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.

A Market Study of Organic and Fair Trade Coffee in Bolivia

The purpose of this research is to study the commercialization of Fairtrade and Organic coffee in the Bolivia. Fairtrade and Organic coffee are alternative trade systems designed to promote the equitable and environmentally sustainable production of coffee. However, these alternative trading systems often fail to meet these goals. The producers and environment these systems are intended to protect remain marginalized. These failures are due to a number of local institutions. In order to better understand these institutions, this research conducted interviews of various stakeholders including producers, cooperative leaders, organic/Fair Trade certifiers, government agencies and private buyers. All these stakeholders influence the success of the alternative trade systems. By better understanding how these stakeholders impact the commercialization of coffee in Bolivia; new policies can be develop to improve the outcomes of alternative trade, to benefit both producers and the environment. This is especially critical in Bolivia because of the environmentally sensitive area in which coffee is grown, the potentially damaging impact of coca on the region and, the devastating economic impact to farmers.