A nonparametric approach to pricing and hedging derivative securities via learning networks (1994)

by James M. Hutchinson , Andrew W. Lo , Tomaso Poggio
Venue:Journal of Finance
Citations:104 - 4 self

Active Bibliography

309 Regularization Theory and Neural Networks Architectures – Federico Girosi, Michael Jones, Tomaso Poggio - 1995
DERIVATIVE SECURITIES VIA – James M. Hutchinson, Andrew W. Lo, Tomaso Poggio - 1994
13 The Informational Complexity of Learning from Examples – Partha Niyogi - 1996
Application of Multilayer Feedforward Networks in the Solution of Compressible Euler Equations – Andrew J. Meade - 1998
1 Interpreting Neural-Network Models – Nathan Intrator, Orna Intrator - 1993
65 Regression Modeling in Back-Propagation and Projection Pursuit Learning – Jenq-neng Hwang, Shyh-Rong Lay, Martin Maechler, Doug Martin, Jim Schimert - 1994
43 Neural Networks for Optimal Approximation of Smooth and Analytic Functions – H. N. Mhaskar - 1996
35 Survey of Neural Transfer Functions – Wlodzislaw Duch, Norbert Jankowski - 1999
31 Generalization Bounds for Function Approximation from Scattered Noisy Data – Partha Niyogi, Federico Girosi - 1998
1 Decision Boundary and Generalization Performance of Feed-Forward Networks with Gaussian Lateral Connections – Ravi Kothari, David Ensley
39 Approximation theory of the MLP model in neural networks – Allan Pinkus - 1999
79 Priors, Stabilizers and Basis Functions: from regularization to radial, tensor and additive splines – Federico Girosi, Michael Jones, Tomaso Poggio - 1993
4 Machine learning, machine vision and the brain – Tomaso Poggio, Christian R. Shelton - 1999
Lower Bounds for Approximation of some classes of Lebesgue measurable functions by Sigmoidal Neural Networks – José L. Montaña, Cruz E. Borges
3 Quantifying generalization in linearly weighted neural networks – Martin Anthony, Sean B. Holden - 1994
194 A Theory of Networks for Approximation and Learning – Tomaso Poggio, Federico Girosi - 1989
25 A Neural Network Primer – Hervé Abdi - 1994
17 Combining Exploratory Projection Pursuit And Projection Pursuit Regression With Application To Neural Networks – Nathan Intrator - 1992
Communicated by Steven J. Nowlan Combining Exploratory Projection Pursuit and Projection Pursuit Regression with Application to Neural Networks – Nathan Intrator