代写07 40055 LM Applied Financial Econometrics代做留学生R程序

Assignment Remit

Programme Title	MSc Money, Banking and Finance
Module Title	LM Applied Financial Econometrics
Module Code	07 40055
Assignment Title	Assignment
Level	Masters level
Weighting	50%
Hand Out Date	28/10/2024
Deadline Date & Time	08/01/2025		12pm
Feedback Post Date	16th working day after the deadline date
Assignment Format	Report
Assignment Length	1500 words
Submission Format	Online	Individual

Module Learning Outcomes:

This assignment is designed to assess the following module learning outcomes. Your submission will be marked using the Grading Criteria given in the section below.

LO 1. Apply and evaluate econometric procedures employed to analyse financial data.

LO 2. Critically evaluate the results and the approaches adopted.

LO 3. Critically analyse financial databases and create dynamic models using appropriate software, thereby developing key transferrable skills for banking and finance graduates.

LO 4. Develop complex problem solving, digital, analytical and advanced numeracy skills.

General information

• This coursework accounts for 50% of your final mark.

• The coursework is an individual piece of work. You are required to write your own answers and cannot work jointly. All submissions will be routinely checked for plagiarism. [Plagiarism Policy]

• The coursework in either part should not be longer than 750 words, for a maximum of 1500 words in total.

• Figures, tables and codes do not count towards the word limit.

• Please make sure that you fill in the cover page when submitting your report.

Assignment:

Please read the following requirements carefully before you start your project.

The Assignment will be in two parts, Part A and Part B. Each part is worth 50% of marks. Students must answer both parts of the questions. Students shall submit two pdf documents, one for each part, clearly declaring whether the document is for part A or part B.

Part A [50%]

In Part A, you shall

• Follow the assignment remit and answer all the questions as required.

• Perform. the appropriate quantitative analysis and make sure your codes work well. If you receive any error messages, try to correct it. Otherwise, delete or hashtag (#) the code that caused the problem so that you can compile the codes.

• Perform. statistical tests to support your results and empirical approach if needed. Explain the tests hypothesis and interpret the results clearly.

• Present your tables and graphs clearly.

• Explain your procedure (of selecting the best fit model) clearly and provide a detailed and thorough analysis on your results (without going over the word limit)

Bear in mind that

• This is NOT an essay. There is no requirement on the format. But your work needs to be readable and follow the requirements in this remit.

• The coursework MUST be compiled in RStudio and submitted via Canvas in PDF format. You can compile your script. to a Word document first and then add the cover page. Please check if your document is clearly readable. If everything looks good to you, you can save it as a PDF file for submission using Microsoft Word.

• The answers to each question MUST be clearly stated. Your comments and answers to the questions could be written following “#” in your R codes, which will be compiled.

Assignment Questions

You are required to select a listed company in either S&P500 or FTSE100 indices. Download its daily close price data from 1^st January 2024 to the date that you start this project (this can be any date between the release date of this remit and the deadline) and then perform. the following analysis.

1. Write a very brief description on the data you study (no more than 100 words). You need to introduce the company, the sample period, and the data source. You also need to show that the sample is in line with the requirement. [5%]

2. Create a time series plot on the price data and comment on its trends. Then take the log differences on the prices and generate the daily return rates (Returns). Report and comment on the summary statistics including mean, median and standard errors. Plot the time series plot and the histogram of the Returns. Comment on your results. [5%]

3. Plot the ACF and PACF of the Returns and comment on your graphs. Is the daily return series a white noise process? Is it stationary? [5%]

4. Test the stationarity of the Returns with appropriate ADF and KPSS tests. Explain the null hypothesis and the specific format of the tests. [5%]

5. Estimate an appropriate ARIMA model for the Returns. You need to present the estimation results in a well-organised table, explain why you select such a model, and comment on the estimated coefficients. [10%]

6. Based on the ARIMA model of your choice, forecast the stock prices in the next five trading days? You need to explain the details of your forecasting procedure. Comment on your forecast if you know the realised prices. [5%]

7. Based on the ARIMA model of your choice, check if there is an ARCH effect. You must explain your procedure and results clearly. If yes, estimate an appropriate ARMA-GARCH model and explain why you select such a model. Otherwise, estimate a GARCH(1,1) model on the Returns. Based on your model, what is the forecasted volatility of the Returns in the next trading day? [10%]

8. Reflect on your work, assuming you are a line manager and you read such a report.  Comment on the work in terms of its strengths and weaknesses. Identify the areas that need to improve. Please be honest in your reflection. You are welcome to discuss your feelings about this assignment (no more than 100 words). [5%]

Part B [50%]

Computer Project

Aim

Use the dataset Bankdata.dta, which has been extracted from BankFocus, to undertake econometric analysis on bank profitability, measured by either return on average assets, return on average equity or net interest margins.

BankFocus is a global database of banks and financial institutions previously known as Bankscope. The information is sourced by Bureau van Dijk from a combination of annual reports, information providers and regulatory sources. BankFocus offers detailed, standardized reports and data for over 55,000 banks across the globe (30,000 US and 25,000 non-US).  Due to the difficulties accessing data, you are given the dataset.

Bankdata.dta, which can be found under the “Assignment” section on Canvas, contains variables from 11,485 banks over the sample period 2005 to 2019.  A list of the variables and the mnemonics is given in the appendix.  Please note that there are a considerable number of missing observations for some variables.

You must select:

· a specific research question

· the dependent variable

· the group of countries to analyse

· the sample period

· a number of estimation techniques

Since some articles use macroeconomic variables as control variables, you can add macroeconomic variables to the dataset but need to submit the data in an Excel file.  The best places to get the macroeconomic variables are:-

OECD: https://stats.oecd.org/

IMF: https://data.imf.org/?sk=4c514d48-b6ba-49ed-8ab9-52b0c1a0179b&sId=1409151240976

World Bank: https://databank.worldbank.org/home.aspx

You are expected to write an academic report, containing a literature review, presentation/description of data and econometric model, discussion/interpretation of econometric results and analysis plus a conclusion.

Please submit the do file along with the report (compulsory).

A list of suggested references will be provided in Lecture notes and in the assessment support period.

Grading Criteria / Marking Rubric

Your submission will be graded according to the following criteria:

1. Perform. the appropriate quantitative analysis to answer each of the questions.

2. Provide a detailed and thorough analysis on the results, without going over the word limit.

3. Submit a well organised and detailed report.

4. Submit a piece of work that is well written, with no typos or grammatical mistakes, organised and well formatted.