BLILI, M. Mohamed (2024) Calibration du modèle Heston avec les méthodes Kernel PRE - Research Project, ENSTA.
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Abstract
This research project aims to calibrate the Heston model using Kernel methods, with an initial exploratory phase dedicated to neural networks. The Heston model is crucial in finance for evaluating options and capturing the dynamics of stochastic volatilities, but its precise calibration remains complex.We will start by using neural networks to obtain robust initial estimates of the model parameters. Then, we will refine these estimates using Kernel techniques, known for their flexibility and precision.
Item Type: | Thesis (PRE - Research Project) |
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Uncontrolled Keywords: | Heston, Calibration, Kernel, Neural Networks, Implied Volatility |
Subjects: | Mathematics and Applications |
ID Code: | 10014 |
Deposited By: | Mohamed BLILI |
Deposited On: | 28 août 2024 18:54 |
Dernière modification: | 28 août 2024 18:54 |
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