ULMS Electronic Module Catalogue |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | Econometrics for Finance 1 | ||
Code | ACFI225 | ||
Coordinator |
Dr A Gazi Finance and Accounting Adnan.Gazi@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2024-25 | Level 5 FHEQ | First Semester | 15 |
Pre-requisites before taking this module (other modules and/or general educational/academic requirements): |
ACFI111 QUANTITATIVE METHODS FOR ACCOUNTING AND FINANCE |
Modules for which this module is a pre-requisite: |
Programme(s) (including Year of Study) to which this module is available on a required basis: |
Programme(s) (including Year of Study) to which this module is available on an optional basis: |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
24 |
6 |
30 | ||||
Timetable (if known) | |||||||
Private Study | 120 | ||||||
TOTAL HOURS | 150 |
Assessment |
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EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Assessment 1: Multiple Choice Midterm Assessment Type: Unseen Examination, Not Managed by SAS Duration: 1 hour Weighting: 30% Reassessment Opportunity: Yes Penalty for Late Submission: Standard U | 1 | 30 | ||||
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Assessment 3: Individual Presentation Assessment Type: Presentation Duration: 5 minutes Weighting: 10% Reassessment Opportunity: Yes Penalty for Late Submission: Standard UoL Penalty applies Ano | 5 | 10 | ||||
Assessment 2: Individual Report Assessment Type: Coursework Size: 2500 words Weighting: 60% Reassessment Opportunity: Yes Penalty for Late Submission: Standard UoL Penalty Applies Anonymous Asse | 0 | 60 |
Aims |
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This module aims to: |
Learning Outcomes |
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(LO1) Students will be able to apply their knowledge of regression models using the statistical software Eviews |
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(LO2) Students will be able to test single and multiple hypotheses |
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(LO3) Students will be able to interpret the output of a statistical software |
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(LO4) Students will be able to evaluate the assumptions underpinning the estimation methodology |
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(LO5) Students will be able to identify and address the various issues pertaining to a particular analysis |
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(S1) Problem Solving Skills |
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(S2) Analytical Skills |
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(S3) Communication Skills |
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(S4) Lifelong Learning |
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(S5) Digital Fluency |
Teaching and Learning Strategies |
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The module entails 12 face to face lectures. The key applications will be mostly done during the 6 seminars (1-hour each) in the computer lab. Journal articles and financial press articles will be used to illustrate the real-world applications of the key concepts. The teaching will also be supported by online activities. These include self-assessment quizzes that enable students to evaluate their own learning and receive formative feedback instantaneously. Furthermore, discussion boards will be used to foster the exchange of ideas, thus deepening the knowledge of students and improving their communication skills. These activities will be moderated by the module instructor. Students will also be directed to key academic and practitioner readings to further develop their learning. Teaching Method 1: Lecture Teaching Method 2: Seminar Self-Directed Learning Hours: 120 Skills and Attribute Mapping Skill 1: Problem Solving Skills Skill 2: Analytical Skill 3: Communication Skills Skill 4: Lifelong Learning Skill 5: Digital Fluency |
Syllabus |
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• Multiple regression model |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |