Australian Financial Graphs: An Empirical Study

The use of graphs to disclose financial information in corporate annual reports represents a significant dimension of financial disclosure management. This study replicates and extends previous research into financial graphs by documenting the nature and extent of graph use and departures from representational neutrality among the 1991 corporate annual reports of the top one hundred companies listed on the Australian Stock Exchange. Eighty-nine per cent of companies use graphs; the mean number is 9.4, with diversified companies using the most graphs. The most commonly graphed financial variables are sales, profit, EPS and DPS. Evidence is found that graph use is contingent upon favourable performance. In addition, material measurement distortion is found in 34 per cent of all key financial graphs. Eighty-six per cent of companies have slope parameters which depart more than 10° from the optimum, thus impairing communicative effectiveness. A range of design strategies are employed which are consistent with the adoption of an impression management schema. No persistent systematic differences between forms of distortion and industry group are found. Comparison with prior single-country studies reveals that graphs are used more extensively in Australia than in the U.S.A., the U.K. or Canada, but that there is less evidence of impression management. This latter finding is consistent with the view that there are fewer short-term and capital-market pressures in Australia.     

Managing impressions using distorted graphs of income and earnings per share: The role of memory

This study investigates the role that memory plays in interpreting and using distorted graphs that mislead the user of the financial information. It draws upon the literatures concerning memory, impression management and effective graph design. In order to examine whether reliance on memory for distorted graphs leads to different impressions of the data, we conduct an experiment in which we manipulate the type of graph distortion and whether memory of the graph is required by the decision. We present evidence that individuals receiving misleading graphs are more likely to misinterpret underlying data trends and that memory moderates the effect depending upon the type of distortion used to mislead the individual. The resulting data interpretation errors lead to more positive judgments and investment decisions than would otherwise be warranted. Thus our findings suggest that graph distortions mislead users into incorrect conclusions about the underlying data and that these interpretation errors persist in memory and affect judgments and investment decisions. We extend the prior literature, which has not considered the direct effects of graph interpretation or the effects of memory, and provide a baseline for investigating the effects of memory on impression management.     

The Impact of Graph Slope on Rate of Change Judgments in Corporate Reports

The use of graphs to disclose financial information in annual reports represents a significant dimension of financial disclosure management. Statistical graphics studies demonstrate that the accurate visual decoding of a graph is contingent upon the graph's slope parameter . This article reports two related studies into the slope parameter in a financial reporting context. A laboratory experiment indicates that sub-optimal slope parameters produce distorted judgments of corporate performance and an examination of the graphical formatting choices of 240 large U.K. companies indicates material departures from the optimal slope parameter. Policy implications are discussed.     

The Use and Representational Faithfulness of Graphs in Annual Reports: Australian Evidence

Effective communication of information using graphs depends on the graphs being constructed so that they faithfully represent the underlying data. If certain principles of graphic construction are violated, graphs will be distorted and may mislead users of financial statements. The paper develops and tests hypotheses concerning the relationship between the use and construction of graphs in the annual reports of companies and the performance of those companies.     

Earnings manipulation and similarity of annual report disclosure: Evidence from China

The Management Discussion and Analysis (MD&A) section is an important component of a company's annual report, where the management team provides a textual analysis of the company's performance for investors. Due to the existence of agency problems, management is likely to mask any earnings manipulation in order to maximise their salary, build a corporate empire or obtain more financing, which will reduce the reliability of the company's financial information. Utilising 13,679 Chinese A-share listed companies from 2008 to 2020, this study examines the correlation between management earnings manipulation and annual report MD&A similarity. We find that earnings manipulation leads to increased MD&A similarity in order to reduce the transmission of useful information and thus stymie investors. As such, we recommend that regulatory authorities should monitor the level of similarity and validity of MD&A disclosures in addition to the authenticity of numerical financial information.     

Investment appeal of small growth stocks

We examine the investment appeal of small growth stocks by addressing: (1) the extent of mean reversion in small growth stocks; and (2) the set of financial variables that uniquely and strongly identify small growth stocks with the most investment appeal. We use 22 years of data derived from Forbes' annual list of best small growth companies. Our findings indicate that the market generally overreacts in the 36 months leading up to the month of Forbes' publication. Cumulative abnormal returns decline sharply after publication of Forbes list. We also examine whether Forbes' financial filters are justified or investors should expand the financial parameters to identify stocks with better investment appeal. Our findings suggest that three out of four Forbes financial filters to screen companies performed better in the post-publication period. Small stocks performed poorly in the post-publication period when analyzed on 13 additional financial variables. Specifically, sales growth rate, cash flow growth rate, 5-year compound EPS growth rate, and net income growth rate were more than halved for the average company in the 36 months after the publication of Forbes' list. These results suggest that financial filters Forbes used to generate its list may not capture the underlying performance of small stocks. In examining the two research questions, evidence is unsettling and to some extent contrary to that provided by prior research.     

