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A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy

A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy

Kei Nakagawa
Masaya Abe
Junpei Komiyama
ArXiv (abs)PDFHTML

Papers citing "A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy"

5 / 5 papers shown
Title
The cross-sectional stock return predictions via quantum neural network and tensor network
The cross-sectional stock return predictions via quantum neural network and tensor network
N. Kobayashi
Yoshiyuki Suimon
Koichi Miyamoto
K. Mitarai
AIFin
149
2
0
25 Apr 2023
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty
Yugo Fujimotol
Kei Nakagawa
Kentaro Imajo
Kentaro Minami
AIFin
70
3
0
31 Oct 2022
Fractional SDE-Net: Generation of Time Series Data with Long-term Memory
Fractional SDE-Net: Generation of Time Series Data with Long-term Memory
Kohei Hayashi
Kei Nakagawa
AI4TS
62
8
0
16 Jan 2022
AI in Finance: Challenges, Techniques and Opportunities
AI in Finance: Challenges, Techniques and Opportunities
LongBing Cao
AIFin
98
265
0
20 Jul 2021
Data science and AI in FinTech: An overview
Data science and AI in FinTech: An overview
LongBing Cao
Qiang Yang
Philip S. Yu
AIFin
114
95
0
10 Jul 2020