Some Empirical Evidence On the Outliers and the Non‐Normal Distribution of Financial Ratios

So, Jacky C.

doi:10.1111/j.1468-5957.1987.tb00108.x

Cited by 50 publications

(40 citation statements)

References 28 publications

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“…A second reason why financial ratios may not be normally distributed is because the sample is not homogeneous (C. Lee, 1985;Ezzamel et al, 1987;So, 1987). Ratios have been shown to be dependent on the industry, e.g., with some industries having structurally higher current ratios than others.…”

Section: Theorymentioning

confidence: 99%

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Distributional Properties of Some Financial Ratios in Insurance

van der Heijden

2011

SSRN Journal

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This paper presents a distributional analysis of some financial ratios in the insurance industry.Although previous studies have established a reasonably good understanding of the frequency distributions of financial ratios, to date most of our knowledge has been derived from cross-sectoral studies, or from the manufacturing sector in particular. This paper aims to contribute to the literature by further applying and extending this knowledge into the financial services sector.The focus is on four key profitability ratios: the combined ratio, the expense ratio, the loss ratio and return on assets. A sample of 115 global insurance conglomerates, 64 from the United States and 55 from the EU, is used to test the effects of an outlier-removal procedure and data transformation on the normality of the distributions. The study successfully applies a modest normalisation procedure for all four ratios, highlights the dangers of conducting parametric tests on non-normal data series, and finds that lognormal transformation is beneficial just for the Return on Assets ratio.

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Section: Theorymentioning

confidence: 99%

“…Several different distribution have been proposed, including the Gamma distribution (Frecka & Hopwood, 1983), the Cauchy distribution and the Student distribution (McLeay, 1986), and the stable Pareto distribution (So, 1987). All of these are variations of the Gaussian distribution, but allow for the occurrence of more extreme values.…”

Section: Theorymentioning

confidence: 99%

Distributional Properties of Some Financial Ratios in Insurance

van der Heijden

2011

SSRN Journal

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“…This includes Box-Cox transformations (e.g., Ezzamel & Mar-Molinero, 1990;Mcleay & Omar, 2000;Watson, 1990), logarithmic transformations (e.g., Cowen & Hoffer, 1982;Deakin, 1976;Sudarsanam & Taffler, 1995), transformations by ranges (e.g., Kane et al, 1998), by square roots (e.g., Deakin, 1976;Frecka & Hopwood, 1983;Martikainen, Perttunen, Yli-Olli & Gunasekaran, 1995), by generalized risk box (e.g., Bahiraie, Azhar & Ibrahim, 2010), and other processing methods, such as weight of evidence (e.g., Nikolic, ZarkicJoksimovic, Stojanovski & Joksimovic, 2013), outlier trimming (e.g., Ezzamel & Mar-Molinero, 1990;Frecka & Hopwood, 1983;Lev & Sunder, 1979;Martikainen et al, 1995;So, 1987;Watson, 1990), and outlier winsorization (e.g., Lev & Sunder, 1979).…”

Section: Introductionmentioning

confidence: 99%

Expansion of the current methodology for the study of the short-term liquidity problems in a sector

Casas

Linares‐Mustarós

Noguer

2018

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Purpose: The aim of this work consists of defining and applying a new methodology for the calculation of short-term financial ratios that more reliably approximate the solvency of a sector. Design/methodology:We begin with a classic sector analysis and propose the creation of ratios that limit the debt repayment on an individual level and that do not imply the compensation of aggregate balances, as occurs with the current formulas of calculation. Findings:The new methodology more reliably approximates the solvency of a sector by being able to estimate with greater precision its global capacity for short-term debt repayment. Research limitations/implications:The limitations to the proposed sector ratios are the same as the limitations of the customary individual ratios. Therefore, to offer an example, the ratios do not correct the assumption that the only source of resources to meet current liabilities is made up by available and liquid assets. In other words, no new tools are proposed to include future income from sales by the companies. Practical implications:To be able to study the solvency of the different sectors that make up the economy with more uniform criteria. Social implications:The information provided by the new ratios obtained in this work proves to be relevant information in the case of wanting to determine the degree of dependence of companies in a sector on financial institutions, or in the case of wanting to determine the degree of dependence on aid in a subsidized sector. Originality/value:The proposal of new tools that go beyond the current limitations.

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“…In fact, it is a full-length mirror reflecting their state of affairs. This tool has very crucial role in decisions regarding companies' trading, investments and financing (Conner, 1973).…”

Section: Introduce the Problemmentioning

confidence: 99%

Top Companies Ranking Based on Financial Ratio with AHP-TOPSIS Combined Approach and Indices of Tehran Stock Exchange - A Comparative Study

Hosseini¹,

Ezazi²,

Heshmati³

et al. 2013

IJEF

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This paper aims to explore the relationship between ranking of the top-50 listed companies on Tehran Stock Exchange (TSE) for the years 2009-2011 in terms of their liquidity, operation, leverage and profitability ratios using combined AHP-TOPSIS approach and the ranking made by the stock exchange. Ranking of the companies on the stock exchange is done based on their state in terms of the above ratios and it serves as a criterion for decision making on investment. Using a questionnaire, views of experts, scholars and the capital market authorities on the effect of financial ratios were gathered and then using AHP-TOPSIS technique the companies were ranked based on these ratios. The obtained results from the Spearman Test show a weak correlation between the rankings based on AHP-TOPSIS approach and the ranking of the stock exchange. Finally, our results indicate that financial ratios of the top stock exchange selected companies are crucial factors in investment and ranking. This paper contributes to a signaled need for investigation on how and why financial statements of top listed companies cannot be regarded as a critical factor in ranking and decision making on investment.

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Some Empirical Evidence On the Outliers and the Non‐Normal Distribution of Financial Ratios

Cited by 50 publications

References 28 publications

Distributional Properties of Some Financial Ratios in Insurance

Distributional Properties of Some Financial Ratios in Insurance

Expansion of the current methodology for the study of the short-term liquidity problems in a sector

Top Companies Ranking Based on Financial Ratio with AHP-TOPSIS Combined Approach and Indices of Tehran Stock Exchange - A Comparative Study

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