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Behavioural Finance
Creation date：2024-05-11 16:52:36
Belonging category：金融Finance
Behavioural

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Behavioural Finance
Module code/name MSIN0225/ Behavioural Finance

Assessment title Individual project Brief
Individual/group assessment Individual

Return and status of marked assessments: Within 4 weeks from the date of submission as per UCL guidelines. The
module team will update you if there are delays through unforeseen circumstances (e.g. ill health). All results when
first published are provisional until confirmed by the Examination Board.
Copyright Note to students: Copyright of this assessment brief is with the module leader(s) named above. If this
brief draws upon work by third parties (e.g. Case Study publishers) such third parties also hold copyright. It must not
be copied, reproduced, transferred, distributed, leased, licensed or shared any other individual(s) and/or
organisations, including web-based organisations, without permission of the copyright holder(s).
Academic Misconduct: Academic Misconduct is defined as any action or attempted action that may result in a
student obtaining an unfair academic advantage. Academic misconduct includes plagiarism, obtaining help
from/sharing work with others be they individuals and/or organisations or any other form of cheating. Refer to
Academic Manual Section 9: Student Academic Misconduct Procedure - 9.2 Definitions.
Referencing: You must reference and provide full citation for ALL sources used, including articles, text books, lecture
slides and module materials. This includes any direct quotes and paraphrased text. If in doubt, reference it. If you
need further guidance on referencing please see UCL’s referencing tutorial for students here: https://library-
guides.ucl.ac.uk/referencing-plagiarism/welcome. Failure to cite references correctly may result in your work being
referred to the Academic Misconduct Panel.
Content of this assessment brief
Section Content
A Core information
B Coursework brief and requirements
C Module learning outcomes covered in this assessment
D How your work is assessed
E Additional information

Published 18th July 2022

Section A: Core information

Submission date 01/08/2022
Submission time 10am
Assessment is marked out of: 100
% weighting of this assessment
within total module mark
100%
Maximum word count/page
length/duration
2000
Footnotes, appendices, tables,
figures, diagrams, charts included
in/excluded from word count/page
length?
Everything apart for the reference list, tables, graphs, and the
appendices is included in the word count
Bibliographies, reference lists
included in/excluded from word
count/page length?
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
Standard UCL penalties for exceeding (deduction of 10
percentage points, capped at 40% for Levels 4,5, 6, and 50% for
Level 7) Refer to Academic Manual Section 3: Module
Assessment - 3.13 Word Counts.

Penalty for late submission Standard UCL penalties apply. Students should refer to Refer to
https://www.ucl.ac.uk/academic-manual/chapters/chapter-4-
assessment-framework-taught-programmes/section-3-module-
assessment#3.12
Submitting your assessment Please submit your project to the Turnitin box ‘Individual
project’ on the web site of Behavioural Finance, under the tab
‘Submissions’.
Anonymity of identity. Normally, all
submissions are anonymous unless
the nature of the submission is such
that anonymity is not appropriate,
illustratively as in presentations or
where minutes of group meetings
are required as part of a group work
submission
The nature of this assessment is such that anonymity is required.


Published 18th July 2022

Section B: Assessment 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.

The write-ups should include:
a. [15 marks] Introduction
i. Background and literature review leading to the research question and
two hypotheses. The literature review should include papers from peer-
reviewed journal, but it can include also other sources of information.
ii. An explanation about the importance of the research question.
iii. An explanation about the contribution of the study to the literature
(showing in which ways the study is original).

[Marking scheme:
10-15 marks: Challenging and innovative research question, which has important
applications. The research question is closely related to at least one of the topics
taught at the course. The hypotheses are related to the research question and are
well-formulated. The research questions and the hypotheses clearly draw on
contemporary Behavioural Finance research, including studies which were taught
at the course Behavioural Finance.

Published 18th July 2022

5-9 marks: The research question is appropriate, but not innovative or somewhat
related to one of the topics taught at the course. The hypotheses are satisfactorily
stated. The relationship to the literature, to the contents of the course, and the
applications lack some clarity or are modest.

0-5 marks: The research question or the hypotheses are poorly formulated, have
unclear scope, or are not closely related to any of the topics taught at the course.
The relationship to the literature is unclear or absent.]

b. [25 marks] Method
i. Data sources (for experiments and surveys, that should include
participants’ details. For studies using secondary data – the data
sources).
ii. Additional information about the data / materials used (for experiments
and surveys – the materials, e.g. questionnaires, pictures, or graphs. For
studies using secondary data – any additional relevant information about
the data, e.g. data characteristics).
iii. Study design (for experiments and surveys, this section should include
the design and procedure of the study, independent variables,
dependent variables, control variables, operational definitions, and
procedure. For studies using secondary data – the independent
variables, dependent variables, control variables and any other relevant
methodological details).

[Marking scheme:
17-25 marks: The data sources are comprehensive and the design is thoughtful and
relevant to the research question and hypotheses. The research methods used are
robust. There is strong evidence of attention to details and critical thought about the
method.

10-17 marks: The data sources are appropriate and the design is clear and relevant
to the research question and hypotheses. The research methods used have many
limitations. There is some evidence of attention to details.

0-10 marks: Poor research approach which lacks consideration of the chosen
methods in terms of their suitability to the context of the research. There is little
evidence of attention to details. The study has many limitations or important details
are absent.]



c. [25 marks] Results, including hypothesis testing (and the statistical analysis
details), qualitative analysis (in case the study involved also qualitative
elements), explanations and interpretation.

