QUANTITATIVE FINANCE TRAINING COURSES
Essentials of Quantitative Finance
Ref: EQF-255
Learning Outcomes
- Understanding, role, and various careers in quantitative finance.
- Mastery of fundamental mathematics for financial modeling.
- Concepts of probability and introduction to stochastic calculus.
- Understanding of the Black-Scholes model for option pricing.
- Study of key interest rate forecasting models.
- Methodologies for measuring and managing financial risks.
- Practical application of VaR and CVaR and entropy pooling.
- Principles of portfolio construction and optimization.
- Concepts of Alpha, Beta, and optimization of the Sharpe ratio.
- Implementation of acquired skills in real or simulated contexts.
- The overall objective is to provide participants with essential skills in quantitative finance, enabling the rapid transposition of knowledge into professional daily life.
Who Should Attend
-
Students in Finance/Economics/Mathematics starting their studies or seeking an introduction to quantitative finance to complement their academic
curriculum.
- Young Finance Professionals looking to gain introductory yet solid foundations in quantitative finance.
- Professionals from other fields (Engineers, computer scientists, and other professionals) looking to enter or explore the financial universe and needing a basic understanding of quantitative concepts.
-
Financial institutions wishing to introduce their staff to the fundamental concepts of quantitative finance.
-
Junior Consultants and Auditors starting their careers in consulting or financial auditing and seeking to understand the basics of quantitative
techniques.
- Enlightened amateurs: Individuals interested in an introduction to financial markets and wishing to understand the basic concepts of quantitative finance.
Duration
-
2 days or 14 hours
Price
- €2550 for one participant.
- €2040 each for a group of 2 or 3 participants, only with group registration.
- €1630 each for groups of more than 3, only with group registration.
Tailored Training Solutions
- We offer the option to collaboratively develop customized programs.
- If you don't find precisely what you're looking for, we are here to assist you in constructing the perfect solution for your organization.
- Any of our training courses can be delivered just for your team.
- We can also co-create bespoke programmes, so if you can't find exactly what you need, we can help you build the right solution for your organisation.
Training Agenda
I. Introduction and Fundamentals
1. Definition of Quantitative Finance
- Understanding its objectives and applications in financial markets.
2. The Different Profiles of “Quants”
- Trading, risk management, quantitative research, and algorithm development.
3. Essential Mathematical Concepts:
- Differential and integral calculus: foundations and applications in finance.
- Linear algebra: matrices, determinants, and eigenvectors.
- Probability: fundamental laws, conditional expectation, and independence.
- Statistics: regressions, hypothesis testing, and parameter estimation.
Practical Case Study:
-
Solving a system of equations to determine the expected return of 3 distinct assets.
II. Introduction to Stochastic Calculus
1. Symmetric Random Walk, Brownian Motion, Stochastic Processes, and Itô’s Lemma
- Understanding the basics of continuous random processes.
2. Black-Scholes Model and Binomial Tree
- Explanation of the assumptions and the Black-Scholes formula.
- Methodology of binomial trees for option pricing.
Practical Case Study:
- Using Itô’s Lemma to solve the Black-Scholes partial differential equation.
- Building a binomial tree to evaluate a European option.
III. Interest Rate Models
1. Vasicek Model
- Application to bond markets and rate forecasting.
2. Cox-Ingersoll-Ross (CIR) Model
- Rate evolution under variable volatility.
3. Hull-White Model
- Incorporating deterministic terms into interest rate models.
4. Heath-Jarrow-Morton (HJM) Model
- Comprehensive modeling of the yield curve.
5. Libor Market Model (LMM)
- Applications in pricing interest rate derivatives.
Practical Case Study:
-
Using the Vasicek model to estimate interest rate evolution.
IV. Risk Management
1. Risk Measurement and Management
- Identification of different risk types (market, credit, counterparty, liquidity).
2. Value at Risk (VaR) and Conditional VaR (CVaR)
- Tools for measuring potential extreme losses.
3. Stress Testing and Scenario Analysis
- Anticipating and simulating extreme shocks in financial markets.
Practical Case Study:
-
Calculating VaR and CVaR.
V. Portfolio Management
1. Efficient Frontier and Capital Allocation Line
- Foundations of modern portfolio theory.
2. Sharpe Ratio and Optimization
- Maximizing risk-adjusted returns.
3. Capital Asset Pricing Model (CAPM) and Multi-Factor Models
- Explanation and implementation of asset valuation models.
4. Mean-Variance Optimization (MVO) and Black-Litterman Model
- Traditional and advanced approaches to portfolio optimization.
5. Introduction to “Entropy Pooling”
Practical Case Study:
- Building a portfolio of assets using various models.
VI. Pricing and Valuation
1. Exotic Options
- Understanding complex options and their volatility.
- Developing tailored hedging strategies.
2. Pricing Exotic Options
- Analytical models: binomial trees, Black-Scholes.
- Numerical models: Monte Carlo, finite differences.
3. Pricing and Valuing Credit Derivatives
- Introduction to correlation, dependence structures, and marginal distributions.
- Copula models, CDOs, and “first to default.”
- Techniques for extreme risk coverage.
Practical Case Study:
-
Using Excel-based pricers with copula models.
