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Behavioural Finance MSIN0225
Creation date：2024-05-06 16:45:48
Belonging category：金融Finance
Behavioural Finance

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Behavioural Finance

MSIN0225

Term 1, 2 or 3: Term 3
Nature of assessment – individual or group: individual

Content of this coursework Brief
Section Content
A Core information
B Coursework brief and requirements
C Module learning outcomes covered in this
assessment
D Assessment of this coursework

2

Section A: Core information
This assessment is
marked out of
No marks will be given. However, feedback will be provided.
% weighting of this
assessment within
total module mark
0% of the final mark of the course
Word count/page
length - maximum
1 page, font 11, regular margins
Footnotes, appendices,
tables, figures,
diagrams, charts
included in/excluded
from word count
Excluded from the word count

Bibliographies,
reference lists included
in/excluded from word
count
In-text references are included in the word count.
The reference list is excluded from the word count.

Penalty for exceeding
word count/page
length
None, but feedback will be given only on the first page.
Academic misconduct
(including plagiarism)
Academic Misconduct is defined as any action or attempted
action that may result in a student obtaining an unfair
academic advantage. Refer to Academic Manual Section 9:
Student Academic Misconduct Procedure - 9.2 Definitions.
Submission date Tuesday 10 May
Submission time 10.00 am UK time
Penalty for late
submission
None. However, research proposals will be marked only if
they are submitted before 24 May.
Submitting your
assignment
Your answers to the questions MUST be submitted to the
module submission link located within this module’s
Moodle ‘Assessment’ tab by the specified deadline.
Anonymity of identity The nature of this assessment is such that anonymity is
required. Accordingly, no reference to your name(s) should
appear on your submission. Insert only your UCL ID number(s)
and do so on the front cover.

Return and status of
marked assignments
At the latest this will be within 4 weeks from the date
of submission but we will endeavour to return it much
earlier than this.

3

Section B: Research proposal Brief and Requirements

For the Behavioural Finance project, students are required to conduct research on topic of
their choice, subject to the following conditions:
1. The project topic should be closely related to one of the topics taught in the course
Behavioural Finance, including
a. Judgment and decision making under uncertainty; prospect theory
b. Central behaviour finance effects (e.g. attention effects and the disposition
effect)
c. Emotional finance theories
d. Financial practitioner – client relationship
e. Bank client behaviour
f. Financial crime
g. Ethics in Finance.
2. The topic should go beyond the existing Behavioural Finance literature.
3. It should be possible to study the topic using quantitative research methods. The use
of qualitative research methods in addition to quantitative methods is optional.
4. The topic should enable research which is in line with the ethics requirements of the
School of Management. If the research involves participants, it should satisfy the
Ethics Code of Conduct of the British Psychology Society.

In particular, students are required to
• Conduct a literature survey on their topic
• Formulate a research question and two relevant hypotheses
• Design a study to test the two hypotheses. The study can include an experiment, a
survey, or analysis of secondary data
• For studies involving experiments or surveys: submit an ethics form through the
ethics form Turnitin box on the web site of the course. The work on the project is
conditioned by an approval of the ethics form
• Conduct the study
• Analyse the data
• Summarise and submit the literature survey, method, results, and conclusions in a
write-up. Project submissions should be done to the Turnitin box ‘Individual projects’
on the web site of the course.

To prepare you for this task, we invite you to submit a research proposal. The purpose of
the research proposal is to provide the students with feedback on their dissertation ideas.

Thus, it would be good if you choose for your research proposal a topic that satisfies the
conditions which are mentioned above.
Then, conduct an extensive literature survey. Please include in your literature survey
papers from peer-reviewed journals.
Then, choose three papers from the ones that you read, which are:
4

• The most relevant to your research question
• From peer-reviewed journals.