Reporting accountant appointments and accounting restatements: Evidence from UK private companies

In recent years, regulators have exempted an increasing number of companies from the requirement to appoint auditors, yet little is known about the role of the accounting profession in preparing and validating the financial statements of unaudited companies. In this paper, we examine empirically the factors associated with the appointment of reporting accountants. We then provide novel evidence on whether unaudited UK small private companies are less likely to restate their annual accounts when they have been prepared by an external accountancy firm (i.e., a reporting accountant). Based on a cross sectional analysis of a large sample of small private unaudited UK companies, we find that, in accordance with the ‘confirmation hypothesis’, larger companies that voluntarily disclose more financial information are more likely to appoint a reporting accountant. We also find that the accounts of companies with a reporting accountant are significantly less likely to be restated than those without. This result is more pronounced for companies disclosing more financial information and for those employing a larger accounting firm. Given the dwindling number of private companies opting for audits, our findings contribute to debates on the role of the accounting profession in enhancing private company financial reporting quality.     

基于CFaR模型与Logistic回归的财务困境预警研究

从现金流风险角度出发,对企业财务困境进行预警研究：首先构建一个基于企业内部环境、宏观经济政策、货币政策及财政政策等因素的CFaR模型,识别出期望现金流及风险现金流;然后以这两个指标作为预警变量,构建一个二元Logistic财务困境预警模型;最后选取27家中国证券市场中代表陷入财务困境的ST公司及配对的财务良好的非ST公司作为样本进行实证研究。结果表明,所构建的CFaR模型能较好地度量两类上市公司的现金流状况,且两类公司的期望现金流和风险现金流水平存在显著的差异;二元Logistic预警模型能较好地实现对上市公司财务风险的预警,对两类公司的预警正确率分别达到85.2%和81.5%。     

The Israeli XBRL Adoption Experience

eXtensible Business Reporting Language (XBRL) is a language for the electronic communication of business and financial data which is revolutionizing business reporting around the world. It is a tool to bridge potential language barriers and unify financial reporting. This has appeal to foreign investors, among others, who can rely on information in XBRL‐tagged financial reports to make investment decisions without having to translate financial statements from local language. In 2008, Israel required most public companies to adopt International Financial Reporting Standards (IFRS) for financial reporting and to use XBRL‐tagged reporting format, as part of an aggressive effort to make its capital markets more transparent and attractive for foreign investors. In this paper, we study all Israeli public companies and analyze the accuracy and reliability of their XBRL‐tagged financial statements that are available on MAGNA, the Israel Securities Authority's electronic system. We describe the process by which the XBRL‐based data were collected and reported. We document, categorize, and analyze deficiencies in the XBRL‐tagged filings, and inconsistencies between them and the Hebrew‐based annual reports. We observe pervasive data entry errors resulting in inaccurate XBRL‐generated financial reports, which went undetected for over one year. Further, first year XBRL reporting (in conjunction with IFRS adoption) did not increase foreign investment in the Israeli capital markets. This analysis allows us to better understand the benefits and challenges of the adoption of XBRL.     

Do Corporate Managers Know When Their Shares Are Undervalued? New Evidence Based on Actual (and Not Just Announced) Stock Buybacks

This article summarizes the findings of the authors' recent study, published in the Journal of Financial Economics, of whether public companies are able to repurchase their own shares at a discount to the market, thereby earning more than a market return on such “investments.” To the extent the answer is yes, it would suggest that management has an advantage in assessing the intrinsic value of the companies they manage. Using as their sample all 2,237 publicly traded U.S. companies that repurchased their own stock between 2004 and 2011, the authors compared the average price paid during the month to the average price at which the firm's shares traded during that month as well as three and six months after the repurchase. (All earlier studies had measured stock performance from the date of the repurchase announcements rather than from the date of the actual repurchases.) The authors' conclusion, which may come as more of a surprise to financial economists than practicing corporate executives, was that the majority of companies repurchasing their shares have in fact earned a positive return on their investment in their own stock. Perhaps the most important finding of the study, however, was that infrequent repurchasers—defined as companies that bought back their own stock four or fewer times a year—have been much more successful in buying undervalued shares than regular repurchasers. For example, when evaluated over a six‐month holding period, the annual “alpha” of infrequent repurchasers was 2.4% greater than that of frequent repurchasers—those that bought back their shares at least nine times a year. And this advantage was even more significant for companies that repurchased just once during the year—a group that recorded an alpha of 5.9%, as compared to 1.5% for monthly repurchasers. Moreover, the results were essentially the same when extended over considerably longer holding periods. For the entire sample of companies that repurchased their shares, the authors reported finding positive and significant alphas of 0.3% per month over windows ranging from three months to three years after the repurchase. But, as reported above, the infrequent repurchasers significantly outperformed frequent repurchasers over all time horizons, with differences in alpha that ranged from a low of 0.3% and to as high as 0.6% per month.     

