand of fixed deposit. The relevant data has been provided to you by the ministry in Appendix 1 and 2.
Use at least three of the following appropriate quantitative management techniques to examine and analyse a particular aspect of the case study:
(i) One-sample / two-sample t-test for difference
(ii) Chi-squared test for independence
(iii) Correlation / simple or multiple linear regression
(iiii) Fixed effect factor model/Random effect factor model
(v) Factor analysis/Structural equation modelling
(vi) Forecasting techniques
Write a report, with a maximum of 1500 words, that tackles the following tasks:
Briefly describe the case study, identify the area/issue to be investigated, and explain its importance.
(b)​Aims, objectives and hypotheses
Identify the main aims, objectives of the study and formulate THREE difference hypotheses to be tested.
(c)​Findings & Discussions
Demonstrate the applications of suitable quantitative management techniques in the testing of these three difference hypotheses. The goal is to describe the data measured and the analyses performed as indicated based on the hypotheses. Tables and charts need to be labelled and numbered for easy reference (at least must have four tables/charts). Each chart or table should be able to stand on its own and tell its own story.
Descriptions of the analysis methods should be complete so that the reader can assess the validity of your methods. You need to include a description of what was being tested, the statistical methods used and any assumptions that were made. You do not need to include all your output, but select the output that supports your conclusions. Interpret all the findings. You should include any explanations you may have for what you have found in the data.
(d)​Conclusions & Recommendations
Draw conclusions (e.g: which factors give a high impact on the demand of the fixed deposit and etc…) and make recommendations. What are the limitations of the analysis? Where appropriate, identify areas for further investigations/study.
(e)​Reference Use proper referencing.
Use proper appendix to enhance report presentation. It may include the data and output of SPSS. Also include data view and variable view from SPSS.
(g)​Presentation, structure, organisation and writing styles
The report presentation, structure and organisation. The writing styles in the report include the language used, proper grammar and spelling.

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