Course Overview

The Quantitative Finance Course equips learners with advanced mathematical and statistical techniques used in financial analysis and decision-making. The course covers key areas such as financial modelling, derivatives pricing, risk management, and algorithmic trading. By the end of this course, learners will be able to apply quantitative methods to solve complex financial problems and drive data-driven decision-making in financial markets.

Prerequisites

  • A strong foundation in mathematics, statistics, and probability.
  • Basic programming skills and familiarity with financial markets.

Target Audience

This course is ideal for finance professionals, quantitative analysts, and individuals looking to deepen their knowledge of quantitative methods in financial decision-making. It is also suitable for those involved in risk management, trading, and financial modelling.

Course Highlights

  • Master the application of quantitative methods in financial analysis.
  • Learn to build and use financial models for pricing, forecasting, and risk assessment.
  • Explore algorithmic trading strategies and backtesting techniques.
  • Hands-on experience with data analysis tools and real-world financial scenarios.

Course Objectives

By the end of this course, learners will be able to:

  1. Apply advanced quantitative methods to build and evaluate financial models.
  2. Develop pricing models for derivatives using tools like Black-Scholes and binomial option pricing.
  3. Measure and manage financial risks using techniques such as Value at Risk (VaR) and Monte Carlo simulations.
  4. Design and backtest algorithmic trading strategies with real-world data.
  5. Implement advanced statistical methods for market analysis and portfolio optimisation.

 

Course Outline

Instructional Methods: Demonstration of key quantitative concepts through interactive modelling, practice exercises with financial data, and group discussions on financial applications.

Topics Covered:

  • The role of quantitative methods in financial analysis.
  • Introduction to financial modelling and key statistical techniques.

Instructional Methods: Hands-on modelling exercises, group projects on derivatives pricing, and demonstration of key pricing models like Black-Scholes.

Topics Covered:

  • Building financial models for derivatives pricing.
  • Application of the Black-Scholes model and binomial option pricing models.

Instructional Methods: Practical exercises in risk measurement, scenario analysis, and live demonstrations of risk models like Value at Risk (VaR).

Topics Covered:

  • Quantitative techniques for measuring and managing financial risks.
  • Using Value at Risk (VaR), stress testing, and Monte Carlo simulations.

Instructional Methods: Live demonstration of algorithmic trading strategies, hands-on exercises in building trading algorithms, and group discussions on backtesting techniques.

Topics Covered:

  • Introduction to algorithmic trading strategies and their development.
  • Backtesting trading strategies using historical market data.

Instructional Methods: Demonstrations of advanced statistical methods, practice exercises with real-world market data, and peer feedback sessions on advanced model applications.

Topics Covered:

  • Advanced statistical methods for market analysis and forecasting.
  • Quantitative techniques for portfolio optimisation and performance measurement.

Certification

A certificate of completion will be awarded upon successful completion of the course.

Course Fees

$788 $488