[Marking scheme:
17-25 marks: The hypotheses are tested using relevant statistical methods and the
results are interpreted correctly. The analysis and the presentation of results is
outstanding or to a publishable standard. There is a clear contribution to
knowledge.
Case category
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EMESTER1 MAS8383 ECO 512 STAT 8310 CMN3102 MA577 CMPT 225 COMP0045 Methods Equations MATH 113 Math 3283W ICS-33 EN4302/ENT603 BIA B350F MA318 MTHM506 MECH 5315M ECONOMICS MAS8382 COM 2004 PX3142 XJEL 3662 STAT 231 MGT B399F PX4131 COM2108 30AM MSCI521 ECONM1015 ACFI304 GR5241 MATH10101 ECON 2070 COMS31900 EFIM20011 CSE 250B ACSE-5 STAT4207 SOFT2412 ELEC 331 AY2020 MSIN0209 FIT2094 CS 241L ST404 CS 411 3D CA3 INF4002 COMP3506 SIT718 CS 188 CS 170 MATH 138 CSE 251A CMT118 DATA5207 CMPT307 CMPT459 T1 PGEE11108 COSC 3P32 ME 163 MATH96007 7QQMM203 EE6227 BA 574 STA 4234 ECO206Y1Y ECO2008 MT2300 MATH 11158 CS 527 MACM 316 CSE474 2DI70 ISE 525 COMP3411 EMAT30007 7CCSMBDT MFIN704 MFIN704W21 MfIB ECE 438 CS 436 F36 CS5344 FE 621A FE621 TBA 612 ECM3151 ECMM422 MF1 MSIN0107 ESSMENT CS 5854 MFIT 5008 MIPS R4000 ENG5274 BU52018 ENG2079 BIOA02 STA2570 F0 INF553 STAT 440 STAT3008 COMP9417 COMP6451 6COM1042 BU52006 ST303 HW-1 CISC-235 CS 510 MATH3161 ECN 140 ECE391 Comp 3613 CVEN 9625 PRG455 UESTION 1 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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 MATH20602 COMP532 MAS275 COMP5318 COMP4002 FIT5086 MAST20004 FIT3152 FIT5129 CIS2380 CS521 COMP 1005 EECMS CITS5501 ECE 462 ECON 6002 ENG 4051 CSC 648 CMT654 MECHENG 713 PHYS1002 AMME 2000 FP0060 DDES3200 MECHENG 743 BINF90002 FIT2081 ISYS90081 ELECTENG 722 BUS 360 ECOS3010 BUS2810 ETF2100 ENG2048 STAT5002 COMP2017 CEME 2003 MATS3004 COMP9319 PHYS1001 COMP5349 AMME2261 COMP-381 FIT3173 COSC2757 ENG4025 QBUS2820 COMP9414 MATH2021 EOSC118 MFIN6690 PMATH 321 CSE-141L MATH575A COMPSCI5002 COMP1511 management comp2123 FINS3616 COMP 3331 COMS30034 DTSC 71 AcF 702 AcF702 DTSC71 MAT021 ELE8083 ACFI213 EG-127J 127J FIT5163 FIT2001 ELE00113M CMT310 CS 245 ENGL 1101 MTH6115 EE497 CS 325 Math 124A MTH5130 MBA502 MGT 5380 ARCH 1261 F033800 20LLP109 ELE4009 FINANCIAL COMP3331 Computer ECE4179 20T3 COMP9311 COMP9311 UNSW MFIN6210 ACCT 5930 EE590 ENG2029 ECO100 SIT315 ACCT3610 COMP3600 STK2100 FIT2004 COMP30020 ACTL1101 Stat 101B BANA 200 COSC2473 ENGG1400 AI COMP90043 MMF 1914H PHYS 127 CS584 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MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A 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ACCOUNTING BUSS1040 CHEM 181 MAT136H1 GY 6183 COMP3170 AGRI90089 PHYSICS 1002 ECON10003 IEOR E4004 ACS61012 MATH 40550 MKTG2113 TELE4653 ENSC1004 ECE 232E MK726 MTRX2700 SHEET 3 CSCA08 COMP30027 Math 2XX3 statistic MMAN3200 BISM7213 ECMM109 ECON 2022 FNCE 20005 GR5067 CSCB09 ME 3017 CS 5100 PHYS 2903 COMS 4771 COMP222 COMP 1046 CSC148H1 ISYS2038 FINS2615 OT5206 COMP2048 A6 MECH5770M MA826/20 CMPT 726 STA457 INFS6071 INFS588 integral ECON 216 IRDR 0017 MA323 PA 15213 PSYC2001 ENV222 Statistics ACCT5930 ACCT12 LAND2121 ME 5405 COMM1180 TELE3113 A7 ECE 568 ACCT2019 INFS1200 ENGG1340 CS 1400 ASST3 FINM7409 SWEN30006 INFO2222 FIN20150 SOSS1000 CSSE7231 FINS5513 COMS3200 CECN 702 ECON4060H MN3515 HW2 PSYA02H3 ECON 2112 COMP90051 CS 1652 MA30059 AF1605 MKTG7501 ECO-6003B COM4521 CTM ECON3350 COMP 3804 ELEC9762 BISM 7255 ST22 MATH20014 MNE3122 COMP343 MATH5165 ELE7029 ENGR30002 SEEM3500 ECON7350 RISK5002 FINM7405 COMP90059 MOS 3320B STAT 431 BISM7221 MATH3014 MTH783P EBA 35302 ACS133 BUS2206 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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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