Chartered Fintech Professional (CFtP) Foundation Training Module 2: Statistics and Quantitative Methods (Synchronous E-Learning)
About This Course
At the end of the 2-day module, participants will be able to:
• Understand the concept of probability distribution properties and how it can be used to model patterns of financial data
• Discuss how useful information about the financial market (population) can be obtained from a sample estimation
• Discuss the confidence interval estimate of a financial variable
• Understand steps of statistical hypothesis to test on the significance of a hypothesised financial statement
• Formulate a multiple regression equation to inference about the relationship between different factors of interest in a fintech problem
• Define Boolean Algebra and Logic gates and the conceptual framework
• Convert any number given in base A to one in base B in number systems
• Computing addition and multiplication tables associated with modular arithmetic
• Understand basic matrix operations and associated properties and how its applied in Finance, e.g., to calculate risk and expected return profiles of investment portfolios
• Understand clustering and classification concepts, cluster validation, proximity measures, and limitations of clustering, and be able to conduct cluster analysis to solve FinTech problem like customer segmentation analysis
What You'll Learn
Section 1 on “Statistics” provides an understanding of the key concepts of statistical analysis. As Fintech uses data to try to understand and predict behaviour and operation contingencies, this segment discusses 4 aspects of statistical analysis: Statistical Distribution, Sampling and Estimation, Hypothesis Testing, and Regression Analysis. Section 2 on “Quantitative Methods” discusses the rudiments of quantitative methods that facilitate understanding of computing and other data analysis applications. This is covered in five sections: Boolean Algebra and Logic Gates, Number System, Modular Arithmetic, Matrix Operation, and Clustering and Classification. Technologies such as Artificial Intelligence (AI), blockchain, and quantum computing have been widely applied to various areas in finance. Having a solid understanding of the underlying mechanisms in these technologies will give Fintech professionals a better idea of the potential and the use of emerging technologies to solve issues in the financial industry.
Entry Requirements
No prerequisites but if a participant intends to register for the Chartered Fintech Professional examination following the completion of this training course, do note that an undergraduate degree from a recognised university or equivalent professional qualification is a compulsory enrolment requirement.