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Deep calibration of financial models: turning theory into practice

URN to cite this document:
urn:nbn:de:bvb:355-epub-478933
DOI to cite this document:
10.5283/epub.47893
Büchel, Patrick ; Kratochwil, Michael ; Nagl, Maximilian ; Rösch, Daniel
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License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 24 Aug 2021 09:09

This publication is part of the DEAL contract with Springer.


Abstract

The calibration of financial models is laborious, time-consuming and expensive, and needs to be performed frequently by financial institutions. Recently, the application of artificial neural networks (ANNs) for model calibration has gained interest. This paper provides the first comprehensive empirical study on the application of ANNs for calibration based on observed market data. We benchmark ...

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