讲解 FINS3645 Financial Market Data Design and Analysis - 2024辅导 Python编程

FINS3645 Financial Market Data Design and Analysis - 2024

Published on the  13 May 2024

Course Details & Outcomes

Course Description

Technology is a disruptive factor that is transforming the banking and fnance industry. Financial market participants need to process an ever-increasing amount of heterogeneous data to make  fnancial decisions and create disruptive fnancial products.

In this hands-on course, you will learn to leverage the relationship between data requirements    and competitive advantage in a rapidly evolving marketplace. Through constant interaction with large datasets, you will develop the product design and delivery skills necessary for developing  solutions to real-world fnancial data problems.

Course Aims

This course aims to develop skills in data handling in the context of banking and fnance and to gain introductory exposure to state-of-the-art data modeling and analytics. This course is thus   designed for students aiming to understand the connections between banking,fnance and technology.

Relationship to Other Courses

Technology is a disruptive factor that is transforming the banking and fnance industry, It is important that fnance graduates are informed of these development and have a basic understanding of the underlying technology and data handling so they could contemplate, adapt, innovate and shape an increasingly technology driven world. This course builds on basic fnance theory and capital market courses and complement other fnance courses with a unique technology and innovation perspective.

Course Learning Outcomes

Learning and Teaching Technologies

Moodle - Learning Management System | Blackboard Collaborate | EdStem

Learning and Teaching in this course

This is a practical and hands on course. Students undertake individual data driven project. The project requires all stages and steps to be fully contemplated, from idea generation to implementation. The course will draw on concepts, problems and practical implications from textbooks, academic papers, fnancial press articles as well as relevant fnancial regulators and government agencies. The aims of this course are:

  Develop skills in data handling in the context of Banking and Finance

  Gain introductory exposure to state-of-the-art data modeling and analytics

This course is thus designed and developed for students aiming to understand the connections between banking,fnance and technology.

Assessments

Assessment Structure

Assessment Details

Data Design Model and Report

Assessment Overview

Building on your Data Design Business Case, you will report on the prototyping and implementation of your data-driven FinTech solution. You will be required to explain your model, outline your considerations of user needs, and explain how you have addressed assumptions and difculties, and in doing so demonstrate your capacity to take initiative and bring about innovation. Further details will be made available during term.

Assesses: PLO1, PLO2, PLO3, PLO7

BCom students: myBCom course points for PLO7

Course Learning Outcomes

  CLO3 : Apply appropriate and responsible solutions to address real-world fnancial data problems.

  CLO4 : Design and deliver innovative data-driven solutions for the banking and fnance sector.

Detailed Assessment Description

Weight     Assessment Name       Assessment Due Date

50%        FinTech Project B         Week 10

As an individual and a FinTech specialist you deliver on programming project and will be tasked with contemporary, complex and real-world problem to be solved by using big-data analytics and current state-of-the-art approaches in fnancial engineering. Final delivery is in a form of a code and data design and analysis leading to delivering FinTech product wireframes. Realistic solution offnal delivery is assumed. Further details on tech cooperation and relevant tips and suggestions will be posted on Moodle.

(BCom students: myBCom course points for PLO7)

Submission notes

See Detailed assessment description

Assignment submission Turnitin type

Not Applicable

Data Design Business Case

Assessment Overview

For the Data Design Business Case you will take the role of product architect to design and pitch a data-driven FinTech solution to a provided case. You will outline key product decisions and features, supported by python code of ETL and feature engineering. As part of this, you will be required to think ethically and sustainably in delivering a responsible FinTech solution. Further details will be made available during term.

Assesses: PLO1, PLO2, PLO3, PLO5, PLO7

BCom students: myBCom course points for PL05

Course Learning Outcomes

·  CLO2 : Interpret and analyse large sets of both structured and unstructured fnancial data.

·  CLO3 : Apply appropriate and responsible solutions to address real-world fnancial data problems.

·  CLO4 : Design and deliver innovative data-driven solutions for the banking and fnance sector.

Detailed Assessment Description

Weight       Assessment Name     Assessment Due Date

20%         FinTech Project A       Week 8

As an individual and a FinTech specialist you deliver on programming project and will be tasked with contemporary, complex and real-world problem to be solved by using big-data analytics and  current state-of-the-art approaches in fnancial engineering. Final delivery is in a form of a code and data design and analysis leading to delivering FinTech product wireframes. Realistic solution offnal delivery is assumed. Further details on tech cooperation and relevant tips and suggestions will be posted on Moodle.

Submission notes

See Detailed assessment description

Assignment submission Turnitin type

Not Applicable

Quizzes

Assessment Overview

This individual assessment is comprised of two quizzes that assess material covered across Weeks 3-9. Each quiz will be made up of a series of multiple choice questions and short answer programming questions. This assessment is aimed at providing you with early feedback on your performance and understanding of the course topics.

Assesses: PLO1, PLO2

Course Learning Outcomes

·  CLO1 : Review various data handling, analytics and computational methodologies.

·  CLO2 : Interpret and analyse large sets of both structured and unstructured fnancial data.

Detailed Assessment Description

Weight  Assessment Name    Assessment Due Date

15%       Quiz 1                         Week 7

15%       Quiz 2                         Week 7

Quiz #1 to Quiz #2 test material covered across Weeks 3-7. This will be in a format of Multiple

Choice Questionnaire and Programming Short Assignments. This is aimed to allow you to  receive early and continuous feedback on your performance and understanding of covered topics.

(BCom students: myBCom course points for PLO2)

Submission notes

See Detailed assessment description

Assignment submission Turnitin type

Not Applicable

General Assessment Information

As a student at UNSW you are expected to display academicintegrity in your work and interactions. Where a student breaches the UNSWStudentCode with respect to academic integrity, the University may take disciplinary action under the Student Misconduct Procedure. To assure academic integrity, you may be required to demonstrate reasoning, research and the process of constructing work submitted for assessment.

To assist you in understanding what academic integrity means, and how to ensure that you do comply with the UNSW Student Code, it is strongly recommended that you complete the Working withAcademicIntegrity module before submitting your frst assessment task. It is a free, online   self-paced Moodle module that should take about one hour to complete.

Grading Basis

Standard

Requirements to pass course

In order to pass this course students must:

• Achieve a composite mark of at least 50 out of 100

•  Engage actively in course learning activities and attempt all assessment requirements

•  Meet any additional requirements specifed in the assessment details

•  Meet the specifed attendance requirements of the course (see Schedule section)