Global Finance Analytics MSc Online
2 years
Part Time
Tuition: GBP 26,076
Paid Monthly: Pay in Instalment
Intakes: Sept 2026
Deadline: 28 Aug 2026
Course overview
The Global Finance Analytics MSc Online course from King’s College London provides students with a comprehensive understanding of investment management procedures through industry-standard techniques utilised by financial institutions.
Aspiring financial analysts will gain a profound understanding of how financial progress is propelled through contemporary investment strategies. Moreover, students will acquire extensive knowledge of contemporary methods, practices, and opportunities brought about by new developments in econometric theory.
Furthermore, not only will graduates of the Global Finance Analytics MSc Online degree attain the acumen necessary to critically analyse models and decisions, but they will also acquire the ability to implement portfolio management principles and strategies to real-world business challenges.
Global Finance Analytics MSc Online
Global Finance Analytics MSc Online
Teaching & Assessment
The Global Finance Analytics MSc Online course is assessed through 100% assignment based coursework such as presentations, case studies, essays, and research reports.
This Online finance analytics Msc course measures students’ critical awareness, comprehension and knowledge of the subjects covered throughout the course. Additionally, this Online degree also evaluates the student’s capacity to examine and implement specialised knowledge in practical scenarios.
The methods of evaluation may vary across different modules, but generally include a combination of the following components:
- Individual projects: Enables students to exhibit a thorough understanding of particular subjects.
- Collaborative presentations: Evaluates students’ capacity to collaborate with others and convey complex concepts.
- Written assignments: Comprising of:
- Essays: To highlight critical thinking and argumentative abilities.
- Dissertations: For an in-depth investigation of a selected topic.
- Research projects: To assess proficiency in conducting independent research.
Benefits
This Global Finance Analytics MSc Online course is meticulously structured, developed, and delivered by academic teams who are experts in their respective finance fields as well as in the realm of online education. Students benefit from the guidance of highly qualified teaching staff who are committed to providing exceptional education, constructive feedback, and thorough assessments.
Financial analysts will acquire practical skills that are applicable to both present and future financial situations. Moreover, the comprehensive knowledge gained will prepare graduates for sustained success and open up rewarding career paths worldwide, including areas such as risk management, investment analysis, financial modelling, and strategic decision-making.
In addition, by engaging with an international network of like-minded peers, students will gain the diverse perspectives necessary to effectively navigate the increasingly global financial environment.
Career path
The multidisciplinary design of the Global Finance Analytics MSc Online course makes it an excellent choice for a variety of professionals. Those in the finance industry who wish to elevate their careers, specialize in analytical fields, or transition into academic positions will find this program particularly fitting.
Moreover, programming enthusiasts aiming to alter their career direction towards financial services will also find this course to be a valuable opportunity. Students enrolled in this program will be equipped to meet these goals, ensuring that graduates are well-prepared for a diverse range of career paths.
- 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
Academic progression
Eligibility
Standard entry requirements:
You should have programming knowledge and meet one of the following criteria:
- A 2:1 honours degree (or above) in a business, finance or other quantitative subject area or international equivalent.
- A 2:1 honours degree (or above) in any subject area or international equivalents and at least two years’ relevant professional experience.
Degree certificates or transcripts (including evidence of quantitative subject) will be required when submitting your application. If you’re required to provide evidence of your professional experience, you should also include a CV detailing your professional experience in the finance sector.
Non-standard entry requirements
- If you don’t meet the standard entry requirements, your application may still be considered and will be assessed on a case-by-case basis. This includes situations where you are applying based on professional experience and qualifications.
- Non-standard applications will need to be supported by degree certificates or transcripts (where relevant). You’ll also need to provide a CV detailing your professional experience in the finance sector and your familiarity with (or knowledge of) coding and programming.
English language requirements
English language band: B
To study at King’s, it is essential that you can communicate in English effectively in an academic environment. You’re usually required to provide certification of your competence in English before starting your studies.
Nationals of majority English speaking countries (as defined by the UKVI) who have permanently resided in this country are not usually required to complete an additional English language test. This is also the case for applicants who have successfully completed:
- An undergraduate degree (at least three years duration) within five years of the course start date.
- A postgraduate taught degree (at least one year) within five years of the course start date.
- A PhD in a majority English-speaking country (as defined by the UKVI) within five years of the course start date.
Personal statement and supporting information
Core Modules
This module introduces the quantitative methods and financial econometrics used in banking and finance.
You’ll cover industry-standard techniques like Ordinary Least Squares estimation, Instrumental Variable estimation, Probability models, and more. Rather than simply learning about the methodologies, you’ll go further and focus on how they can be applied practically in empirical analyses.
In this module, you’ll gain a thorough understanding of investment management processes using industry-standard methods employed by banks and financial institutions.
Focusing on the practical application of finance theory, you’ll explore decision-making aspects such as investment rules, diversification, financial market theories, and risk management. By applying these to real-world scenarios, you’ll develop a profound awareness of how contemporary investment techniques drive progress in finance.
