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A simultaneous perturbation weak derivative estimator for stochastic neural networks

Flynn, Thomas; Vázquez-Abad, Felisa - In: Computational Management Science : CMS 16 (2019) 4, pp. 715-738

Persistent link: https://www.econbiz.de/10012126685

Deep learning-based least squares forward-backward stochastic differential equation solver for high-dimensional derivative pricing

Liang, Jian; Xu, Zhe; Li, Peter - In: Quantitative finance 21 (2021) 8, pp. 1309-1323

Persistent link: https://www.econbiz.de/10012608649

Conditional nonparametric variable screening by neural factor regression

Fan, Jianqing; Wang, Weining; Zhao, Yue - 2024

more generally a set of variables. Our test statistics are based on the estimated partial derivative of the regression … derivative estimator is the convolution of a deep neural network regression estimator and a smoothing kernel. We demonstrate that … necessary to smooth the partial derivative of the neural network estimator to recover the desired convergence rate for the …

Persistent link: https://www.econbiz.de/10015053806

Efficient estimation of average derivatives in NPIV models : Simulation comparisons of neural network estimators

Chen, Jiafeng; Chen, Xiaohong; Tamer, Elie T. - In: Journal of econometrics 235 (2023) 2, pp. 1848-1875

Persistent link: https://www.econbiz.de/10014471433

Predicting stock return and volatility with machine learning and econometric models: a comparative case study of the Baltic stock market

Nõu, Anders; Lapitskaya, Darya; Eratalay, M. Hakan; … - 2021

Persistent link: https://www.econbiz.de/10012694117

Inference using simulated neural moments

Creel, Michael D. - 2020 - This version: November 2020

Persistent link: https://www.econbiz.de/10012431141

Trading by estimating the quantized forward distribution

Ceffer, Attila; Fogarasi, Norbert; Levendovszky, Janos - In: Applied economics 50 (2018) 59, pp. 6397-6405

Persistent link: https://www.econbiz.de/10012063433

Financial frictions and the wealth distribution

Fernández-Villaverde, Jesús; Hurtado, Samuel; Nuño, Galo - 2019

Persistent link: https://www.econbiz.de/10012195801

Machine learning advances for time series forecasting

Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - 2020

In this paper we survey the most recent advances in supervised machine learning and highdimensional models for time series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to penalized regressions and ensemble of models. The...

Persistent link: https://www.econbiz.de/10012390030

Neural nets for indirect inference

Creel, Michael D. - 2016

Persistent link: https://www.econbiz.de/10011607329

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