Taming Tail Risk: Regularized Multiple β Worst-Case CVaR Portfolio

K Nakagawa, K Ito - Symmetry, 2021 - mdpi.com
The importance of proper tail risk management is a crucial component of the investment
process and conditional Value at Risk (CVaR) is often used as a tail risk measure. CVaR is …

TPLVM: Portfolio Construction by Student's t-Process Latent Variable Model

Y Uchiyama, K Nakagawa - Mathematics, 2020 - mdpi.com
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 been …

GO-GJRSK model with application to higher order risk-based portfolio

K Nakagawa, Y Uchiyama - Mathematics, 2020 - mdpi.com
There are three distinguishing features in the financial time series, such as stock prices, are
as follows:(1) Non-normality,(2) serial correlation, and (3) leverage effect. All three points …

A Novel Mean–Variance-Entropy Portfolio with Two-Parameter Coherent Triangular Intuitionistic Fuzzy Number

X Deng, F Geng - Computational Economics, 2024 - Springer
There are a lot of fuzzy uncertainties in the real financial market, and fuzzy numbers can well
depict this phenomenon. On the one hand, compared with fuzzy numbers (only with …

Quaternion valued risk diversification

S Sugitomo, K Maeta - Entropy, 2020 - mdpi.com
Risk diversification is an important topic for portfolio managers. Various portfolio optimization
algorithms have been developed to minimize portfolio risk under certain constraints. As an …

[HTML][HTML] Bibliometric Analysis of Credit Risk Based on the Web of Science (WOS)

J Xue, Y Fan - American Journal of Industrial and Business …, 2023 - scirp.org
To clarify the evolution of credit risk research, the article searches the literature data on
credit risk research from 2007 to 2022 through the Web of Science (WOS) database and …

Schr\"{o} dinger Risk Diversification Portfolio

Y Uchiyama, K Nakagawa - arXiv preprint arXiv:2202.09939, 2022 - arxiv.org
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. However …

How do we predict stock returns in the cross-section with machine learning?

M Abe, K Nakagawa - Proceedings of the 2020 3rd Artificial Intelligence …, 2020 - dl.acm.org
Stock return prediction is one of the most important themes for investors. Until now, there are
many studies for the application of machine learning methods to predict stock returns in the …

Forecasting Nonstationary Time Series Based on Dicrete Hilbert Transform

W Ekasasmita, K Tunnisa, MT Aditya - Statistics, Optimization & …, 2024 - iapress.org
Various predictive methods have been applied to predict the value of stocks. The purpose of
this research is to implement the discrete Hilbert transform in stock returns. The ability to …

Mean Variance Complex-Based Portfolio Optimization

IA Majidah, A Rahim, M Bahri - Statistics, Optimization & Information …, 2024 - iapress.org
Mean-Variance (MV) is a method that collects several assets using appropriate weight
intending to maximize profits and to reduce risk. Stock market conditions are very volatile …