Markus Pelger | DeepAI

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∙ 08/29/2023

Target PCA: Transfer Learning Large Dimensional Panel Data

This paper develops a novel method to estimate a latent factor model for...

0 Junting Duan, et al. ∙

∙ 02/02/2022

Bayesian Imputation with Optimal Look-Ahead-Bias and Variance Tradeoff

Missing time-series data is a prevalent problem in finance. Imputation m...

0 Jose Blanchet, et al. ∙

∙ 06/08/2021

Deep Learning Statistical Arbitrage

Statistical arbitrage identifies and exploits temporal price differences...

0 Jorge Guijarro-Ordonez, et al. ∙

∙ 02/25/2021

Time-Series Imputation with Wasserstein Interpolation for Optimal Look-Ahead-Bias and Variance Tradeoff

Missing time-series data is a prevalent practical problem. Imputation me...

18 Jose Blanchet, et al. ∙

∙ 01/15/2021

TextGNN: Improving Text Encoder via Graph Neural Network in Sponsored Search

Text encoders based on C-DSSM or transformers have demonstrated strong p...

0 Jason Zhu, et al. ∙

∙ 03/11/2019

Deep Learning in Asset Pricing

We estimate a general non-linear asset pricing model with deep neural ne...

0 Luyang Chen, et al. ∙

∙ 09/07/2018

Change-Point Testing and Estimation for Risk Measures in Time Series

We investigate methods of change-point testing and confidence interval c...

0 Lin Fan, et al. ∙

∙ 05/09/2018

Interpretable Proximate Factors for Large Dimensions

This paper approximates latent statistical factors with sparse and easy-...

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