18 citations · 84 across the 13 of their papers we have counts for
13 papers
Doubly Robust Mean-CVaR Portfolio
Kei Nakagawa, Masaya Abe, Seiichi Kuroki
In this study, we address the challenge of portfolio optimization, a critical aspect of managing investment risks and maximizing returns. The mean-CVaR portfolio is considered a pr…
A New Initial Distribution for Quantum Generative Adversarial Networks to Load Probability Distributions
Yuichi Sano, Ryosuke Koga, Masaya Abe +1
Quantum computers are gaining attention for their ability to solve certain problems faster than classical computers, and one example is the quantum expectation estimation algorithm…
Schrödinger Risk Diversification Portfolio
Yusuke Uchiyama, Kei Nakagawa
The mean-variance portfolio that considers the trade-off between expected return and risk has been widely used in the problem of asset allocation for multi-asset portfolios. Howeve…
Fractional SDE-Net: Generation of Time Series Data with Long-term Memory
Kohei Hayashi, Kei Nakagawa
In this paper, we focus on the generation of time-series data using neural networks. It is often the case that input time-series data have only one realized (and usually irregularl…
Improving Nonparametric Classification via Local Radial Regression with an Application to Stock Prediction
Ruixing Cao, Akifumi Okuno, Kei Nakagawa +1
For supervised classification problems, this paper considers estimating the query's label probability through local regression using observed covariates. Well-known nonparametric k…
Controlling False Discovery Rates under Cross-Sectional Correlations
Junpei Komiyama, Masaya Abe, Kei Nakagawa +1
We consider controlling the false discovery rate for testing many time series with an unknown cross-sectional correlation structure. Given a large number of hypotheses, false and m…
Cross-sectional Stock Price Prediction using Deep Learning for Actual Investment Management
Masaya Abe, Kei Nakagawa
Stock price prediction has been an important research theme both academically and practically. Various methods to predict stock prices have been studied until now. The feature that…
NAPLES;Mining the lead-lag Relationship from Non-synchronous and High-frequency Data
Katsuya Ito, Kei Nakagawa
In time-series analysis, the term "lead-lag effect" is used to describe a delayed effect on a given time series caused by another time series. lead-lag effects are ubiquitous in pr…
TPLVM: Portfolio Construction by Student's -process Latent Variable Model
Yusuke Uchiyama, Kei Nakagawa
Optimal asset allocation is a key topic in modern finance theory. To realize the optimal asset allocation on investor's risk aversion, various portfolio construction methods have b…
A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy
Kei Nakagawa, Masaya Abe, Junpei Komiyama
Stock return predictability is an important research theme as it reflects our economic and social organization, and significant efforts are made to explain the dynamism therein. St…
Deep Recurrent Factor Model: Interpretable Non-Linear and Time-Varying Multi-Factor Model
Kei Nakagawa, Tomoki Ito, Masaya Abe +1
A linear multi-factor model is one of the most important tools in equity portfolio management. The linear multi-factor models are widely used because they can be easily interpreted…
Complex Valued Risk Diversification
Yusuke Uchiyama, Takanori Kadoya, Kei Nakagawa
Risk diversification is one of the dominant concerns for portfolio managers. Various portfolio constructions have been proposed to minimize the risk of the portfolio under some con…
Deep Factor Model
Kei Nakagawa, Takumi Uchida, Tomohisa Aoshima
We propose to represent a return model and risk model in a unified manner with deep learning, which is a representative model that can express a nonlinear relationship. Although de…