An Assessment of Managing Financial Risk in Organizations within 'Grey Zone' by Use of Key Financial Ratios

2018 ◽  
Author(s):  
Frederick Anning
Keyword(s):  
Financial Risk ◽  
Financial Ratios ◽  
Grey Zone

Financial Risk and Financial Imbalances

2020 ◽  
pp. 1-31
Author(s):  
Carlos Piñeiro Sanchez ◽  
Pablo de Llano-Monelos
Keyword(s):  
Random Sample ◽  
Financial Stability ◽  
Financial Risk ◽  
Financial Data ◽  
Financial Ratios ◽  
Diagnostic Tools ◽  
Z Score ◽  
Resource Based View ◽  
It Resources ◽  
The 1960S

The study of the financial imbalances of companies is a common topic for academics and practitioners because bankruptcy affects financial stability and modifies the investors' behavior. Since the 1960s, financial ratios have been used as diagnostic tools and also as independent variables within models aimed at quantifying firms' financial risk (e.g., Altman's Z-Score). In parallel, the strategic theory has developed theoretical constructs to explain why competitiveness is empirically heterogeneous. The resource-based view argues that companies can outperform rivals if they manage scarce, expensive, and hard-to-imitate resources. Ultimately, outperformers should be able to avoid (or overcome) financial imbalances. This chapter intends to analyze whether IT resources modify firm performance and financial risk. To do that, the authors collected data from a random sample of Galician SMEs, combining questionnaires, focused interviews, and public financial data. Hypotheses are explored by applying parametric statistical methods.

Dairy farm financial performance: firm, year, and size effects

2016 ◽  
Vol 76 (4) ◽  
pp. 532-543 ◽  
Author(s):  
Christopher A. Wolf ◽  
Mark W. Stephenson ◽  
Wayne A. Knoblauch ◽  
Andrew M. Novakovic
Keyword(s):  
Credit Risk ◽  
Financial Performance ◽  
Financial Management ◽  
Financial Risk ◽  
Dairy Farm ◽  
Herd Size ◽  
Financial Ratios ◽  
Management Tools ◽  
Content Type ◽  
Over Time

Purpose The purpose of this paper is to evaluate dairy farm financial performance over time utilizing farm financial ratios from three university business analysis programs. The evaluation includes measures of profitability, solvency, and liquidity by herd size. Design/methodology/approach Financial ratios to reflect profitability (rate of return on assets), solvency (debt to asset ratio), and liquidity (current ratio) were collected from Cornell University, Michigan State University, and the University of Wisconsin for dairy farms from 2000 to 2012. The distribution of farm financial performance using these ratios was examined over time and by herd size. Variance component methods are used to examine the percent of variation due to individual firm and industry aspects. A simple credit risk score is calculated to examine relative farm risk. Findings Dairy farm profitability performance is similar across herd sizes in poor years but larger herds realized significantly more profitability in good years. Findings were similar with respect to liquidity. Large herds consistently carried relatively more debt. Large herds’ financial performance was more uniform than across smaller herds. Larger herds had more financial risk as measured by credit risk scoring but recovered quickly to industry averages in profitable years. Originality/value The variation of dairy farm financial performance in an era of volatile milk and feed price is assessed. The results have important implications for farm financial management and benchmarking farm financial performance. In addition to helping to evaluate the efficacy of various price and income risk management tools, these results have important implications for understanding the benefits of the new federal Margin Protection Program for Dairy that is available to all US dairy farmers.

An Empirical Study on Predicting Financial Risk of Listed Companies

2010 ◽  
Vol 108-111 ◽  
pp. 1267-1271 ◽  
Author(s):  
Yan Li Chen ◽  
Li Hui Chen
Keyword(s):  
Financial Crisis ◽  
Financial Reporting ◽  
Early Warning ◽  
Financial Risk ◽  
Listed Companies ◽  
Financial Ratios ◽  
Growth Ratio ◽  
Revenue Growth ◽  
Discriminant Model ◽  
Set Up

Financial crisis early warning analysis is a matter of grave social and economic concern. It is important for enterprises, commercial banks and various investors. This is an exploratory study to determine if financial ratios of crisis companies differ from those of no crisis companies. The crisis firms (n=63) were then matched with no crisis firms on the basis of firm size, time period, and industry. Using this matched-pairs design, choose 63 listed companies, which are marked ST companies because of abnormal financial standing in Shanghai and Shenzhen in 2006, form the financial crisis samples, and choose some similar sized listed companies in same industry as matching samples, Taking the index of property liabilities ratio, audit opinion, finance lever ratio, gross property net profit ratio, sales revenue growth ratio and cash flux to current liability ratio as the final variants, set up the discriminant model by Fisher’ coefficient, conduct the case analysis of financial crisis early warning. These results provide empirical evidence of the limited ability of financial ratios to detect and predict crisis financial reporting.

