Financial Engineering and Computational Pricing Methods

Understanding how to price complex financial instruments is a critical skill in quantitative finance. This course introduces the computational frameworks necessary to value options and manage financial risk through mathematical modeling. You will gain a thorough understanding of how market variables influence pricing and how to apply numerical methods to solve real-world financial problems. The curriculum covers the transition from basic market concepts to the application of advanced stochastic models used in the industry today. What you'll learn: - Define key terminology and the structure of option and interest rate markets - Apply numerical techniques such as Fourier Transform (FT) and Fast Fourier Transform (FFT) for efficient pricing - Analyze the evolution of stock prices using Black-Merton-Scholes, Heston, and Variance Gamma models - Perform model calibration to ensure theoretical models reflect current market conditions - Practice implementing financial algorithms through written code examples and logic exercises - Understand modern risk management principles and computational efficiency in finance The course begins with essential definitions and market basics before moving into the mathematical and algorithmic techniques used by financial engineers. It is designed for beginners and requires no prior experience in quantitative finance or advanced engineering. Develop your expertise in computational finance through structured written study.