Managing credit risk and the cost of equity with machine learning techniques

Credit risks and the cost of equity can influence market participants' activities in many ways. Providing in-depth analysis can help participants reduce potential costs and make profitable strategies. This kind of study is usually armed with conventional statistical models built with researchers' knowledge. However, with the advancement of technology, a massive amount of financial data increasing in volume, subjectivity, and heterogeneity becomes challenging to process conventionally. Machine learning (ML) techniques have been utilised to handle this difficulty in real-life applications. This PhD thesis consists of three major empirical essays. We employ state-of-art machine learning techniques to predict peer-to-peer (P2P) lending default risk, P2P lending decisions, and Environmental, Social, Corporate Governance (ESG) effects on firms' cost of equity. In the era of financial technology, P2P lending has gained considerable attention among academics and market participants. In the first essay (Chapter 2), we investigate the determinants of P2P lending default prediction in relation to borrowers' characteristics and credit history. Applying machine learning techniques, we document substantial predictive ability compared with the benchmark logit model. Further, we find that the LightGBM has superior predictive power and outperforms all other models in all out-of-sample predictions. Finally, we offer insights into different levels of uncertainty in P2P loan groups and the value of machine learning in credit risk mitigation of P2P loan providers. Macroeconomic impact on funding decisions or lending standards reflects the risk-taking behaviour of market participants. It has been widely discussed by academics. But in the era of financial technology, it leaves a gap in the evidence of lending standards change in a FinTech nonbank financial organisation. The second essay (Chapter 3) aims to fill the gap by introducing loan-level and macroeconomic variables into the predictive models to estimate the P2P loan funding decision. Over 12 million empirical instances are under study while big data techniques, including text mining and five state-of-the-art approaches, are utilised. We note that macroeconomic condition affects individual risk-taking and reaching-for-yield behaviour. Finally, we offer insight into macroeconomic impact in terms of different levels of uncertainty in different P2P loan application groups. In the third essay (Chapter 4), we use up-to-date machine learning techniques to provide new evidence for the impact of ESG on the cost of equity. Using 15,229 firm-year observations from 51 different countries over the past 18 years, we document negative causal effects on the cost of equity. In addition, we uncover non-linear effects because the level of ESG effects on the equity cost decrease with the enhancements of ESG performance. Furthermore, we note the heterogeneity in ESG effects in different regions by breaking down our sample. Finally, we find that global crises change the sensitivity of the equity cost towards ESG, and the change varies in areas

Somatic mutation of the cohesin complex subunit confers therapeutic vulnerabilities in cancer

A synthetic lethality-based strategy has been developed to identify therapeutic targets in cancer harboring tumor-suppressor gene mutations, as exemplified by the effectiveness of poly ADP-ribose polymerase (PARP) inhibitors in BRCA1/2-mutated tumors. However, many synthetic lethal interactors are less reliable due to the fact that such genes usually do not perform fundamental or indispensable functions in the cell. Here, we developed an approach to identifying the "essential lethality" arising from these mutated/deleted essential genes, which are largely tolerated in cancer cells due to genetic redundancy. We uncovered the cohesion subunit SA1 as a putative synthetic-essential target in cancers carrying inactivating mutations of its paralog, SA2. In SA2-deficient Ewing sarcoma and bladder cancer, further depletion of SA1 profoundly and specifically suppressed cancer cell proliferation, survival, and tumorigenic potential. Mechanistically, inhibition of SA1 in the SA2-mutated cells led to premature chromatid separation, dramatic extension of mitotic duration, and consequently, lethal failure of cell division. More importantly, depletion of SA1 rendered those SA2-mutated cells more susceptible to DNA damage, especially double-strand breaks (DSBs), due to reduced functionality of DNA repair. Furthermore, inhibition of SA1 sensitized the SA2-deficient cancer cells to PARP inhibitors in vitro and in vivo, providing a potential therapeutic strategy for patients with SA2-deficient tumors

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

MAL2 drives immune evasion in breast cancer by suppressing tumor antigen presentation

Immune evasion is a pivotal event in tumor progression. To eliminate human cancer cells, current immune checkpoint therapy is set to boost CD8+ T cell-mediated cytotoxicity. However, this action is eventually dependent on the efficient recognition of tumor-specific antigens via T cell receptors. One primary mechanism by which tumor cells evade immune surveillance is to downregulate their antigen presentation. Little progress has been made toward harnessing potential therapeutic targets for enhancing antigen presentation on the tumor cell. Here, we identified MAL2 as a key player that determines the turnover of the antigen-loaded MHC-I complex and reduces the antigen presentation on tumor cells. MAL2 promotes the endocytosis of tumor antigens via direct interaction with the MHC-I complex and endosome-associated RAB proteins. In preclinical models, depletion of MAL2 in breast tumor cells profoundly enhanced the cytotoxicity of tumor-infiltrating CD8+ T cells and suppressed breast tumor growth, suggesting that MAL2 is a potential therapeutic target for breast cancer immunotherapy