scholarly journals NEW INTERNAL RATING APPROACH FOR CREDIT RISK ASSESSMENT / NAUJAS VIDAUS REITINGU MODELIS KREDITO RIZIKOS VERTINIMUI

2011 ◽  
Vol 17 (2) ◽  
pp. 369-381 ◽  
Author(s):  
Vytautas Boguslauskas ◽  
Ričardas Mileris ◽  
Rūta Adlytė
Keyword(s):  
Risk Assessment ◽  
Credit Risk ◽  
Financial Risk ◽  
Credit Ratings ◽  
Assessment Model ◽  
Financial Ratios ◽  
Mahalanobis Distances ◽  
Credit Risk Assessment ◽  
Internal Rating ◽  
Kolmogorov Smirnov

The assessment and modeling of the credit risk is one of the most important topics in the field of financial risk management. In this investigation the credit risk assessment model was developed and tested for Lithuanian companies. 20 financial ratios of the companies were calculated for each year of the 3 year period of interest. The analysis of variance (ANOVA) and Kolmogorov-Smirnov test were applied and the set of variables reduced from 60 to 25. Logistic regression was used for the classification of the companies into reliable and not reliable ones. Financial ratios, having the highest correlation to the possibility of default were selected for further investigation and several credit ratings were attributed to the companies according to these variables’ values. The average values of Mahalanobis Distances calculated for the most reliable companies were the lowest and these values increased with a decreased reliability of the company. The differences between Mahalanobis Distances of the companies having different credit ratings confirmed the reliability of the model results. Santrauka Kredito rizikos vertinimas ir modeliavimas – viena iš aktualiausiu temų, kalbant apie finansinės rizikos valdymą. Atlikto tyrimo metu buvo sukurtas kredito rizikos modelis. šis modelis išbandytas 198 Įmonių aibėje, skaičiuojant po 20 finansinių rodiklių 3 analizuojamų metu laikotarpiu. Panaudojus ANOVA metodą ir Kolmogorovo – Smirnovo statistiką, kintamųjų kiekis buvo sumažintas nuo 60 iki 25 rodiklių. Įmonįu klasifikavimui į 2 grupes: patikimus ir nepatikimus banko klientus, atsižvelgiant į jų įsipareigojimų nevykdymo tikimybę, buvo naudojama logistinė regresija. 97 proc. patikimų (nebankrutavusių) ir 82 proc. nepatikimų (bankrutavusių) įmonių suklasifikuotos teisingai. Tolimesniam tyrimui atrinkti 7 finansiniai rodikliai, kurių koreliacinis ryšys su įsipareigojimų nevykdymo tikimybe buvo didžiausias. Atsižvelgiant į šių kintamųjų reikšmės, įmonėms buvo priskirti 9 kredito reitingai. Vidutines Mahalanobio atstumu reikšmes, apskaiČiuotos patikimiausioms kompanijoms buvo mažiausios; šios reikšmės didėjo, mažejantįmonių patikimumui. Skirtingį reitingį įmonėms apskaiČiuoti Mahalanobio atstumų skirtumai, pagrindė modelio rezultatų patikimumą.

scholarly journals Justification of the list of indicators financial stability of the banking system

2018 ◽  
Vol 17 (3) ◽  
pp. 1-16
Author(s):  
Nataliia Pohorelenko
Keyword(s):  
Financial Stability ◽  
Financial Risk ◽  
Banking System ◽  
Financial Ratios ◽  
Resource Base ◽  
Synthetic Indicators ◽  
Net Interest Margin ◽  
Hierarchic Structure ◽  
The Stability ◽  
The One

