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An investigation of earnings management and earnings manipulation in the UKMarinakis, Pantelis January 2011 (has links)
What causes managers to manipulate their financial statements? How best can shareholders or prospective investors, auditors, financial analysts and regulators detect earnings manipulations? Addressing these questions is of critical importance to the efficient functioning of capital markets. For an investor it can result to improved returns, for an auditor it can mean avoiding costly litigation, for an analyst it can mean avoiding a damaged reputation, and for a regulator it can lead to enhanced investor protection and fewer investment disasters. The objective of this thesis is two-fold. The first objective is to investigate the frequency and the magnitude of earnings management. Second, is to provide an analysis of the characteristics of companies discovered to manipulate earnings and the determinants of these manipulations. Exploratory interviews with the Financial Reporting Review Panel suggest that earnings manipulation usually results from escalating earnings management that after a certain stage violates accounting principles. This is analysed in a review of a series of companies publicly criticised for applying aggressive accounting practises. It is suggested that these cases involve specific accounting standards that require increased judgement from management. In order to gain a broader view of the extent that companies manage earnings, this thesis examines the distribution of earnings among thresholds such as zero earnings and earnings decreases. This thesis documents evidence of unusually low frequencies of small decreases in earnings and small losses and unusually high frequencies of small increases in earnings and small positive earnings. Additional evidence suggests that three components of earnings, cash flow from operations, changes in working capital and discretionary accruals, are used to achieve increases in earnings. Finally, this thesis presents evidence of the characteristics of firms that manipulate earnings and proposes a model for detecting earnings manipulation. Companies found to manipulate earnings appear to have lower accrual quality, declining performance, weaker corporate governance structure, weaker balance sheet and increased leverage. The output of this investigation is a scaled logistic probability model for discriminating accounting manipulations, where higher values suggest a greater probability of manipulation.
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