Machine learningComputational Methods
Greeks via Automatic Differentiation
Automatic differentiation (AD) is a computational technique for computing derivatives (Greeks) by differentiating the computer code that computes the option price. AD avoids manual derivation of formulas and finite-difference approximations, yielding exact sensitivities with machine precision. It has become essential for real-time risk management in modern trading systems.
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Sources
- Giles, M. B. (2008). Adjoint code by automatic differentiation. Journal of Computational Finance, 12(1), 1-18. DOI: 10.21314/JCF.2008.189 ↗
- Homescu, C. (2011). Adjoints and automatic differentiation in computational finance. arXiv:1107.1188. link ↗