Global Finance Analytics MSc

Program Overview

The Global Finance Analytics MSc from King's College London is an online, part-time program that equips professionals with the skills and knowledge needed to navigate the evolving financial landscape. Combining core finance principles with advanced analytics methods, the program prepares graduates for careers in risk analysis, investment management, data science, and more. The flexible study schedule and internationally recognized degree make it an ideal choice for professionals seeking to advance their careers in finance.

Program Outline

Global Finance Analytics MSc (online, part-time) - King's

Degree Overview

Objective:

The Global Finance Analytics MSc aims to equip professionals with the cutting-edge skills and knowledge needed to navigate the rapidly evolving financial landscape shaped by AI and data analytics. The program combines core finance principles with advanced analytics methods, allowing students to delve into crucial industry topics like artificial intelligence, investment analysis, big data, and machine learning.

Key Features:

• 100% online: Offers flexibility and accessibility for students worldwide.
• Part-time: Allows students to balance their studies with professional commitments.
• 2 years duration: Provides ample time to master the necessary skills and knowledge.
• Focus on practical application: The program emphasizes translating theoretical concepts into real-world financial scenarios.
• Internationally recognized: King's College London is a prestigious institution with a global reputation for academic excellence.
• Career-oriented: Equips graduates with the skills necessary to pursue rewarding careers in various finance-related fields.

Outline

Program Structure:

• 7 Core Modules (15 credits each)
• 10 Optional Modules (15 credits each)
• Research Project (30 credits)

Core Modules:

• Quantitative Methods for Finance and Banking: Introduces industry-standard quantitative methods and financial econometrics used in the field.
• Investments: Explores investment management processes using industry-standard methods employed by banks and financial institutions.
• Introduction to Statistical Programming: Focuses on basic statistical programming using R and Python, covering data loading, preparation, cleaning, analysis, and visualization.
• Empirical Finance: Compares financial theories with real-world data, analyzing price and return behavior in markets using statistical techniques.
• Computational Finance: Focuses on using traditional and modern computational methods for pricing and managing risk in financial derivatives.
• Big Data and Deep Learning: Introduces high-dimensional inference, machine learning, and contemporary techniques like lasso and ridge regression to neural nets and support vector machines.

Optional Modules:

• Financial Statements: Explores the practical application of financial statement analysis beyond standard accounting practices.
• Financial Derivatives: Introduces key financial derivative contracts like Futures, CDOs, CDS, and Exotic Options.
• Applied Risk Management for Banking: Focuses on practical risk management techniques and tools used in the financial industry.
• Corporate Finance: Introduces Corporate Finance and Mergers and Acquisitions, focusing on valuation tools and responsibilities of professionals.
• Financial Econometrics: Introduces econometric techniques in finance, including empirical research on asset returns, market efficiency, and pricing models.
• Wealth Management: Explores the regulatory framework of Wealth Management and covers client profiling, investment portfolio construction, major asset classes, and various investment approaches.
• Global Tactical Asset Allocation: Enhances investment decision-making and portfolio management skills through practical insights and industry-standard methodologies.
• Behavioural Finance: Provides theoretical and practical insights into the psychology of financial decision-making for investors and traders.
• Research Project: Provides comprehensive training in applying data analytics to economics, banking, and finance problems, covering various techniques and exploring a wide range of topics.

Assessment

Assessments are designed to test students' knowledge, understanding, and critical awareness of the topics covered in the program. They may include projects, group presentations, written coursework (essays, dissertations, and the research project), and exams.

Teaching

The program utilizes a variety of teaching methods, including online lectures, interactive sessions, tutorials, and independent study. Students benefit from access to experienced faculty with expertise in finance, data analytics, and related fields.

Careers

The program prepares graduates for a wide range of careers in the finance industry, including:

• Risk Analyst
• Quantitative Risk Manager
• Investment Analyst
• Portfolio Manager
• Asset Manager
• Financial Data Analyst
• FinTech Analyst
• Data Scientist
• Quantitative Analyst
• Financial Engineer
• Compliance Analyst
• Regulatory Consultant

Other

• The program may be suitable for both finance professionals looking to advance their careers and individuals with a programming background seeking to transition into the financial services industry.
• Graduates will be well-equipped to face the challenges and opportunities in the evolving financial landscape.
• The program offers a valuable opportunity to gain in-demand skills and knowledge while maintaining a flexible study schedule.

Conclusion

The Global Finance Analytics MSc at King's College London provides a comprehensive and versatile program tailored to the needs of professionals in the dynamic field of finance. Through a combination of theoretical foundation and practical application, the program prepares graduates for successful careers in a variety of financial roles.