Computational Finance
Lecture 11- Hedging and Monte Carlo Greeks
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This course is based on the book:
"Mathematical Modeling and Computation in Finance: With Exercises and Python and MATLAB Computer Codes", by C.W. Oosterlee and L.A. Grzelak, World Scientific Publishing, 2019.
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- Codes and the slides can be found at: https://github.com/LechGrzelak/Computational-Finance-Course
- See https://quantfinancebook.com/ for more details and for additional materials.
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0:00 Introduction
3:56 Hedging with the Black-Scholes Model
36:13 Dynamic Hedging- Python Experiment
52:04 Hedging in Presence of Jumps
1:03:12 Delta, Gamma and Vega Hedging
1:17: 33 Monte Carlo Greeks: Finite Difference
1:22:33 Monte Carlo Greeks: Pathwise Sensitivities
1:38:40 Monte Carlo Greeks: Likelihood Ratio Method
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CONTENT OF THIS COURSE:
Lecture 1- Introduction and Overview of Asset Classes
Lecture 2- Stock, Options and Stochastics
Lecture 3- Option Pricing and Simulation in Python
Lecture 4- Implied Volatility
Lecture 5- Jump Processes
Lecture 6- Affine Jump Diffusion Processes
Lecture 7- Stochastic Volatility Models
Lecture 8- Fourier Transformation for Option Pricing
Lecture 9- Monte Carlo Simulation
Lecture 10- Monte Carlo Simulation of the Heston Model
***** Lecture 11- Hedging and Monte Carlo Greeks
Lecture 12- Forward Start Options and Model of Bates
Lecture 13- Exotic Derivatives
Lecture 14- Summary
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