Please include in your research proposal:
1. Title - Your topic
2. Introduction section, including:
a. Discussion of the three papers from peer reviewed journals that you chose,
their main results and how they lead to your research question
b. Discussions of the shortcomings of the literature, as reflected through the
papers that you read in your literature survey and in particular in the three
papers that you chose. In addition, your discussion should explain how your
dissertation would extend the existing literature and highlight the originality of
your research question.
3. Theoretical background and hypotheses development, including discussion of
references (possibly other references) and how they lead to your hypotheses
• The suggested method – that could be an experiment, a survey, or analysis of
secondary data. Please include essential details about your method, including your
design, how you would measure/ manipulate/ find data for your independent and
dependent variables, materials, and your sample (data sample or participants’
sample). If you intend to conduce an experiment or a survey, please give an
example of your questions or tasks.
4. Ideas for your analysis, including an explanation of how you would conduct your
analysis (for example, regressions, t-tests, content analysis, etc).
5. Applications (for example, an explanation of the way in which groups, such as
investors, or institutions, such as banks or firms, could benefit for your work).
6. Reference list

Referencing:
The referencing should be in line with the Harvard referencing style and UCL’s referencing
standards. Whenever you use information from sources, use in-text references to indicate
that, and write their complete references in your reference list.

Length limit:
One page, not including reference list (but including in-text references). Please use font 11
(e.g. Calibri or Times New Roman), single spaced paragraphs and have regular margins
and spaces.


Good luck!







5

Section C: Module Learning Outcomes covered in this
Assignment
This assignment contributes towards the achievement of the following stated
module Learning outcomes:
1. Understand central behavioural finance theories and their applications: students’
project should be closely related to the contents of the course Behavioural Finance.
Thus, to write a project, students should understand the theories taught in the
course.
2. Recognise the way psychological factors influence financial decision making: the
course reviews psychological factors affecting financial decision making, and thus,
related projects should demonstrate knowledge of these effects.
3. Be familiar with research methods used in behavioural science: students are
required to be familiar with research methods used in Behavioural Finance in order
to design an original study.
4. Be able to perform research on Behavioural Science: students will indeed conduct a
Behavioural Finance study. Thus, they will demonstrate that they can conduct
research on Behavioural Finance.
Section D: Assessment of this Coursework
Within each section of this coursework you may be assessed on the following aspects,
as applicable and appropriate to this particular assessment, and should thus consider
these aspects when fulfilling the requirements of each section:
• Appropriate use of relevant literature;
• The strengths and quality of your overall methodology, analysis, arguments
and evidence that you provide in support of your arguments;
• The accuracy and appropriateness of any suggested methods;
• Structure and coherence of your project proposal;
• Appropriate and relevant use of the taught topics and additional reference

