User profiles for Jun-Ya Gotoh
 | Jun-ya GotohDepartment of Data Science for Business Innovation, Chuo University Verified email at kc.chuo-u.ac.jp Cited by 1566 |
DC formulations and algorithms for sparse optimization problems
J Gotoh, A Takeda, K Tono - Mathematical Programming, 2018 - Springer
We propose a DC (Difference of two Convex functions) formulation approach for sparse
optimization problems having a cardinality or rank constraint. With the largest-k norm, an exact …
optimization problems having a cardinality or rank constraint. With the largest-k norm, an exact …
Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios
Index tracking is a passive investment strategy in which a fund (eg, an ETF: exchange traded
fund) manager purchases a set of assets to mimic a market index. The tracking error, ie, the …
fund) manager purchases a set of assets to mimic a market index. The tracking error, ie, the …
Third degree stochastic dominance and mean-risk analysis
J Gotoh, H Konno - Management science, 2000 - pubsonline.informs.org
In their recent article, Ogryczak and Ruszczyński (1999) proved that those portfolios associated
with the efficient frontiers generated by mean-lower semi-standard deviation model and …
with the efficient frontiers generated by mean-lower semi-standard deviation model and …
[HTML][HTML] Robust empirical optimization is almost the same as mean–variance optimization
We formulate a distributionally robust optimization problem where the deviation of the
alternative distribution is controlled by a ϕ -divergence penalty in the objective, and show that a …
alternative distribution is controlled by a ϕ -divergence penalty in the objective, and show that a …
Calibration of distributionally robust empirical optimization models
We study the out-of-sample properties of robust empirical optimization problems with smooth
φ -divergence penalties and smooth concave objective functions, and we develop a theory …
φ -divergence penalties and smooth concave objective functions, and we develop a theory …
Newsvendor solutions via conditional value-at-risk minimization
In this paper, we consider the minimization of the conditional value-at-risk (CVaR), a most
preferable risk measure in financial risk management, in the context of the well-known single-…
preferable risk measure in financial risk management, in the context of the well-known single-…
Multi-period portfolio selection using kernel-based control policy with dimensionality reduction
This paper studies a nonlinear control policy for multi-period investment. The nonlinear strategy
we implement is categorized as a kernel method, but solving large-scale instances of the …
we implement is categorized as a kernel method, but solving large-scale instances of the …
On the role of norm constraints in portfolio selection
J Gotoh, A Takeda - Computational Management Science, 2011 - Springer
Several optimization approaches for portfolio selection have been proposed in order to
alleviate the estimation error in the optimal portfolio. Among them are the norm-constrained …
alleviate the estimation error in the optimal portfolio. Among them are the norm-constrained …
Maximization of the ratio of two convex quadratic functions over a polytope
JY Gotoh, H Konno - Computational Optimization and Applications, 2001 - Springer
In this paper, we will develop an algorithm for solving a quadratic fractional programming
problem which was recently introduced by Lo and MacKinlay to construct a maximal …
problem which was recently introduced by Lo and MacKinlay to construct a maximal …
Efficient DC algorithm for constrained sparse optimization
K Tono, A Takeda, J Gotoh - arXiv preprint arXiv:1701.08498, 2017 - arxiv.org
We address the minimization of a smooth objective function under an $\ell_0$-constraint
and simple convex constraints. When the problem has no constraints except the $\ell_0$-…
and simple convex constraints. When the problem has no constraints except the $\ell_0$-…