Systemic risk contribution of banks and non-bank financial institutions across frequencies: The Australian experience

The Australian financial sector (AFS) is highly concentrated and interconnected. Besides, Australian banks' lending portfolios are dominated by residential mortgage loans, and 70% of insurance companies' revenues arise from non-policyholder sources. The AFS also performed relatively well during the global financial crisis (GFC). Given these distinctive features, in this paper, we examine the systemic risk contribution of Australian banks, insurance companies, and other financial services providers. We use a flexible copula-based delta conditional value-at-risk (ΔCoVaR) method across different frequencies. Further, we study the systemic risk determinants in a panel setting. We find that the major Australian banks are systemically more important than all other financial institutions. Systemic risk is typically higher after the GFC than in the pre-crisis period, despite the introduction of more stringent capital requirements. In addition, the short-term ΔCoVaR is significantly higher than the medium- and long-term ΔCoVaRs. Finally, institution-specific characteristics and market-wide variables explain the cross-sectional and time-series variation in systemic risk, and their explanatory power varies across frequencies.     

An Empirical Analysis of the Effect of Financial Distress on Trade Credit

This paper studies the use of supplier's trade credit by firms in financial distress. Trade credit represents a large portion of firms’ short‐term financing and plays an important role in financial distress. We find that firms in financial distress use a significantly larger amount of trade credit to substitute for alternative sources of financing. Firms that are smaller, with less market power, and with more unique products tend to use more trade credit financing when in distress. We also find that firms that significantly increase their trade payables when in financial distress, experience an additional drop of at least 11% in sales and profitability growth over the previously documented 21% average drop for financially troubled firms.     

Politician as venture capitalist: Politically-connected VCs and IPO activity in China

This study examines the impact of venture capitalists' (VC) political connections on their portfolio companies. Specifically, we use a manually-collected dataset of VCs' political connection to investigate the potential benefits and costs that politically-connected VCs bring to their portfolio companies. On the benefit side, we find that companies backed by politically-connected VCs are more likely to obtain IPO approval from the Chinese Securities Regulatory Commission (CSRC, China's counterpart to the SEC in the US). On the other hand, these VCs are more likely to acquire equity in the company at a significant discount and to invest shortly before the IPO application. In addition, we find that politically-connected VC-backed companies do not experience greater improvements in financial performance, corporate governance, or innovation output subsequent to receiving venture financing. Our results further show that companies backed by VCs with political connections are less mature and experience more underpricing at their IPO than non-politically-connected VC-backed companies. Finally, we find that, compared to non-politically-connected VCs, politically-connected VCs exit earlier after a company's IPO and that their portfolio companies experience greater post-IPO underperformance and performance volatility.     

BEYOND THE NUMBERS: MINING THE ANNUAL REPORTS FOR HIDDEN CUES INDICATIVE OF FINANCIAL STATEMENT FRAUD

Unlike previous fraud detection research, a vast majority of which has focused primarily on the use of quantitative financial information to predict fraud, in this study we examine qualitative textual content in annual reports to predict fraud and see whether there are discernible differences in the writing and presentation style between companies that committed fraud and those that did not. We believe that while numeric financial information in the annual reports can hide details of fraud, textual information relating to writing and presentation styles in such reports provides valuable clues pertaining to the existence of fraud. In this study we use the chi‐square test to analyse our data and test hypotheses about predictors of fraud that may explain linguistic feature variations in fraudulent and nonfraudulent annual reports. We provide new results on the usefulness of the qualitative content of annual reports in detecting fraud. Copyright © 2012 John Wiley & Sons, Ltd.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Location and lease intensity

U.S. firms lease assets extensively. We find that, during 1980–2011, the average U.S. firm has a lease intensity of about 40%. Or, the average firm has present and future (up to five years) rent commitments equal to 16.6% of their total assets. We investigate whether agency costs between the lessor and the lessee affect the lease intensity of firms. To do so, we examine the impact of firms' location on the use of operating leases. The main idea of our paper is that, because obtaining information and monitoring is costly for potential lessors, especially when a lessee is relatively far away from financial centers, rural firms are less likely to use operating leases. Consistent with this hypothesis, we show that rural firms tend to have lower lease intensities than similar urban and small city firms. In addition, we find that firms with higher levels of debt capacity lease less and firms that face more financial constraint lease more. Our findings are robust to industry and lease maturity controls and consistent with the existence of an agency problem associated with leasing.     

