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Presents a case study demonstrating financial statement ratio analysis (FSRA). This analysis matches company to industry data and builds sales forecasting models. FSRA imputes forecast standards of sales and costs, and applies them to a budgeted financial statement variance analysis for the EE (electronic and electrical) industry. Develops the concept of industry base standards, integrating them into the more traditional statistical and accounting concepts of quality control standards. Provides an implementation example, and reviews possible improvements to the current methodology and approach. Uses a similar methodology to forecast the stock market value with some exceptions. Models sales and costs of an individual company and an industry based largely on aggregate industry databases. For this purpose, uses a multivariate linear trend regression analysis for the sales forecasting model. Defines and tests related hypotheses and evaluates their significance and confidence levels. For an illustration uses the EE industry and the APM company. Also demonstrates a microcomputer‐based FSRA software that speeds, facilitates, and helps to accomplish the stated objectives. The FSRA software uses industry financial statement databases, computes financial ratios and builds forecasting models.

The application of factor analysis to the area of financial ratio analysis was pioneered by Pinches, Mingo, and Caruthers (1973) in a study of U.S. industrial firms. During the last two decades numerous studies have applied the technique as a means of eliminating redundancy among financial ratios and/or reducing the number of ratios selected as a basis for further investigation to a limited but crucial subset. It is observed that all studies reported were on the manufacturing and retailing sectors. The international commercial airline sector was chosen as the subject of the present research in an attempt to study the factor groupings in a sector whose financial characteristics differ from manufacturing or retailing. Results show that factor categorization reflects the sector's financial characteristics. The study also draws conclusions on some observed differences between the empirical and theoretical ratio classification observed in the literature. The study lends support to the conclusion that factor analysis provides a useful means by which to develop and test the theoretical structure and grouping of financial ratios.

This study seeks to evaluate the stability of financial ratios across industry and over time. The sample comprises companies listed on the Stock Exchange of Singapore from 1980 to 1991 over six industry groupings. A set of 29 most commonly used ratios was selected for the study. Descriptive statistics, factor analysis and analysis of variance were performed. From the factor analysis results, eight representative ratios were identified. Analysis of variance and multiple comparisons were subsequently performed for each representative ratio to test if it is significantly different across industry and over time. The results indicate that financial ratio averages of the various industries are significantly different. This implies that the appropriate benchmark for evaluating company performance and position should be industry‐specific instead of economy based. Also, five of the representative ratios are significantly different over time and not all the industrial averages move consistently over time (i.e., interaction effects of industry and time exist). Thus, industry averages are not necessarily appropriate benchmarks for setting and evaluating performance through time.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.

The Chinese Telecoms Industry has been rapidly growing over the years since 2001. An analysis of financial performance of the three giants in this industry is very important. However, it is difficult to know how many ratios can be used best with little information loss. The paper aims to discuss this issue.

A total of 18 financial ratios were calculated based on the financial statements for three companies, namely, China Mobile, China Unicom and China Telecom for a period of 17 years. A principal component analysis was run to come up with variables with significance value above 0.5 from each component.

At the end, the authors conclude how financial performance can be analysed using 12 ratios instead of the costly analysis of too many ratios that may be complex to interpret. The results also showed that ratios are all related as they come from the same statements, hence, the authors can use a few to represent the rest with limited loss of information.

This study will help different stakeholders who are interested in the financial performance of each company by giving them a shorter way to analyse performance. It will also assist those who do financial reporting on picking the ratios which matter in reflecting the performance of their companies. The use of PCA gives unbiased ratios that are most significant in assessing performance.

The purpose of this paper is to analyze the financial structure of Italian cooperatives in the period before and during the crisis (2004-2013), in relation to two discriminating factors. At this end, it focuses on two research questions: What financial dynamics the Italian cooperatives have involved before, during and after the 2008 crisis, that is, in the decade 2004/2013? Are there statistically differences between business sectors and geographic area?

Secondary data on AIDA database have been used. The financial structure is assessed using two ratios: the financial leverage ratio and quick ratio. The final sample consists of 1,446 cooperatives. The trend and exploratory analysis, analysis of variance and Tukey-Kramer post-hoc test have been used.