The generalization of scientific approaches to the assessment of the financial stability of the banking system has demonstrated the multivariance of views on structuring and listing of financial stability indicators and has made it possible to distinguish three main ones: on the basis of macroeconomic and macro financial indicators; on the basis of separate indicators; based on synthetic indicators. It is proved that the latter is most effective since the large number and variability of financial ratios used by different authors to assess the level of financial stability of banking systems does not allow for unambiguous results. A hierarchic structure of indicators of the stability of the banking system is proposed, which is characterized by the simultaneous existence of a certain number, not ordered in a heterarchic manner. In accordance with it, the integral index of financial stability of the banking system includes subindices: stability of the NBU, stability of system banks, banks with foreign capital, banks with private capital, financial vulnerability of the banking system. The expediency of accounting for the indicators of financial risk assessment: credit, liquidity risk, interest rate, investment risk, unstable resource base risk, which are characterized by such financial ratios as part of provisions for depreciation of loans in the loan portfolio, is justified in the composition of such a synthetic indicator of the financial stability of the banking system; the norm of instant liquidity; net interest margin; part of the provision for depreciation of securities in the securities portfolio; coefficient of instability of the resource base. Also, indicators for assessing the stability of the central bank were proposed: indicators of the adequacy of reserves; indicators of the effectiveness of monetary policy; indicators of the effectiveness of foreign exchange regulation; indicators of compliance of banking supervision with the main principles of efficiency. This approach will allow taking into account all the structural components of the banking system in the process of assessing financial stability, on the one hand, and in time to identify potential threats to the loss of stability, on the other.

scholarly journals PREDICTION OF FINANCIAL DISTRESS IN THE AUTOMOTIVE COMPONENT INDUSTRY: AN APPLICATION OF ALTMAN, SPRINGATE, OHLSON, AND ZMIJEWSKI MODELS

2020 ◽  
Vol 1 (4) ◽  
pp. 606-618
Author(s):  
Hendra Pratama ◽  
Bambang Mulyana
Keyword(s):  
Panel Data ◽  
Financial Distress ◽  
Sampling Technique ◽  
Safe Zone ◽  
Financial Ratios ◽  
Grey Zone ◽  
Z Score ◽  
Automotive Component ◽  
Automotive Component Industry ◽  
Early Warnings

This study aims to identify and examine the condition of financial distress in the automotive component industry issuers in the period 2014 ~ 2018, using the Altman Z-score, Springate S-score, Ohlson O-score, and Zmijewski X-score against financial ratios as an analysis form of company management to predict the early warnings of company bankruptcy. This study uses quantitative, secondary, and panel data; while the sample uses a non-probability boring sampling technique of 11 companies. The results showed that these four models can predict financial distress by identifying each model. Altman’s model found 8 distress zone points, 16 grey zone points, and 31 safe zone points. Springate’s model found 37 points in the distress zone, and 18 points in the safe zone. Ohlson's model found 3 points in the distress zone, and 52 points in the safe zone. Zmijewski's model found only 1 point in the distress zone

scholarly journals Risk Management and Airline Sector by Using Financial Ratios - An Application

2017 ◽  
Author(s):  
Burcu Sakız
Keyword(s):  
Airline Industry ◽  
Financial Risk ◽  
Evaluation Model ◽  
Financial Ratios ◽  
Financial Status ◽  
Intense Competition ◽  
Airline Passenger ◽  
Cargo Transportation ◽  
International Airlines ◽  
Risk Evaluation Model

The growing airline transportation in the world and Turkey in recent years has increased the importance of airline passenger and cargo transportation operations and has brought intense competition in the domestic and international airlines market. Under intense competition, it is of utmost importance to capture the sustainable success of an ever-evolving and growing market by accurately assessing the financial performance and risks of businesses. In addition to the financial ratios generally used in all sectors, a number of indicators specific to the airline industry are used to assess the financial status of companies operating in the airline industry. These ratios and indicators will be calculated to compare for past periods and years, to assess risks for the future, to make forecasts, to report, to be able to see the financial status of the business concerned and to plan and make decisions in a more healthy and accurately. In this paper, after literature review, one of the most important financial risk evaluation model Altman Z’’ score is examined and an application with Turkish Airlines’ quarterly last 3 years financial data is evaluated.

scholarly journals Performance Analysis of Nigerian Brewery Industry

2018 ◽  
Vol 9 (1) ◽  
pp. 47 ◽  
Author(s):  
Lucas O. Elumah ◽  
Peter Shobayo
Keyword(s):  
Performance Analysis ◽  
Capital Structure ◽  
Financial Performance ◽  
Research Design ◽  
Financial Risk ◽  
Stock Exchange ◽  
Financial Ratios ◽  
Reasonable Amount ◽  
Ex Post ◽  
Ex Post Facto

This research attempted to assess the financial performance of the firms in the brewery industry using financial ratios. It adopted a descriptive ex-post facto research design by using brewery firms of the Nigeria Stock Exchange (NSE) from 2011-2015. The result suggests that the brewery industry is profitable and efficient in using its asset to generate profit and return it to its shareholders. Similarly, the industry financial risk is relatively low, and manager in the industry manage their stocks efficiently. This suggests that managers of firms should endeavor to reduce the amount of debt in their capital structure and manage a reasonable amount of debt in its capital structure since a high debt implies a high financial risk.

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