Robust portfolio optimization: a categorized bibliographic review
Robust portfolio optimization refers to finding an asset allocation strategy whose behavior
under the worst possible realizations of the uncertain inputs, eg, returns and covariances, is …
under the worst possible realizations of the uncertain inputs, eg, returns and covariances, is …
Robust portfolio selection problems: a comprehensive review
A Ghahtarani, A Saif, A Ghasemi - Operational Research, 2022 - Springer
This paper reviews recent advances in robust portfolio selection problems and their
extensions, from both operational research and financial perspectives. A multi-dimensional …
extensions, from both operational research and financial perspectives. A multi-dimensional …
Robust enhanced indexation with ESG: An empirical study in the Chinese Stock Market
X Li, F Xu, K Jing - Economic Modelling, 2022 - Elsevier
The enhanced indexation constructs tracking portfolios to outperform the benchmark index
without incurring additional downside risk. Previous studies only consider optimizing the …
without incurring additional downside risk. Previous studies only consider optimizing the …
Big data-driven cognitive computing system for optimization of social media analytics
AK Sangaiah, A Goli, EB Tirkolaee… - Ieee …, 2020 - ieeexplore.ieee.org
The integration of big data analytics and cognitive computing results in a new model that can
provide the utilization of the most complicated advances in industry and its relevant decision …
provide the utilization of the most complicated advances in industry and its relevant decision …
On nonsmooth robust multiobjective optimization under generalized convexity with applications to portfolio optimization
M Fakhar, MR Mahyarinia, J Zafarani - European Journal of Operational …, 2018 - Elsevier
We introduce a new concept of generalized convexity at a given point for a family of real-
valued functions and deduce nonsmooth sufficient optimality conditions for robust (weakly) …
valued functions and deduce nonsmooth sufficient optimality conditions for robust (weakly) …
Repercussions of the Russia–Ukraine war
E Tong - International Review of Economics & Finance, 2024 - Elsevier
Using the heteroscedasticity-based estimator of Rigobon and Sack (2005) to identify daily
shocks of the Russia–Ukraine war, I assess and quantify the dynamic impact of the conflict …
shocks of the Russia–Ukraine war, I assess and quantify the dynamic impact of the conflict …
[HTML][HTML] Lstm-based deep learning model for stock prediction and predictive optimization model
AM Rather - EURO Journal on Decision Processes, 2021 - Elsevier
A new method of predicting time-series-based stock prices and a new model of an
investment portfolio based on predictions obtained is proposed here. For this purpose, a …
investment portfolio based on predictions obtained is proposed here. For this purpose, a …
[PDF][PDF] Behavioral Finance biases: A Comprehensive Review on regret approach studies in portfolio optimization
In the ever-evolving realm of finance, investors have a myriad of strategies at their disposal
to effectively and cleverly allocate their wealth in the expansive financial market. Among …
to effectively and cleverly allocate their wealth in the expansive financial market. Among …
Norm constrained minimum variance portfolios with short selling
Short selling is a wealth-building trading procedure which, when included in the portfolio
construction, not only helps increase the return on investment but also reduces the investor's …
construction, not only helps increase the return on investment but also reduces the investor's …
Stochastic portfolio optimization: A regret-based approach on volatility risk measures: An empirical evidence from The New York stock market
Portfolio optimization involves finding the ideal combination of securities and shares to
reduce risk and increase profit in an investment. To assess the impact of risk in portfolio …
reduce risk and increase profit in an investment. To assess the impact of risk in portfolio …