Workshops
Professional lectures focus on banking and european regulations (ICAAP Stress test, Financial Derivatives), machine learning algorithms used in credit risk and sharing our practical experiences with the introduction of IFRS 9 modeling and its validation in various European banks.
Workshops are supplemented by practical examples. Listeners will develop hands-on experience manipulating real world data using a range of data science tools (including R and Python) over the two-day modeling course. Our lecturers have extensive professional and practical experiences and can also therefore help with specific questions about your current issues. Events are specified for data analysts, risk managers, marketing and any other interested people.
These courses can be implement directly in your company.
Topics
Introduction to Statistics, Machine Learning and Programming in R with Application to Finance
Financial Derivatives, Counterparty Risk and the Regulatory Requirements
Modern Machine Learning Modeling for Credit Risk Management
IFRS 9 – One Year Later
Stress Testing in the Context of ICAAP
Are you interested in one of our workshops? Please write to us at info@quantitative.cz. We will be happy to provide you with more information.
Machine Learning and Data Visualization in R with Applications in Finance
— Unsupervised learning
— Supervised learning
— Neural networks
— Reinforcement learning
— Natural language processing
— Applications in finance
— Introduction to R
— Linear programming
— Creating graphs
— Shiny app introduction
Introduction to Statistics, Machine Learning and Programming in R with Applications in Finance
— Introductory to statistics
— Measures of central tendency and variability, quantiles
— Distribution of random variable
— Point and interval estimation
— Hypothesis testing
— Regression models
— Introduction to R
— Introduction to machine learning
Financial Derivatives, Counterparty Risk and the Regulatory Requirements
— Principles of derivatives, structure and development of the derivatives market
— Forward and futures contracts
— Interest rate derivatives – FRA, futures, swaps
— Options, Black-Scholes model and volatily smile
— Interest rate options, exotic options
— Counterparty credit risk and credit valuation adjustment
Modern Machine Learning Modeling for Credit Risk Management
— Practical training in R and Python with real data
— Overview of counterparty risk estimation models
— Logistic regression, regression trees
— Principles of bagging, boosting, ensemble modeling
— Investigation real-life data modeling scenarios in a computer lab
IFRS 9 – One Year Later
— Overview of IFRS 9
— Pitfalls and difficulties associated with implementation
— Various approaches within regulatory requirements
— Risk pricing and stress testing
Stress Testing in the Context of ICAAP
— Stress testing priciples
— Basel II/III requirements
— Credit risk stress testing
— The use of models in macroeconomic
— Market risk stress testing in comparison with VaR/CVaR methodologies
— Liquidity (and other types of risk) stress testing
— Aggregation and interpretation of stress testing results