Computation Graphs for AAD and Machine Learning: Part III: Application to Derivatives Risk Sensitivities
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Computation Graphs for AAD and Machine Learning : Part III: Application to Derivatives Risk Sensitivities. / Savine, Antoine.
I: Wilmott, Nr. 106, 2020, s. 24–39.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning
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TY - JOUR
T1 - Computation Graphs for AAD and Machine Learning
T2 - Part III: Application to Derivatives Risk Sensitivities
AU - Savine, Antoine
PY - 2020
Y1 - 2020
N2 - Three articles with code, exploring the notion of computation graph, with words, mathematics and code, and application in Machine Learning and finance to compute a vast number of derivative sensitivities with spectacular speed and accuracy.
AB - Three articles with code, exploring the notion of computation graph, with words, mathematics and code, and application in Machine Learning and finance to compute a vast number of derivative sensitivities with spectacular speed and accuracy.
U2 - 10.1002/wilm.10830
DO - 10.1002/wilm.10830
M3 - Journal article
SP - 24
EP - 39
JO - Wilmott
JF - Wilmott
SN - 1540-6962
IS - 106
ER -
ID: 239521246