Richard Taffler

The Audit Report Under Going Concern Uncertainty: An Empirical Analysis

Abstract This study explores the value of the audit report in the context of the going concern qualification (GCQ) decision along the joint dimensions of auditor competence and independence. Likelihood of company failure, auditor switch rates, the self-fulfilling prophecy argument and audit firm size are analysed as variables potentially affecting the value of the audit report in a GCQ situation. This study focuses on the outcomes of such decisions: the presence or absence of a GCQ, for a large sample of UK quoted companies over the decade 1977–86. Our results suggest that, unless the likelihood of failure is very high, the probability of a GCQ is very low. We find some evidence in support of an association between the presence of a GCQ and auditor switching but no support for the self-fulfilling prophecy argument. In addition, smaller UK audit firms do not appear to exhibit lower GCQ rates than do large firms. There is some evidence that the issues of auditor competence and independence may be a cause fo...

Accounting Information and Analyst Stock Recommendation Decisions: A Content Analysis Approach

Abstract We explore the information set used by sell-side equity analysts in their stock recommendation decisions through content analysis of their company reports. In particular, we assess the relative importance of accounting measures compared with non-financial information items. We conclude that whereas accounting information is of fundamental importance to analysts, it is not the only, nor even the most important, source. Financial analysts are equally concerned with the firms management and strategy and its trading environment in arriving at their investment recommendations. Our results have implications in terms of enhancing the relevance of financial reporting to key user constituencies.

Empirical models for the monitoring of UK corporations

Abstract This paper has four main aims. Firstly it attempts a critical appraisal of extant UK Z-score models and seeks to assess in each case their operational utility. Next two previously unpublished models are described which address respectively (i) the need for separate models for manufacturing and distribution companies, and (ii) the utility of the jackknife discriminant approach in practice. Then developments of the technique to enhance considerably its utility to the practitioner are described. Finally a brief review of how such approaches are currently being used in the UK and by whom is provided.

Readability and Understandability: Different Measures of the Textual Complexity of Accounting Narrative

Adopts an empirical approach to demonstrate that a marked difference exists between the terms “readability” and “understandability”, suggesting that “reading ease”, as measured by formulae like FLESCH and LIX based on word and sentence complexity, conveys data which may be different to that conveyed by tests of the understandability of the message. The CLOZE method is used as a measure of understandability with audiences of differing accounting sophistication to measure the predictability of the narrative and to demonstrate inter‐group and inter‐formulae distinctions. Analysis of the results suggests that readability and understandability are different concepts and that standard setters should pay more attention to “understandability” as a desirable characteristic of accounting disclosures since there is a danger that the intended messages are of a complexity beyond the sophistication of the target audience.

Twenty Five Years of the Taffler Z-score Model: Does it Really Have Predictive Ability?

Abstract Although copious statistical failure prediction models are described in the literature, appropriate tests of whether such methodologies really work in practice are lacking. Validation exercises typically use small samples of non‐failed firms and are not true tests of ex ante predictive ability, the key issue of relevance to model users. This paper provides the operating characteristics of the well‐known Taffler (1983) UK‐based z‐score model for the first time and evaluates its performance over the 25‐year period since it was originally developed. The model is shown to have clear predictive ability over this extended time period and dominates more naïve prediction approaches. This study also illustrates the economic value to a bank of using such methodologies for default risk assessment purposes. Prima facie, such results also demonstrate the predictive ability of the published accounting numbers and associated financial ratios used in the z‐score model calculation.

Creative Accounting and Investment Analyst Response

Abstract This paper investigates the impact of window dressing on stockbroker analyst evaluation of a companys annual accounting numbers. A new methodological approach is used involving a laboratory experiment in which a large sample of experienced investment analysts drawn from five of the top London houses processes real company accounts. The research was conducted in the first half of 1990 at the end of a long bull market. The participating analysts were not overly concerned about the quality of published accounting information and creative accounting was not then viewed as a serious problem. Contrary to our prior expectations we found little evidence of window dressing adjustments being made by the subjects in general. However, those subjects who did correct were significantly more experienced. Possible explanations for our results and potential implications for capital market behaviour and information processing are discussed.

Phantastic Objects and the Financial Market's Sense of Reality: A Psychoanalytic Contribution to the Understanding of Stock Market Instability

This paper sets out to explore if standard psychoanalytic thinking based on clinical experience can illuminate instability in financial markets and its widespread human consequences. Buying, holding or selling financial assets in conditions of inherent uncertainty and ambiguity, it is argued, necessarily implies an ambivalent emotional and phantasy relationship to them. Based on the evidence of historical accounts, supplemented by some interviewing, the authors suggest a psychoanalytic approach focusing on unconscious phantasy relationships, states of mind, and unconscious group functioning can explain some outstanding questions about financial bubbles which cannot be explained with mainstream economic theories. The authors also suggest some institutional features of financial markets which may ordinarily increase or decrease the likelihood that financial decisions result from splitting off those thoughts which give rise to painful emotions. Splitting would increase the future risk of financial instability and in this respect the theory with which economic agents in such markets approach their work is important. An interdisciplinary theory recognizing and making possible the integration of emotional experience may be more useful to economic agents than the present mainstream theories which contrast rational and irrational decision‐making and model them as making consistent decisions on the basis of reasoning alone.

Financial Distress, Asset Sales, and Lender Monitoring

In the United Kingdom, the main benefit from divestitures comes from the resolution of financial distress. These sales can minimize the direct and indirect costs of bankruptcy, which accounts for the positive returns to the divesting firms shareholders.

Neural Networks and Empirical Research in Accounting

Abstract This article seeks to provide an overview of the potential role of neural network (connectionist) methodology in empirical accounting research. It highlights how the accounting task domain differs substantially from those for which neural network techniques were originally developed. A non-technical overview of neural network methodology is given, along with guidelines to help accounting researchers interested in applying these new tools to recognise the potential dangers and strengths underlying their use. An illustrative example is provided. The paper suggests research areas in accounting where neural network approaches could make a potential contribution. Explicit recommendations for prospective authors are made.

Improving the communication of accounting information through cartoon graphics

There has been limited study to date of the effectiveness of alternative methods of presenting accounting information for financial decision purposes. Explores the relative usefulness of the schematic face, compared with conventional presentation formats, for communicating the multivariate information set conveyed in a set of financial statements. Compares the ability of accounting statement users of different levels of sophistication to “predict” bankruptcy and financial health of companies on the basis of cartoon faces, accounting statements and financial ratios. Presents evidence that the schematic representations are processed more quickly than either of the more traditional methods of information presentation, and with no loss of accuracy, by all three different types of user examined. Concludes by arguing the potential generalizability of the cartoon graphic approach to more complex financial decision applications, such as those in banking and financial analysis.