Notice that this assignment does not count towards your final Behavioural Finance
mark.
Case category
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MGMTMFE 405 25579 1ECE 273 M122 COMP4434 1ELEC ELEC5620M STAT0010 BFF2401 MXB361 MATH3811 CS330 CMT307 FIT1033 CptS 583 UP 431 MATH6005 AF5343 CS2435 ECOM30002 ES50061 CS 2506 ECMT6002 CODE 00099F MT4539 ESSAY ICM317 MATH1231 MFIT5010 BMA547 MATH334 CIVL2201 MATH39032 T-04 CIVE97119 EMESTER CAB302 CAB301 59PM STAT802 ISYS3412 RM3 COSC 2123 AcF 311 MATH2022 1FINAL 4CCS1PHC ICM 142 ENVS3023 Math 4023 I1 ACSE8 FIN B385F CS-275 STA 4109-01 A31021 EE140 MT1 EE124 ECO-6004B Inf2-IADS CS126 IS2184 UL18 MATH5092 ECOM009 COMP 6211 ELEC202 MKT3019 IAB230 FIT5046 584-S21 COMP3210 CO250 A29401 MATH 136 MGT6174 ECMT6007 DATA2001 MAT 443 MATH10222 PHDE0071 ELE00123M COSC1295 MAT00045H MATH32032 1004GRC MAS223 COMP10001 DATA3404 CIVL2110 STAT2008 FNCE10002 EEE6431 COM6515 COMP9120 NBS8185 ECTE942 ECON 405 MATH314301 STAT 2011 COMPSCI 350 COMP20007 CMPSC-132 ECON5002 STA 35 MTH6108 FIT5147 MTH6150 100C FINA 5260 DESC9115 ECON4998 NBS8257 GMM ECON 6070 BSA2 ECE599 STATS 102B STA120 INFS601 BFC3241 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CMP7000A CMP-7038B Math 263 LAW3016 CS371 STAT 334 FIN0008 ACC3004 STAT 371 ​COMP1921 MTH201 ACCT2000 UN3412 CIV6000 MATHS 3021 MATE7014 ECON1 CIBC6035 LAW121G COMM 321 CSC8204R TTM2033 CSCI 2600 MAE 115 LNG302 CENV6175W1 ECON30019 CPS2015 BST969 DDES9015 AMATH242 CS 1151 N1592 ACCT600 EG503G SMM519 EC318 Ecstatistics EEE 471 MARK2051 Topology COM00037H ACCT3000 MTHM501 EG501V COM00055H BUSN9085 GGR273 MATH 2B ITD102 MA214 ECON0060 ECE3114 ECMM447 Mechanics CCT361H5S BSAN3210 WELF2001 Fin3001 RESP5001 STA 137 Linguistics 101 CSCI368 CMPSC497 LUBS3655 OMBA 5355 BUSM2562 ​BFF5902 CYBR7001 CULT2005 ECON 7720 MTRX3760 FSE598 ​LUE1001 MGSC 7100 CS3240 COSC7500 ACCT3091 INFOGR TRAN 2080 DESIGN CIVE215001 CIVE2360 CPSC 8430 FNCE2003 Stoichiometry INFS6023 Quantitative Method Math 21D ECE5179 Design ​ECON8022 Chemical DMS 213 ADM1370 BFF5902 BFF2701 AGRI10051 AMN400 ECON7322 ​FINC5090 ​MATH1052 ​SciComp Elec4622 ​FINS5516 ENG 101 MMM143 CS431CA2 BSAN2201 EBSC7070 ES9v9-10 PLIN0009 DATA 8 MATH 101 BCPM0097 ​MAT 237 BISM2201 EEE8099 Physics 11 ECE2238B Biostat 234 ​ECON30009 INF10025 CHEM252 CCMA4008 CIVE 3007 STAT0031 ELEC ENG 3108 MGMT90140 CHEM 252 STAT3016 MMM095 ​MMGT6016 Legal STAT 311 ELEC9764 COMP 370 TCS 3053 EECS 1021 FIT1051 C/C++ EE3C COMP2003J COM398 COMP51915 Simulator FIN42330 8PRO102 PGD ELEC5160 XJCO1921 COMP5123M INFS 2042 CHE1148H ECA5313 IN3329 Microsoft Modeling B15 2TT COMP3687 COMP2432 DMS2030 KAN4TSF CFKG CSE 5322 CSE 445 STATS 3DA3 CHC5223 COMP1048 EL3105 EECS 3221 CS231 ME 4434 ITP4510 ITP4501 CSCI 5708 Controller EECE 5699 CPEN 231L CPN programs CSC8016 MATU9D2 ENGN4213 2. SVM. (10 points) Consider an SVM classifier using RBF kernel, and finish the following python code to search for the optimum kernel parameter γ. You are required to calculate the RBF function and search yourself, instead of using functions in Scikit-Learn (sklearn). def parameter search(gamma list ,Xtr,ytr,Xts,yts ,...): """ Parameters gamma list: A list of RBF kernel parameter gamma to search for Xtr: Training data, shape (ntr,nrow,ncol) ytr: Training labels, shape (ntr,) Xts: Test data, shape (nts,nrow,ncol) yts: Test labels, shape (nts,) ... Add other parameters as needed Returns: gamma optimum: The gamma with minimum error on Xts, yts """ ... return gamma optimum
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