Atractylenolide I enhances responsiveness to immune checkpoint blockade therapy by activating tumor antigen presentation

One of the primary mechanisms of tumor cell immune evasion is the loss of antigenicity, which arises due to lack of immunogenic tumor antigens as well as dysregulation of the antigen processing machinery. In a screen for small-molecule compounds from herbal medicine that potentiate T cell–mediated cytotoxicity, we identified atractylenolide I (ATT-I), which substantially promotes tumor antigen presentation of both human and mouse colorectal cancer (CRC) cells and thereby enhances the cytotoxic response of CD8+ T cells. Cellular thermal shift assay (CETSA) with multiplexed quantitative mass spectrometry identified the proteasome 26S subunit non–ATPase 4 (PSMD4), an essential component of the immunoproteasome complex, as a primary target protein of ATT-I. Binding of ATT-I with PSMD4 augments the antigen-processing activity of immunoproteasome, leading to enhanced MHC-I–mediated antigen presentation on cancer cells. In syngeneic mouse CRC models and human patient–derived CRC organoid models, ATT-I treatment promotes the cytotoxicity of CD8+ T cells and thus profoundly enhances the efficacy of immune checkpoint blockade therapy. Collectively, we show here that targeting the function of immunoproteasome with ATT-I promotes tumor antigen presentation and empowers T cell cytotoxicity, thus elevating the tumor response to immunotherapy

Study of over-examination on tire induced by pressure correction process in flywheel tests

In this paper, the strain energy density (SED) is used to study the over-examination to tire in flywheel test induced by pressure correction process. Flywheel test is the main method for evaluating tire durability, which cannot be measured on flat ground due to the variable road conditions. "Pressure Correction" is a necessary step in flywheel tests, but this process can lead to an over-examination of tire durability, which means the tire durability will be underestimated. However, it is impossible to obtain the tire durability from ideal flat ground test, so this paper utilizes the finite element method (FEM) to simulate the tire rolling condition on flat ground and differently sized flywheels, and the SED is used to evaluate the over-examination of tire durability in flywheel test. According to the results, a flywheel with too small diameter has a large amount of over-examination, and the amount caused by a large flywheel is acceptable. This methodology can be a guideline to assess the over-examination on different sized flywheel tests relative to the flat ground, and for the certain tire in this study, flywheels with 3-5 times the tire diameter appear to have an acceptable over-examination

Effects of high progesterone in in-vitro fertilization cycle on DNA methylation and gene expression of adhesion molecules on endometrium during implantation window

Purpose High progesterone is associated with low implantation rate. Our previous study demonstrated that DNA methylation in endometrium was increased in women with high progesterone in IVF cycles. However, the DNA methylation status is still not yet confirmed, and how it affects endometrial receptivity in high progesterone is still unknown. Current study investigated the effects of high progesterone on DNA methylation and gene expression of adhesion molecules on endometrium during implantation window. Methods A cohort study included 20 women with high progesterone (HP) and 20 with normal progesterone (NP) on the day of human chorionic gonadotropin (hCG) administration after controlled ovarian hyperstimulation in IVF cycle. Endometrial tissues were collected on the 7th day after hCG administration. Immunohistochemical staining of DNA methyltransferases (DNMT1 and DNMT3B) and adhesion molecules (MUC1, CDH1 and CTNNB1) were performed. Methylation of MUC1, CDH1, and CTNNB1 promoter regions was detected by Sequenom MassARRAY or bisulfite sequencing PCR. RT-qPCR was used to quantify mRNA expression levels, and correlation of methylation and gene expression level of the adhesion molecules were determined. Results DNMT3B, but not DNMT1, in nucleus of luminal and glandular epithelial cells in HP group was significantly higher than that in NP group. Promoter regions of CDH1 and CTNNB1, but not MUC1, in endometrium of HP group were hypermethylated. Protein and mRNA expression of MUC1, CDH1, and CTNNB1 in endometrium of HP group was significantly lower than that in NP group. Level of DNA methylation was negatively correlated with the gene expression of CDH1 and CTNNB1, but not MUC1. Conclusions DNA hypermethylation and low expression of adhesion molecules on endometrium were associated with high progesterone during implantation window, which may contribute to the underlying epigenetic mechanism in the failure of IVF treatment