The impact of hedging on the market value of equity

We examine the annual stock performance of firms that disclose the use of derivatives to hedge over the period 1995 to 1999. We find that only 21.6% of publicly traded U.S. corporations in our sample hedged with derivative instruments over this period and their use is concentrated in the larger companies. Similar to other studies we find that when derivatives are used, interest rate and currency securities are used much more frequently than commodity products. Our sample of 1308 companies that hedge outperforms other securities by 4.3% per year on average over our sample period. This result is robust to several alternative methods of estimating abnormal returns. When we segment performance by the type of hedge used, however, we find that the over-performance is due entirely to larger firms that hedge currency. We find no abnormal returns for firms hedging either interest rates or commodities. The abnormal returns in firms hedging currency is robust to alternative models that seek to control for exchange rate fluctuations and global equity returns; however, we find no significant abnormal returns to currency hedgers when using an augmented model that controls for the role of intangible assets.     

XBRL财务报告分类标准评价——基于财务报告分类与公司偏好的报告实务的匹配性研究

XBRL是网络财务报告向高级阶段发展的技术基础,可以改进信息的编报和使用。然而,XBRL财务报告生成和应用的一个关键问题是采用的财务报告分类与公司偏好的报告实务间能否很好的匹配,匹配性差将导致信息损失。本文仅针对财务报表附注项目,将12个行业117个上市公司2005年年报中披露的项目与上交所制定的《中国上市公司信息披露分类》标准中定义的相应标记匹配,发现二者间存在着较大的差异,并且行业间的差异不显著。我们认为XBRL网络财务报告目前还不适宜全面应用,当务之急是进一步修改完善分类标准。     

Uncovering the impacts of structural similarity of financial indicators on stock returns at different quantile levels

The mining industry is the upstream industry of national economic development. In recent years, the mining financial market has rapidly developed. Stock returns have always been a hot topic for investors and researchers. There are many factors affecting stock prices, such as market supply and demand, national policies and the price fluctuations of other financial products. The most essential factor affecting stock price fluctuation is the operating condition of the listed companies that issue shares. A series of financial indicators comprehensively and systematically reflect listed companies' current earnings and future development potential. However, there are few studies on the structure of financial indicators of listed mining companies. Therefore, we take listed mining companies as the research object to explore whether the structural similarity of their financial indicators can uncover their stock returns. The research findings are as follows: (1) The strength of the structural similarity of financial indicators has a significant negative impact on annual returns, so enterprise managers should adjust their business model and attach importance to personalized development. (2) Similar media capabilities have a negative impact on companies with high annual stock returns and a positive impact on companies with low annual stock returns. (3) The impact of similar cohesion on annual returns varies across different networks and it has a positive effect on the earnings of low-returning companies in operation network. A specific analysis should be carried out according to different financial indicator networks to diversify investment.     

China's Convergence with IFRS: Analysis of Dual-listed Companies

This study investigates China's convergence towards International Financial Reporting Standards (IFRS) using generally accepted accounting principles (GAAP) differences data disclosed in AH-share companies’ annual reports from 2006 to 2017. We firstly find that 92% of AH-share companies disclosed GAAP differences in 2006, immediately prior to implementation of converged Chinese accounting standards (CAS). This ratio decreased to 88% in 2007, 58% in 2010, and 38% in 2011, respectively. After 2011, less than one third of AH companies disclosed GAAP differences. Secondly, an increasing number of AH companies (35%) have published CAS-based financial statements in Hong Kong from 2014. Thirdly, except for the first few years after 2007, the disclosed GAAP differences have dropped to a very low level; since 2010 the net profit and net assets GAAP differences ratios have been below 0.5%. Fourthly, reduction of the disclosed GAAP differences appears to be the result of efforts by Chinese standard setters and regulators, work related to the International Accounting Standards Board, or changes in China's special socio-economic environment. Distinct from word-by-word comparison between CAS and IFRS, this research shows that China has achieved its original goal, namely an enterprise applying CAS should produce financial statements that are the same as those of an enterprise that applies IFRS. Our findings provide insights regarding China's institutional evolution in terms of the country's IFRS convergence effort, which are useful for further empirical study.