D'Esposito, Francesco Nicholas (A.A. 2022/2023) Revolutionizing asset pricing: exploiting deep learning for empirical insights. Tesi di Laurea in Asset pricing, Luiss Guido Carli, relatore Nicola Borri, pp. 62. [Master's Degree Thesis]

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Abstract/Index

Literature review. Deep learning methods. Machine learning vs statistical methods in forecasting. Artificial neural networks. Recurrent neural network. Long short term memory. Backpropagation rule and gradient descent method. Methodology. Data description. Algorithm setup. Hyperparameter tuning. Results. Out-of-sample performance. Long-short portfolio.

References

Bibliografia: pp. 45-48.

Thesis Type:	Master's Degree Thesis
Institution:	Luiss Guido Carli
Degree Program:	Master's Degree Programs > Master's Degree Program in Economics and Finance (LM-56)
Chair:	Asset pricing
Thesis Supervisor:	Borri, Nicola
Thesis Co-Supervisor:	Patnaik, Megha
Academic Year:	2022/2023
Session:	Autumn
Deposited by:	Alessandro Perfetti
Date Deposited:	20 May 2024 13:02
Last Modified:	20 May 2024 13:02
URI:	https://tesi.luiss.it/id/eprint/38533

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