Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

Ligand Design for Dual Property Single Molecule Magnets

This thesis describes two different approaches for the preparation of polynuclear clusters with interesting structural, magnetic and optical properties. Firstly, exploiting p-tert-butylcalix[4]arene (TBC4) macrocycles together with selected Ln(III) ions for the assembly of emissive single molecule magnets, and secondly the preparation and coordination of a chiral mpmH ligand with selected 3d transition metal ions, working towards the discovery of chiral polynuclear clusters. In Project 1, the coordination chemistry of the TBC4 macrocycle together with Dy(III) and Tb(III) afforded two Ln6[TBC4]2 complexes that have been structurally, magnetically and optically characterized. X-ray diffraction studies reveal that both complexes contain an octahedral core of Ln6 ions capped by two fully deprotonated TBC4 macrocycles. Although the unit cells of the two complexes are very similar, the coordination geometries of their Ln(III) ions are subtly different. Variable temperature ac magnetic susceptibility studies reveal that both complexes display single molecule magnet (SMM) behaviour in zero dc field and the energy barriers and associated pre-exponential factors for each relaxation process have been determined. Low temperature solid state photoluminescence studies reveal that both complexes are emissive; however, the f-f transitions within the Dy6 complex were masked by broad emissions from the TBC4 ligand. In contrast, the Tb(III) complex displayed green emission with the spectrum comprising four sharp bands corresponding to 5D4 → 7FJ transitions (where J = 3, 4, 5 and 6), highlighting that energy transfer from the TBC4 macrocycle to the Tb(III) ion is more effective than to Dy. Examples of zero field Tb(III) SMMs are scarce in the chemical literature and the Tb6[TBC4]2 complex represents the first example of a Tb(III) dual property SMM assembled from a p-tert-butylcalix[4]arene macrocycle with two magnetically derived energy barriers, Ueff of 79 and 63 K. In Project 2, the coordination of both enantiomers of the chiral ligand, α-methyl-2-pyridinemethanol (mpmH) to Ni(II) and Co(II) afforded three polynuclear clusters that have been structurally and magnetically characterized. The first complex, a Ni4 cluster of stoichiometry [Ni4(O2CCMe3)4(mpm)4]·H2O crystallizes in a distorted cubane topology that is well known in Ni(II) cluster chemistry. The final two Co(II) complexes crystallize as a linear mixed valence trimer with stoichiometry [Co3(mpm)6]·(ClO4)2, and a Co4 mixed valence complex [Co(II)¬2Co(III)2(NO3)2(μ-mpm)4(ONO2)2], whose structural topology resembles that of a defective double cubane. All three complexes crystallize in chiral space groups and circular dichroism experiments further confirm that the chirality of the ligand has been transferred to the respective coordination complex. Magnetic susceptibility studies reveal that for all three complexes, there are competing ferro- and antiferromagnetic exchange interactions. The [Co(II)¬2Co(III)2(NO3)2(μ-mpm)4(ONO2)2] complex represents the first example of a chiral mixed valence Co4 cluster with a defective double cubane topology.

Effect of iron on reactivity of vanillin in wine models /

Phenolic compounds are important components of grapes and wines. They have been found to have important roles in grape and wine systems and properties that are beneficial for human health. Vanillin (3-methoxy-4-hydroxybenzaldehyde) is a phenolic compound coming from the oxidative degradation of lignin in oak-barrels during the aging of wine. Vanillin is an important flavour component of wine and its concentration in wine influences significantly the aroma and flavour of wine. The concentration of vanillin in wine is affected by various factors including the presence of metal ions. In this work, by using HPLC, HPLC-MS, and MS technologies, iron (III) cations were found to affect the oxidation of vanillin in a model system of wine, and the product of the oxidation was identified as divanillin. The mechanism of the redox reaction between vanillin and Fe^"^ is thought to follow that of other phenol oxidations. Increasing the concentration of Fe ^ in the model system accelerates divanillin production. The best pH condition for the divanillin production in the system is the range of 3.0 ~ 3.5. Increasing temperature from 20°C to 40°C accelerates the divanillin production. Divanillin was found to exist in three commercial red wines in this work. Keeping the storage temperature cool and decreasing the contact of grapes and wines with iron are two major measures suggested by this work in order to decrease the oxidation of vanillin during the making and aging of wine.