))
A Practical Guide to G-LSM: Improving High-Dimensional Option Pricing with Minimal Overhead
Manage episode 508418737 series 3474385
A tartalmat a HackerNoon biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a HackerNoon vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
This story was originally published on HackerNoon at: https://hackernoon.com/a-practical-guide-to-g-lsm-improving-high-dimensional-option-pricing-with-minimal-overhead.
Solving high-dimensional option pricing: G-LSM leverages Hermite polynomials and gradients to achieve a 10x accuracy boost over LSM.
Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #computational-finance, #quantitative-finance, #option-pricing, #american-options, #monte-carlo-methods, #financial-engineering, #stochastic-calculus, #high-dimensional-pricing, and more.
This story was written by: @hedging. Learn more about this writer by checking @hedging's about page, and for more stories, please visit hackernoon.com.
Solving high-dimensional option pricing: G-LSM leverages Hermite polynomials and gradients to achieve a 10x accuracy boost over LSM.
345 epizódok
Megosztás
