Description
University of the West of England
College of Business & Law
ACADEMIC YEAR 2023/24
Assessment Brief
Submission deadline : Before 14:00 on Wednesday 17 July 2024
Marks and Feedback due on : Wednesday 14 August 2024
Module title and code : Quantitative Methods for Finance UMADXF-15-M
Assessment type : Written assignment
Assessment title : Assignment
Assessment weighting : 100% of total module mark
Size or length of assessment : 2000 words Maximum word count (no +/- 10% to be used)
Where should I start?
The assignment requires you to produce a quantitative report covering TWO tasks from four topics listed below:
- Multiple regression
- Stationary and non-stationary time series analysis
- Volatility modelling
- Panel data analysis
The full report should not exceed 2000 words excluding references and appendix. Please answer two questions out of four.
PLEASE ANSWER TWO QUESTIONS ONLY
Q1. Multiple regression: Determinants of mutual fund performance
Use multiple regression model to determine which factors explain mutual fund performance. To assess the performance of a given fund manager, researchers regress the fund’s total return against some benchmark index and other factors. We expect that risk is a major factor in determining fund performance. Typically, the independent variables include, the fund manager’s age, years of experience (EXPR), and years of education (EDUC), fund style (value versus growth), fund age, and fund risk exposure (standard deviation, beta).
Data: The file “mult_reg.xlsx” available on Blackboard in the Assignment folder contains all data required for this question.
Research Question:
- Is age a determinant of mutual fund performance?
- Is education more important than experience in improving the performance of fund managers?
Econometric model:
Please state your econometric model with appropriate assumptions.
Hypothesis testing
Please state the hypotheses you are testing and the rationale for these.
Basic statistics:
Please provide the following information in an appropriate table and explain their implications.
Mean, standard deviation, skewness, kurtosis, Jarque-Bera normality test.
Model estimates:
Run regressions and report your findings. Please put your t-stats in brackets and indicate significance with *, **, *** for significance at 10%, 5% and 1% respectively. Alternatively, you may use p-values.
Diagnostic tests:
Please carry out the following tests if you think they are doable given the nature of the data. Explain why these tests are, or are not, relevant.
- Auto-correlation test
- Collinearity check
Conclusion:
Q2. Time Series Analysis of Price and Earnings
You are given time series of price (lnP) and earnings (lnE), and you would like to analyse the value relevance of earnings. Specifically, you are first required to determine if the time series are stationary or integrated with order one, and in the latter case if they are cointegrated. Then, dependent on the outcome of the above analyses, an appropriate autoregressive distributed lag (ARDL) model or ECM is to be fitted.
Data: The file “timeseries.xlsx” available on Blackboard in the Assignment folder contains all data required for this question.
Research Question: Can change in price be explained by earnings?
Preliminary tests:
- Test for presence of unit root
- Test for cointegration
Econometric model: The econometric model will depend on the outcome of unit root tests and cointegration test.
Hypotheses testing
Test for significance of relevant coefficients, i.e. the coefficient of change in earnings and (if appropriate) the coefficient of error from the cointegrating relationship.
Basic statistics:
Mean, standard deviation, skewness, kurtosis, Jarque-Bera normality test.
Model estimates (t-stats in brackets):
Which is the best model?
Diagnostic tests:
Auto-correlation test
Conclusion:
Q3. GARCH models
You are given a financial time series of returns on a stock (RET). You would like to use a GARCH-in-mean model to investigate whether there exists a time-varying risk premium.
Data: The file “garch.xlsx” available on Blackboard in the Assignment folder contains all data required for this question.
Research Question:
– Does higher volatility result in higher expected return?
– Is there a leverage effect?
Econometric model:
State your econometric model with appropriate assumptions
Hypothesis
State your hypothesis
Basic statistics:
Provide the following descriptive information in a suitable table
Mean, standard deviation, skewness, and kurtosis.
Normality test
Estimate the models and report your findings
Which is the chosen model and why?
Suggest a suitable model and justify this choice
Diagnostic test on residuals:
(1) normality;
(2) standardized residuals correlogram test;
(3) Squared standardized residuals correlogram test.
Conclusion:
Q4: Panel data analysis on the determinants of bank profitability.
You would like to find out about the determinants of bank profitability. Where profitability is proxied by (i) return on average asset (ROAA), and (ii) return on average equity (ROAE). The literature suggest that profitability could be influenced by bank capital strength (CAP), credit risk (CR), operating cost (CM), asset quality (AQ) and liquidity (LQ). You are given a panel of N banks each with T years of the explanatory variables. Use pooled, fixed effect and random effect models to analyse the data and undertake a Hausman test. You may wish to discuss why net interest margin (NIM) and total assets (TA) may or may not be appropriate explanatory variables.
Data: The file “bank-panel.xlsx” available on Blackboard in the Assignment folder contains all data required for this question.
Research Question: What are the factors that affect bank profitability?
Econometric model: State your econometric model with appropriate assumptions.
Hypothesis
State the hypotheses you will be testing and why?
Provide the following descriptive statistics in a suitable table.
Mean, standard deviation, skewness, kurtosis, Normality test
Estimate the following models:
- Pooled OLS
- Panel FE Estimates
- Panel RE Estimates
Report both standard and HAC t-stats
Do the Hausman’s test and discuss its implications.
Conclusion
If you wish to receive high quality solution to the above questions, please talk to us on WhatsApp +254716353533.
