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SSRNML & AI Methods

Historical calibration of SVJD models with deep learning

The paper suggests using deep neural networks to calibrate parameters of Stochastic Volatility Jump Diffusion models, proving to be more accurate, robust, and faster than other methods.

Featured in No. 28 on 6 Dec 2023 · 5 days after release · 1 citation today

Released
1 Dec 2023
First featured
No. 28 · 6 Dec 2023
Citations (Semantic Scholar)
1
Influential citations
0
Published in
Not yet, as far as Semantic Scholar knows
Shares when featured
2
Identifier
SSRN 4650097

Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).

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