Liquidity management: an empirical study of U.K. companies

Marques, Maria Manuela Farelo Athayde (1988) Liquidity management: an empirical study of U.K. companies. PhD thesis, University of Glasgow.

Full text available as:
[thumbnail of 1988marquesphd.pdf] PDF
Download (23MB)
Printed Thesis Information:


The present study is an empirically based analysis of liquidity management. The study contributes to the understanding of how U.K.-based companies handle the problem of unexpected events which have major negative implications for the expected funds flow equilibrium of the firm. In particular, the study was aimed at discovering the kind of liquidity management being implemented in practice, and the relationship between specific liquidity management practices and certain characteristics of the firm, and of its (headquarters) finance department. Evidence of the subject in the U.K. is very thin. It is therefore important to collect information on the state of the art in the practice of liquidity management in the U.K. particularly since, for the last decade, companies have been so negatively affected by the instability and unpredictability of the business environment. The study also contributes to the identification of differences between theory and practice. In this respect, it is expected that the recognition of actual differences will challenge not only the level at which companies practice liquidity management but also the teaching of the subject in current corporate finance courses.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Subjects: H Social Sciences > HF Commerce > HF5601 Accounting
Colleges/Schools: College of Social Sciences > Adam Smith Business School > Accounting and Finance
Supervisor's Name: Gray, Prof. Sidney and Keane, Prof. Simon
Date of Award: 1988
Depositing User: Elaine Ballantyne
Unique ID: glathesis:1988-2065
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 23 Aug 2010
Last Modified: 10 Dec 2012 13:51

Actions (login required)

View Item View Item


Downloads per month over past year