This self-contained book is the second of a two-volume set providing a thorough introduction to quantitative finance, covering both theoretical and computational methods.
This volume covers numerical methods, including numerical solutions of ordinary and partial differential equations such as the Black–Scholes–Merton equation, as well as stochastic differential equations, Monte Carlo methods, estimation of implied volatility, stochastic volatility models, and Fourier transform methods for option pricing. The numerical methods are implemented in both Matlab and Python. Background in mathematics is included in the appendices and the level of familiarity with computer programming is kept to a minimum.
This self-contained book is the second of a two-volume set providing a thorough introduction to quantitative finance, covering both theoretical and computational methods.
This volume covers numerical methods, including numerical solutions of ordinary and partial differential equations such as the Black–Scholes–Merton equation, as well as stochastic differential equations, Monte Carlo methods, estimation of implied volatility, stochastic volatility models, and Fourier transform methods for option pricing. The numerical methods are implemented in both Matlab and Python. Background in mathematics is included in the appendices and the level of familiarity with computer programming is kept to a minimum.
Geon Ho Choe
numerical solution of partial differential equation Black-Scholes partial differential equation Monte Carlo integration option pricing numerical methods for option pricing Heston model Estimating volatility Arithmetic average Asian options Fourier transform for option pricing