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Low‐Carbon Energy Transition and Corporate Carbon Emissions: The Critical Role of Climate Change Mitigation Policies and Institutional Context

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines the strategic efficacy of corporate low‐carbon energy transition, such as through nuclear energy adoption, as a response to decarbonization pressures. Analyzing an international sample of energy firms, we demonstrate that the relationship between this form of transition and emission reductions is not technologically ...
Bilal Ahmed Abbasi, Mushtaq Hussain Khan, Ambreen Gul, Inam Ul Haq, Muhammad Umer Azeem   +4 more
wiley   +1 more source

Reinforcement learning-driven optimal capital allocation for intelligent finance. [PDF]

PLoS One
Luo Y, Qi M, Cheng M.
europepmc   +1 more source

Benchmarking Quantum Solvers in Noisy Digital Simulations for Financial Portfolio Optimization. [PDF]

Entropy (Basel)
Shen R, Hao Z, Lee CH.
europepmc   +1 more source

Building crypto portfolios with agentic AI. [PDF]

Front Artif Intell
Giudici P, Piergallini A, Castelli A.
europepmc   +1 more source

Personality Type, Emotional Intelligence, and Successful Matching Into Emergency Medicine Residency Programs. [PDF]

Cureus
Al Balkhi AN, AlGhazzi AM, AlSaif AM, Shaikh TF, Babkair KA, AlSayed TO, Zaher MA.   +6 more
europepmc   +1 more source

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Portfolio Selection with Regularization

Asia-Pacific Journal of Operational Research, 2021
We study the Markowitz mean-variance portfolio selection model under three types of regularizations: single-norm regularizations on individual stocks, mixed-norm regularizations on stock groups, and composite regularizations that combine the single-norm and mixed-norm regularizations.
Ning Zhang, Jingnan Chen, Gengling Dai
openaire   +1 more source

Robust Portfolio Selection Problems

Mathematics of Operations Research, 2003
In this paper we show how to formulate and solve robust portfolio selection problems. The objective of these robust formulations is to systematically combat the sensitivity of the optimal portfolio to statistical and modeling errors in the estimates of the relevant market parameters.
Garud N. Iyengar, D Goldfarb
exaly   +4 more sources

Universal portfolio selection

Proceedings of the eleventh annual conference on Computational learning theory, 1998
A typical problem in portfolio selection in stock markets is that it is not clear which of the many available strategies should be used. We apply a general algorithm of prediction with expert advice (the Aggregating Algorithm) to two different idealizations of the stock market.
V. G. Vovk, Chris Watkins
openaire   +2 more sources

DYNAMIC PORTFOLIO SELECTION WITH UNCERTAINTY

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2009
How to make a prompt decision for uncertainty investment is always a key problem in financial market. In this paper, we present a new dynamic portfolio selection strategy in stock market. The investor is assumed to seek an investment strategy that will maximize his/her final wealth and minimize the total risk.
Mei Yu 0002, Hiroshi Inoue, Satoru Takahashi, Jianming Shi   +3 more
openaire   +2 more sources