A comprehensive study of bankruptcy prediction: Accounting ratios, market variables, and microstructure

Bankruptcy prediction has been a fruitful area of research. Univariate analysis and discriminant analysis were the first methodologies used. While they perform relatively well at correctly classifying bankrupt and nonbankrupt firms, their predictive ability has come into question over time. Univariate analysis lacks the big picture that financial distress entails. Multivariate discriminant analysis requires stringent assumptions that are violated when dealing with accounting ratios and market variables. This has led to the use of more complex models such as neural networks. While the accuracy of the predictions has improved with the use of more technical models, there is still an important point missing. Accounting ratios are the usual discriminating variables used in bankruptcy prediction. However, accounting ratios are backward-looking variables. At best, they are a current snapshot of the firm. Market variables are forward-looking variables. They are determined by discounting future outcomes. Microstructure variables, such as the bid-ask spread, also contain important information. Insiders are privy to more information that the retail investor, so if any financial distress is looming, the insiders should know before the general public. Therefore, any model in bankruptcy prediction should include market and microstructure variables. That is the focus of this dissertation. The traditional models and the newer, more technical models were tested and compared to the previous literature by employing accounting ratios, market variables, and microstructure variables. Our findings suggest that the more technical models are preferable, and that a mix of accounting and market variables are best at correctly classifying and predicting bankrupt firms. Multi-layer perceptron appears to be the most accurate model following the results. The set of best discriminating variables includes price, standard deviation of price, the bid-ask spread, net income to sale, working capital to total assets, and current liabilities to total assets.

Accuracy of Hotel Feasibility Study Projections

Hotel feasibility studies are critical in the determination of hotel construction, sales and refinancing. Discrepancies have been reported between forecasted results and actual operating results. The author, with funding provided by the Hilton corporation, examines whether such studies under- state or overstate occupancy, average rate, and net income.

Protecting Your Assets: A Well-Defined Credit Policy Is The Key

In - Protecting Your Assets: A Well-Defined Credit Policy Is The Key – an essay by Steven V. Moll, Associate Professor, The School of Hospitality Management at Florida International University, Professor Moll observes at the outset: “Bad debts as a percentage of credit sales have climbed to record levels in the industry. The author offers suggestions on protecting assets and working with the law to better manage the business.” “Because of the nature of the hospitality industry and its traditional liberal credit policies, especially in hotels, bad debts as a percentage of credit sales have climbed to record levels,” our author says. “In 1977, hotels showing a net income maintained an average accounts receivable ratio to total sales of 3.4 percent. In 1983, the accounts receivable ratio to total sales increased to 4.1 percent in hotels showing a net income and 4.4 percent in hotels showing a net loss,” he further cites. As the professor implies, there are ways to mitigate the losses from bad credit or difficult to collect credit sales. In this article Professor Moll offers suggestions on how to do that. Moll would suggest that hotels and food & beverage operations initially tighten their credit extension policies, and on the following side, be more aggressive in their collection-of-debt pursuits. There is balance to consider here and bad credit in and of itself as a negative element is not the only reflection the profit/loss mirror would offer. “Credit managers must know what terms to offer in order to compete and afford the highest profit margin allowable,” Moll says. “They must know the risk involved with each guest account and be extremely alert to the rights and wrongs of good credit management,” he advocates. A sound profit policy can be the result of some marginal and additional credit risk on the part of the operation manager. “Reality has shown that high profits, not small credit losses, are the real indicator of good credit management,” the author reveals. “A low bad debt history may indicate that an establishment has an overly conservative credit management policy and is sacrificing potential sales and profits by turning away marginal accounts,” Moll would have you believe, and the science suggests there is no reason not to. Professor Moll does provide a fairly comprehensive list to illustrate when a manager would want to adopt a conservative credit policy. In the final analysis the design is to implement a policy which weighs an acceptable amount of credit risk against a potential profit ratio. In closing, Professor Moll does offer some collection strategies for loose credit accounts, with reference to computer and attorney participation, and brings cash and cash discounts into the discussion as well. Additionally, there is some very useful information about what debt collectors – can’t – do!