The financial structure of cooperatives has not been substantially affected by the crisis in any geographic area and business sector, by virtue of resilience of their business model. Moreover, these two factors produce statistically significant differences in the financial structure of cooperatives.

The study takes into account only the cooperatives that survived the crisis, so, presumably, the strongest. Moreover, another and more ratios should be considered at the end to have a more complete view on the financial dynamics.

The literature on resilience of cooperatives is still not very rich. Moreover, this work analyses and integrates aspects and approaches that are not usually considered together.

This study aims to identify a taxonomy of financial ratios derived from financial statements prepared using International Financial Reporting Standards (IFRS). The work first empirically establishes and then statistically validates the taxonomy of financial attributes captured in financial ratios. In 2005, the European Commission required that publicly traded companies in the European Union use IFRS as the basis for financial reporting. In the same year, Australia adopted IFRS as a basis for financial reporting. Since then, 120 countries and reporting jurisdictions have adopted IFRS as the basis for financial reporting. Given that IFRS predominate in the financial reporting world, it seems essential to establish and validate IFRS-based ratio attributes. Only then can reliance upon and comparability of these ratios be warranted (Altman and Eisenbeis, 1978). Using principle component analysis, the authors empirically identify nine stable attributes (factors) for ratios drawn from IFRS-based financial statements from 84 counties. The findings provides an empirical basis to formulate testable hypotheses regarding the predictive and descriptive utility of financial ratios draw from IFRS-based financial statements.

The paper begins with a broad category of IFRS-based financial ratios, 50, found in practice and research, including income statement, balance sheet, cash flow, profitability and liquidity measures. Then, a sample of companies from the manufacturing sector is segmented using IFRS as a basis of financial statement reporting. Next, principal component analysis, a method of factor analysis, is applied to empirically identify factors and financial attributes captured in financial ratios used in research inquiry and financial analysis.

The authors find that the financial attributes captured by IFRS-based ratios go well beyond the traditional measures of profitability, liquidity and solvency. The authors identify nine factors that are interpretable and stable over the period, 2011-2015: asset relationship, asset turnover, capital structure, expense insight, fixed asset usage, inventory turnover, liquidity, profitability margin and performance return. Interestingly, the authors did not find a separate cash flow factor. Most importantly, the results corroborate that IFRS-based ratios are consistent and comparable, despite innate country differences that have been shown to influence the application, interpretation and use of IFRS.

The efforts are limited to the manufacturing sector. The financial attributes may be different in service, distribution and retail sectors. Also, limiting the effort are the ratios selected in this study. A broader range of ratios may widen the identification of unique stable factors over time.

The findings provide a basis for research and analysis efforts regarding the validity, comparability and stability of IFRS-based financial ratios. Most importantly, the results corroborate that IFRS-based ratios are consistent and comparable, despite innate country differences that have been shown to influence the application, interpretation and use of IFRS. The findings should be of interest to international and national financial reporting standard setters, investors and analysts.

An empirically evidenced classification system for IFRS-based financial ratios has yet to be determined based on a financial statements across a wide breadth of countries and reporting jurisdictions. Identification of stable interpretable factors, financial attributes, has been limited. The first is that inquiry has been limited to domestic-based, such as US Generally Accepted Accounting Principles, financial ratios. The second is inquiry has been limited to IFRS-based financial ratios within a specific country.

Ratio analysis is an excellent way of looking into a firm’s financial status. However, in performing the ratio analysis, an often underemphasized task is the selection of ratios for use. In a multi‐criteria decision‐making framework, poor quality of criteria selection, i.e. financial ratios, will consequently undermine the quality of evaluation. Aims at establishing a systematic approach for finding critical financial ratios to assist in financial analysis for the construction industry. As each sector of the industry is intrinsically unique, the set of critical ratios for different sectors will certainly vary. However, the approach for finding useful financial ratios will not distinguish itself with respect to the concerned sector rather than the purpose of analysis. The proposed approach incorporates the concept of multi‐criteria decision making and the entropy method. The approach is demonstrated in a case study in which major property development firms in Taiwan are evaluated.