The risk of bankruptcy issue has become important for Burberry and Mulberry’s investor and shareholders recently. There are several data quantitative methods, including Beaver’s, Altman’s(Z score) and qualitative method which is Argenti’s (A score) to indicate the risk of firms and help stakeholders make investment decisions in the future.
The pioneer is Beaver’s (1966) defined that failed or non-failed is as the inability of firm to pay its financial obligations as they mature. Every ratio (See Appendix1) obviously shows that Mulberry has more risk that Burberry through calculation. Compared with Mulberry, Burberry has positive cash flow, liquidity that means Burberry has an ongoing ability to generate cash that is money available to invest business in growth. Besides, a higher liquidity ratio shows company is more liquid and has better coverage of outstanding debts. company make more profit by disperse cash and more dividends could be accepted by shareholders. Burberry and Mulberry indicates that positive working capital could stimulate company to reinvest project and shareholders could obtain more dividends. However, their net income ratio has slightly fluctuation of Burberry and hardly growth of Mulberry, it may have trouble paying back creditors or bankruptcy, If a company's current assets do not exceed current liabilities.
It is important signal that Burberry’s capital structure significantly decline, the investor should evaluate whether company has enough funds to meets their debt(current) because of the wealth of shareholders. Beaver’s method benefit to stakeholders understanding because of he applied a univariate model in which a classification model was carried out separately for each ratio (Janer,2011). Conversely, it has a number of potential problems, due to too many ratio to evaluate one company, it would make people confused to classification results. Financial ratio also be restrict on different industries and size such as Moody’s company (Beaver, 1966).
Based on Beaver, Altman(1968) proposed Z score which has rigorous indicate to analysis whether a company have bankruptcy. Burberry, Mulberry has relatively safe score that is all above three, that is lower risk of bankruptcy, whereas Mulberry need to notice some unconfident number (Altman, 2001). Z scores used to compare raw scores that are taken from different tests especially when the data are at the interval of management. In addition, Z score transformation takes into account both the mean value and the variability in a set of raw scores. However, according Martin (1977) argue that Z score is addict to assumptions and outputs score do not provide intuitive interpretation for shareholder to refer. Scores are only good predictors in the short-term and it could be operated.
Argenti’s approach is qualitative factors including defects, mistakes and symptoms of corporate failure. There have big difference score between Burberry(18) and Mulberry(39.5) because of the different performance of non-financial. The advantage of A score to analysis bankruptcy of firm is that contain both financial and non-financial measure, which makes the information complete and it is essential that is includes judgement from the investigator. At same time, A score is also have disadvantages which are the investigator may include judgement always in line with the findings from financial ratios or initial findings without considering changes (Arroyave, 2018).
In summary, this study contributed to shareholder and any stakeholders to look though the financial and non financial performance by three different methods. The ability of making profit and to repay the debt gradually decline than before of Mulberry, Burberry’s revenue is dramatically increase in general. The statistical evidence supporting both univariate and multivariate techniques of predicting failure is generally impressive and often reveals considerable predictive power. Therefore, these method and information is significant for company to adjust the proportion of assets and debts and shareholders to thought whether project could be invested.
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), pp. 589-609.
Altman, E. I. (2001). Bankruptcy, credit risk, and high yield junk bonds. Malden, MA: Blackwell Publishers.
Arroyave,J. (2018). A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia. Journal of International Studies,11(1), 273-287.
Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4(, Empirical Research in Accounting: Selected Studies 1966), pp. 71-111.
Martin, D. (1977). Early warning of bank failure A logit regression approach. Journal of Banking & Finance, 1(3), 249-276.
Janer,J.(2011). Bankruptcy Prediction and its Advantages: Empirical Evidence from SMEs in the French Hospitality Industry.Vol12. pp.34-37.