Essays on Corporate Loans and Credit Risk

Classical asset pricing theory assumes \perfect markets" which means that nancial markets are frictionless. However, in the real world nancial frictions exists. Recently the nancial literature has focused more on these frictions and on how they a ect asset prices. This thesis contributes to the literature by providing evidence on how nancial frictions a ect pricing and trading of corporate loans. The rst chapter examines how managers of collateralized loan obligations (CLOs) trade leveraged loans and how their activity a ects the performance of the CLO. The second chapter examines how the performance of leveraged loans depends on the borrowers' relationship with its bank. The third chapter studies methodologies used to quantify how information ows between the corporate bond and the credit default swap market

Predicting distresses using deep learning of text segments in annual reports

Corporate distress models typically only employ the numerical financial variables in the firms' annual reports. We develop a model that employs the unstructured textual data in the reports as well, namely the auditors' reports and managements' statements. Our model consists of a convolutional recurrent neural network which, when concatenated with the numerical financial variables, learns a descriptive representation of the text that is suited for corporate distress prediction. We find that the unstructured data provides a statistically significant enhancement of the distress prediction performance, in particular for large firms where accurate predictions are of the utmost importance. Furthermore, we find that auditors' reports are more informative than managements' statements and that a joint model including both managements' statements and auditors' reports displays no enhancement relative to a model including only auditors' reports. Our model demonstrates a direct improvement over existing state-of-the-art models

Mitochondrial-Linked <i>De Novo</i> Pyrimidine Biosynthesis Dictates Human T-Cell Proliferation but Not Expression of Effector Molecules

T-cell activation upon antigen stimulation is essential for the continuation of the adaptive immune response. Impairment of mitochondrial oxidative phosphorylation is a well-known disruptor of T-cell activation. Dihydroorotate dehydrogenase (DHODH) is a component of the de novo synthesis of pyrimidines, the activity of which depends on functional oxidative phosphorylation. Under circumstances of an inhibited oxidative phosphorylation, DHODH becomes rate-limiting. Inhibition of DHODH is known to block clonal expansion and expression of effector molecules of activated T cells. However, this effect has been suggested to be caused by downstream impairment of oxidative phosphorylation rather than a lower rate of pyrimidine synthesis. In this study, we successfully inhibit the DHODH of T cells with no residual effect on oxidative phosphorylation and demonstrate a dose-dependent inhibition of proliferation of activated CD3(+) T cells. This block is fully rescued when uridine is supplemented. Inhibition of DHODH does not alter expression of effector molecules but results in decreased intracellular levels of deoxypyrimidines without decreasing cell viability. Our results clearly demonstrate the DHODH and mitochondrial linked pyrimidine synthesis as an independent and important cytostatic regulator of activated T cells