This module will introduce you to the basics of statistical programming. You’ll mostly use R and be introduced to Python. You’ll focus on the basic tasks of data loading, data preparation, data cleaning, basic statistical analysis and output visualisation.
Throughout this process, you’ll learn to write loops, simulate and analyse data, which will be useful in many subsequent modules.
This module is split into two parts. For the first half, you’ll compare financial theories (e.g., efficient markets, CAPM) with real-world data, analysing price and return behaviour in markets using statistical techniques.
The second half explores deviations, discussing popular investment strategies and assessing the potential for market outperformance. You’ll also briefly be introduced to and evaluate the relevance of modern digital assets like cryptocurrencies to traditional investors.
This module focuses on using traditional and modern computational methods for pricing and managing risk in financial derivatives. It covers simulation methods like Monte Carlo, and grid methods such as trees and Finite Differences. There is also a substantial programming component using Matlab and Python.
This module is a must for students aspiring to work with quant libraries in financial institutions, providing hands-on experience in pricing and risk management calculations.
Here, you’ll use the Statistical Programming module as a springboard for diving into more complex topics like high-dimensional regression, model selection, and forecasting. You’ll delve into state-of-the-art methodologies such as ridge regression, lasso, elastic net, and others, discussing their implications for analysing and forecasting high-dimensional data.
You’ll develop a comprehensive understanding of modern techniques, applications, and possibilities arising from recent advances in econometric theory. This knowledge will prove vital, should you opt for the research project module.
Optional Modules
This module goes beyond standard accounting practices, focusing on the practical application of financial statement analysis. You’ll explore its use in evaluating investments, assessing ongoing business value, and gauging corporate performance.
Additionally, you’ll learn how it is used in critical operations like risk identification and management. You’ll become proficient in interpreting key financial statements, ratios, and recognising potential pitfalls.
This module introduces financial derivatives to students at all levels, covering key contracts like Futures, CDOs, CDS, and some Exotic Options. Focusing on practical use, pricing methods, and arbitrage concepts, you’ll learn why and how derivatives are used in industry for hedging and speculation.
You’ll delve into various pricing approaches and applications, including the Binomial Tree Approach, the Black Scholes Model and the Monte Carlo Method for pricing financial derivatives.
This module focuses on practical risk management in the financial industry, exploring types of risks and effective mitigation tools and processes used by institutions.
It goes beyond risk identification, covering analyses of the financial system, key portfolio risks for banks, methods for managing diverse risk types, and an overview of main risk models for managers. By the end of this module, you’ll have a solid understanding of contemporary risks in the financial sector.
This module introduces Corporate Finance and Mergers and Acquisitions, led by an experienced industry practitioner in M&A advisory and Merger Arbitrage Trading. It covers Corporate Finance professionals’ responsibilities, focusing on modelling tools for valuing projects and companies.
You’ll also explore the roles of traders and portfolio managers in markets, particularly at hedge fund and asset management firms.
This module introduces econometric techniques in finance. You’ll explore empirical research on asset returns, market efficiency, and pricing models like CAPM, APT, and consumption-based CAPM. You’ll focus on applying the methodology in practical empirical analyses of real finance issues. By the end of this module, you’ll have enhanced your analytical, report-writing, and critical research evaluation skills.
This module delves into the regulatory framework of Wealth Management for both companies and individuals in modern banking. Topics include client rights, complaints, money laundering, and best execution. You’ll explore client profiling for building tailored wealth portfolios, and how they translate into investment guidelines. The module covers major asset classes, investment approaches, and wealth solutions such as insurance and pensions within the broader wealth portfolio context.
This module enhances investment decision-making and portfolio management, with practical insights and cutting-edge methodologies used by professional portfolio managers. It covers modelling asset price procedures, understanding empirical research findings, and addresses diverse issues relevant to portfolio management. By the end of this module, you’ll master portfolio management and risk concepts. Consequently, you’ll be adept at constructing advanced portfolios, navigating business challenges, critically assessing global investment selections, and using various asset pricing models.
In this module, you’ll gain both theoretical and practical insights into the financial decision-making process for investors and traders, with a focus on electronic finance. Recognising the recent developments in financial markets, you’ll develop your understanding of the psychology influencing markets, investors, and traders when analysing and evaluating market dynamics.
This module introduces high dimensional inference and modern techniques used in text analysis. You’ll cover industry-standard methods for organisations that use big data. The module will provide a clear summary of the theory for each method, but the main focus will be on applying these methods to real-world scenarios.
Course fee
Global:
- Course Fee: GBP 26,076
+VAT if applicable
Fees are determined by where applicants are currently working and residing
GBP is Great British Pounds
Academics
Refaat Kazoun
Philippe Riewer
Ajith Kumar
What our student say
Khaled Abdullah Ahmed Nusair
University of Leicester
MBA
It was an exciting, interesting journey within the University modules, staff, tutors and program. The staff at Stafford are very supportive, cooperative and professional, I am really thankful to all of them.
