Related Experiment Video
Updated: Jul 9, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
Published on: October 14, 2017
Share buybacks: a theoretical exploration of genetic algorithms and mathematical optionality
1Department of High-Tech Business and Entrepreneurship, University of Twente, Enschede, Netherlands.
Abstract:
This article exclusively formulates and presents three innovative hypotheses related to the execution of share buybacks, employing Genetic Algorithms (GAs) and mathematical optimization techniques. Drawing on the foundational contributions of scholars such as Osterrieder, Seigne, Masters, and Guéant, we articulate hypotheses that aim to bring a fresh perspective to share buyback strategies. The first hypothesis examines the potential of GAs to mimic trading schedules, the second posits the optimization of buyback execution as a mathematical problem, and the third underlines the role of optionality in improving performance. These hypotheses do not only offer theoretical insights but also set the stage for empirical examination and practical application, contributing to broader financial innovation. The article does not contain new data or extensive reviews but focuses purely on presenting these original, untested hypotheses, sparking intrigue for future research and exploration.
Jel Classification:
G00.
More Related Videos
Related Concept Videos
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Mutation, Gene Flow, and Genetic Drift
Behavioral Genetics and Its Designs
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
Genetics of Speciation
Exon Recombination
Exon shuffling follows “splice frame rules.” Each exon...
Epistasis Analysis

