Masaya Abe

According to our database, Masaya Abe authored at least 12 papers between 2008 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Enhanced Quantile Portfolio for Multifactor Model with Deep Learning.

Masaya Abe, Kei Nakagawa

Proceedings of the 12th International Congress on Advanced Applied Informatics, 2022

2021

Controlling False Discovery Rates Using Null Bootstrapping.

Junpei Komiyama, Masaya Abe, Kei Nakagawa, Kenichiro McAlinn

CoRR, 2021

2020

RM-CVaR: Regularized Multiple β-CVaR Portfolio.

Kei Nakagawa, Shuhei Noma, Masaya Abe

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

RIC-NN: A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy.

Kei Nakagawa, Masaya Abe, Junpei Komiyama

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

Cross-sectional Stock Price Prediction using Deep Learning for Actual Investment Management.

Masaya Abe, Kei Nakagawa

Proceedings of the ASSE 2020: Asia Service Sciences and Software Engineering Conference, 2020

How Do We Predict Stock Returns in the Cross-Section with Machine Learning?

Masaya Abe, Kei Nakagawa

Proceedings of the AICCC 2020: 2020 3rd Artificial Intelligence and Cloud Computing Conference, 2020

2019

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

Kei Nakagawa, Masaya Abe, Junpei Komiyama

CoRR, 2019

Deep Recurrent Factor Model: Interpretable Non-Linear and Time-Varying Multi-Factor Model.

Kei Nakagawa, Tomoki Ito, Masaya Abe, Kiyoshi Izumi

CoRR, 2019

Deep Learning for Multi-factor Models in Regional and Global Stock Markets.

Masaya Abe, Kei Nakagawa

Proceedings of the New Frontiers in Artificial Intelligence, 2019

2018

Deep Learning for Forecasting Stock Returns in the Cross-Section.

Masaya Abe, Hideki Nakayama

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

2016

SHARAKU: an algorithm for aligning and clustering read mapping profiles of deep sequencing in non-coding RNA processing.

Mariko Tsuchiya, Kojiro Amano, Masaya Abe, Misato Seki, Sumitaka Hase, Kengo Sato, Yasubumi Sakakibara

Bioinform., 2016

2008

Multiplicative Correction of Subject Effect as Preprocessing for Analysis of Variance.

Iku Nemoto, Masaya Abe, Makoto Kotani

IEEE Trans. Biomed. Eng., 2008