The acquisition of own shares by publicly held companies
2022
0 views
0 downloads
Advisor: Prof. Dr. Ali Paslı
Abstract (EN)
Article 22 of the Capital Market Law No. 6362 authorizes the Capital Markets Board to regulate the procedures and principles regarding the acquisition of own shares by publicly held joint-stock companies. Within the scope of this authority, the Capital Markets Board has enacted the Communiqué on Share Buybacks. The institution of the acquisition of own shares by publicly held joint-stock companies is regulated in detail in the Communiqué and is subject to certain conditions and obligations. The fundamental concepts regarding the acquisition of own shares by publicly held joint-stock companies, the reasons for and drawbacks of such acquisitions, the basic rules governing the acquisition, the conditions and exceptions, as well as the legal consequences of the acquisition constitute the main subject of this study. In this study, while examining the institution of the acquisition of own shares by publicly held joint-stock companies, the related concepts are also addressed, and, for the purpose of comparison, the provisions of the Turkish Commercial Code No. 6102 concerning the acquisition of own shares by joint-stock companies are also evaluated to a limited extent.
Author
Dr. Betül Ulusoy Birinci
How to Cite
Betül Ulusoy Birinci (Master Thesis). The acquisition of own shares by publicly held companies, 2022, İstanbul University.
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from İstanbul University
- In the covid 19 pandemic of female employees at a university hospital attitudes and affecting factors in nutrition of 9 months-6 years old children(2022)
- The perception of the right-wing movements in Turkey as to the 27 May Coup: 1960-1980(2020)
- Economic and social life in the Ottoman Empire according to the 1890 year's news of La Turquie Newspaper(2022)
- Land regime in the Umayyads period(2022)
- Merkel hücreli karsinomda tanısal ve prognostik belirteçler(2022)
- Use of machine learning methods in classification of respiratory system diseases(2021)