MM917留学生作业代写、代做Networks课程作业、Python编程语言作业调试、代写Python作业

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Coursework for MM917 “Networks in Finance”
Report 1 deadline: 23:59 29/03/2020 (GMT)
Report 2 deadline: 23:59 15/04/2020 (GMT)
The goal of this coursework is that you write two reports. It will be 30% of your mark. The
first report is about the analysis of research papers on Networks in Finance and the second
is about analysis of network data.
Report 1: Analysis of research papers on networks in finance (20 marks)
Please find the attached file (ResearchPapers.zip) on Myplace. The file contains all the
review papers and research papers. Each of you needs to read three review papers and one
assigned working paper to write your report.
Review papers
The Review papers will provide you general information on financial networks and systemic
risk. Your Report 1 must begin with general introduction to financial networks and systemic
risk based on these review papers. Such general introduction needs to describe the state-ofthe-art
of the use of networks in finance and particularly the importance of network analysis
for the study of systemic risk and contagion in financial networks.
Working papers
Each of you will read and analyze one of working papers. The list of the randomly assigned
working paper is given the table below. You need to analyze your own working paper
and describe your understanding of the paper. This analysis should contain the following
points in your own language (not directly copying from your paper):
A. Background: What did the paper look for? What is the research question and why
answering to the research question is important?
B. Methods: How did the authors answer to the research question? Why they choose
the methods?
C. Results: What did the authors find, measure, derive, or analyze?
D. Implications: What is the answer to the research question? What can we learn? With
the results, what we can do?
Tips for the Report 1
1) I understand that some papers may be difficult for you to understand. BUT FOCUS ON
THE ESSENCE OF YOUR PAPER not on the perfect understanding. Please note that the
points of your report are:
A. To demonstrate the essence of your paper not the technical details. This means that
you need to understand the motivation, the background, the importance, the
methods, the main results, and the implications of your paper.
B. To deliver your understanding to others in your own language.
2) One way to understand your paper better is to read the related papers together. Normally
you can find such related papers in the references of your paper.
3) Read your paper with your colleagues and explain to each other.
How to write Report 1
Write a report addressing the following points and questions:
1) General Introduction (based on review papers): What is systemic risk? What is financial
contagion? Why understanding systemic risk is important? Why networks are important
to understand systemic risk and financial contagion? (750~850 words)
2) Background (of the working paper): What did the paper look for? What is the research
question and why answering to the research question is important? (400~500 words)
3) Methods (of the working paper): How did the authors answer to the research question?
Why they choose the methods? (400~500 words)
4) Results (of the working paper): What did the authors find, measure, derive, or analyze?
(500~600 words)
-You need to explain clearly two key figures in your research paper (e.g. what do the
figures demonstrate? what do the x-axis and y-axis of figures represent?)
5) Implications (of the working paper): What is the answer to the research question? What
can we learn? With the results, what we can do? What is practical meaning of the
results? (300~400 words)
6) Reference: All the references you read to analyze your review papers and working
paper (No page limit)
 Assume that you were explaining your paper to someone not familiar with the subject.
 In general introduction, describe the state-of-the-art of the use of networks in finance
and in particular the importance of network analysis for the study of systemic risk
and contagion in financial systems.
 In Background, demonstrate what problems the authors considered and why these
problems are important.
 Describe the method of your research paper in the Methods in a clear and direct
language and use the authors’ mathematical expressions if necessary..
 In implications, discuss the results in a wider perspective. For example, what is the
answer to the research question, what could we learn from this paper, what the
results mean in finance, and what are the limitations of the paper.
 Refer to all the literatures that you have used, including webpages. The references
must be properly cited in the text, e.g., using numbers. The list of references must
include the authors, title of the paper, journal, volume, year, and pages.
Report 2: Analysis of network data (10 marks)
Please find the attached file (NetworkData.zip) on Myplace. Each of you will have one
network data set. You can analyze this network data with your own codes or existing
programs. Specify what you use in your report. Include any program or code used into
the Appendices as well as any secondary information. If the code is taken from a website,
please mention it in the references. Otherwise make clear you have created your code.
How to write the Report 2
[1] Measure network size, number of links, average degree, the standard deviation of degree.
[2] Plot degree distribution in linear-linear scale and in log-log scale.
[3] Measure the average local clustering coefficient (Newman’s) and plot the average
clustering coefficient of nodes with degree k.
[4] Plot the degree correlation function and measure the Newman’s assortativity coefficient r.
[5] Demonstrate your codes or describe how to use your program to analyze the data.
The following figures illustrate how to plot, as an example. Here P(k) is the degree
distribution. C(k) is the average clustering coefficient of nodes with degree k. Knn(k) is the
degree correlation function.
The network data format: 2-columns, Undirected network.
1 2 (this means node “1” is connected to node “2”)
1 3 (this means node “1” is connected to node “3”)
3 4

-If there is 1 2 in the data, there will be also 2 1 because all the data are undirected one. But
note that you need to consider 1 2 and 2 1 as a single link. Check your program before use
because, depending on the codes you use, some codes may consider this case as two links.
About the programs to be used
There are many codes available for network data analysis. If you google ‘Network analysis
with R’ or ‘Network analysis with python’, then you can find many resources or YouTube
videos tutorial. If you know R, ‘igraph’ is a good tool for you. If you know python, ‘NetworkX’
is a good tool for you. The following links are my recommendations. You do not need to
follow all the detailed information on the following links or read all the manuals. Since our
analysis is very basic, it is sufficient for you to know how you can install these tools on your
computer and how to measure the basic quantities such as degree, clustering coefficient,
and so on.
a. http://kateto.net/networks-r-igraph
http://www.kateto.net/wp-content/uploads/2016/01/NetSciX_2016_Workshop.pdf
(If you know R, these are one of the best resources.)
b. http://networkx.github.io/
https://networkx.github.io/documentation/stable/_downloads/networkx_reference.pdf
https://networkx.github.io/documentation/stable/tutorial.html (Python)
c. https://www.cl.cam.ac.uk/teaching/1415/L109/l109-tutorial_2015.pdf (Python)
d. http://www.levmuchnik.net/Content/Networks/ComplexNetworksPackage.html (Matlab)
Common for Report 1 and Report 2
1. Please use San Serif (e.g. Arial) font and the font size should be at least 11.
2. Your reports should be PDF or Word document. The margin is at least 2 cm.
3. Write down your name and student ID on the report.
4. Keep the deadlines strictly.
5. Start early and prepare the report with sufficient time. If you start the report just few
days before the due date, it is really difficult to write a good report.
6. Before you analyze the network data, test your program with small artificial network
you make to prevent obvious mistakes. For example. If you have only two nodes with
one link in the artificial data, you program should report you that there are two nodes
and one link. Otherwise, your program is wrong.
The assignment of research papers and network data
Name Working paper Network data
Talal Maqsood Qadir Abdulqadir 5 3
MANSOUR MUNAJI N Alrashdi 2 14