Benefits of the Program

 

The CFE program will allow participants to stay current to industrial developments and access new jobs which are being created in an industry in constant evolution. It will allow certificate holders to expand their training and professional horizons globally, it will allow corporations worldwide to reach into rich body of expertise that the different levels of the certification in the program provides. The certificate curriculum builds on the highly successful Quantitative Finance Programs at Universities worldwide into the signature pro- gram of GGSJ Centre, bringing together the traditional expertise required in the financial sector with new developments that technology is introducing, such as artificial intelligence, machine learning, data science and blockchains.

The CFE Curriculum

 

Each level has:

– 24 weeks

– 10 hours per week – 240 hours

Each level consist of 24 weeks of online instruction divided into 2 modules.

The learning management system is synchronous, with live lectures, and asynchronous, which allow students to view lectures and participate in activities at their own convenience.

Level 1

 

One main driver for the development of quantitative finance is the uncertainty of factors influencing markets, in addition to the personal preferences of investors and managers, which bring randomness to the behaviour of financial markets. Financial dynamics and financial risk are therefore an interdisciplinary subject, and requires a mathematical and statistical knowledge base, so these factors are identified and measured adequately.
The learning objectives of level 1 are organized into two modules, one dealing with Applied Mathematics, the other one dealing with the foundations of finance.

APPLIED MATHEMATICS

• Linear Algebra
• Advanced Calculus
• Probability and Statistics
• Statistics and Stochastic Processes • Differential Equations
• MonteCarlo Methods
• Optimization
• Introduction to Data Science

ECONOMICS, INVESTMENTS AND FINANCE

• Economics
• Investments and Finance
• Introduction to Financial Derivatives • Ethical and Professional Standards

Level 2

Portfolio management is the art and the science of employing financial instruments and trading strategies to achieve financial objectives. Level 2 is built on two modules.

Module 1 deals with investment theory and introduces risk management, going beyond the contents of level 1 including advanced trading strategies and financial products that portfolio managers employ in the asset management sector. It introduces financial derivatives and options and elements of regulation which are fundamental in the banking sector.

Module 2 aims to provide tools to understand the complexity of financial markets and trading strategies, especially as they try to model continuous markets, the dependence between its financial components, the influence of human preferences and the impact of human actions. As a result, many practical challenges are not solvable by close-form analytical expressions and require numerical methods, which some times take the form of machine learning algorithms. Since the theory of finance is written using the language of stochastic calculus, oftentimes those problems are rooted in complex stochastic models.

 

 

FINANCE AND RISK MANAGEMENT

• Investment Portfolio Management • Option Pricing
• Risk Regulation

QUANTITATIVE METHODS

• Linear Regression Models
• Numerical Methods I
• Stochastic Calculus II
• Machine Learning Methods

Level 3

Financial innovation is highly correlated with technological innovation:

Module 1 includes some of the modern topics in advanced portfolio and risk management. It addresses risk management techniques in general, with special emphasis on market and credit risk. It presents the theory and practice of cybersecurity threats, and what it means for companies. It also includes the current trend of building investment portfolios which take into account social issues and the impact on society and the environment, through the use of ESG scores.

Module 2 deals with data, including fitting techniques, copulas and data mining techniques in a big data context. It develops a practical knowledge of artificial intelligence and computational efficiency. Blockchains and cryptocurrencies are introduced together with their technology foundations and implementations.

 

 

 

RISK, REGULATION AND COMPLIANCE

• Market and Credit Risk Management

• Financial Risks
• ESG
• Regulation and Compliance • Cybersecurity

DIGITAL TECHNOLOGIES

• Time Series Modelling • Stochastic Calculus III • Big Data & Analytics
• Deep Learning

• Blockchains
• Product Management