Essays in corporate finance and banking

This thesis consists of three empirical studies about corporate finance and banking. In the first chapter, I investigate how CEOs communicate with the market. CEOs have incentives to communicate with their investors after news releases if the market misinterprets the news. I examine how CEOs communicate with the market through their trading patterns. I find that CEOs are more likely to purchase shares after positive and negative news releases, suggesting that they want to confirm their positive news if the market underreacts to it and want to mitigate the market overreaction to their negative news by purchasing shares. These patterns vary conditional on the information environment and news categories. My results suggest that CEOs can make the news salient via their trading pattern. The second chapter uses staggered state-level bank deregulation events in the United States as exogenous shocks to investigate the effects of bank competition on bank liquidity creation at the state level. I document that state-level bank deregulation does not, on average, significantly affect state-level bank liquidity creation, while bank-level analyses demonstrate that enhanced bank competition decreases bank liquidity creation. In addition, I find that states and banks respond to the state-level deregulation events differently. My results suggest that the policy, which is applied to all heterogeneous banks and states in the same way, does not fit all. In the third chapter, I examine how bank CEO debt incentives relate to bank liquidity creation. I find that higher CEO inside debt holdings are associated with lower bank liquidity creation, suggesting that CEOs with higher inside debt holdings adopt more conservative liquidity creation strategies. The result is driven by large banks, suggesting that CEOs in large banks manage banks more conservatively than CEOs in small banks, as their inside debt holdings increase. My results suggest that while regulators could increase bank liquidity creation by imposing lower CEO inside debt holding requirements, it could simultaneously make banks riskier. Debt-based compensation would be a double-edged sword for designing policy about bank liquidity creation and bank soundness

Bank partnership and liquidity crisis

This study empirically investigates the relationship between banking integration and liquidity management. To measure banks’ connectivity, we use the number of partnerships proxied via the syndicated loan arrangements in which they serve as lead arrangers. If banks establish more business partnerships through syndicated loan arrangements, those under market stress are more likely to face increased funding costs, create reduced liquidity, and originate declined small business loans and mortgages. Those banks with more partners are shown to have a lower liquidity coverage ratio, suggesting that business partnerships create a disincentive toward liquidity risk management

Array-Based Protein Sensing Using an Aggregation-Induced Emission (AIE) Light-Up Probe

Protein detection and identification are important for the diagnosis of diseases; however, the development of facile sensing probes still remains challenging. Here, we present an array-based "turn on" protein-sensing platform capable of detecting and identifying proteins using aggregation-induced emission luminogens (AIEgens). The water-soluble AIEgens in which fluorescence was initially turned off showed strong fluorescence in the presence of nanomolar concentrations of proteins via restriction of the intramolecular rotation of the AIEgens. The binding affinities between the AIEgens and proteins were associated with various chemical functional groups on AIEgens, resulting in distinct fluorescent-signal outcomes for each protein. The combined fluorescence outputs provided sufficient information to detect and discriminate proteins of interest by linear discriminant analysis. Furthermore, the array-based sensor enabled classification of different concentrations of specific proteins. These results provide novel insight into the use of the AIEgens as a new type of sensing probe in array-based systems

Person Re-identification in Videos by Analyzing Spatio-temporal Tubes

Typical person re-identification frameworks search for k best matches in a gallery of images that are often collected in varying conditions. The gallery usually contains image sequences for video re-identification applications. However, such a process is time consuming as video re-identification involves carrying out the matching process multiple times. In this paper, we propose a new method that extracts spatio-temporal frame sequences or tubes of moving persons and performs the re-identification in quick time. Initially, we apply a binary classifier to remove noisy images from the input query tube. In the next step, we use a key-pose detection-based query minimization technique. Finally, a hierarchical re-identification framework is proposed and used to rank the output tubes. Experiments with publicly available video re-identification datasets reveal that our framework is better than existing methods. It ranks the tubes with an average increase in the CMC accuracy of 6-8% across multiple datasets. Also, our method significantly reduces the number of false positives. A new video re-identification dataset, named Tube-based Re-identification Video Dataset (TRiViD), has been prepared with an aim to help the re-identification research community

VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception

AI alignment refers to models acting towards human-intended goals, preferences, or ethical principles. Given that most large-scale deep learning models act as black boxes and cannot be manually controlled, analyzing the similarity between models and humans can be a proxy measure for ensuring AI safety. In this paper, we focus on the models' visual perception alignment with humans, further referred to as AI-human visual alignment. Specifically, we propose a new dataset for measuring AI-human visual alignment in terms of image classification, a fundamental task in machine perception. In order to evaluate AI-human visual alignment, a dataset should encompass samples with various scenarios that may arise in the real world and have gold human perception labels. Our dataset consists of three groups of samples, namely Must-Act (i.e., Must-Classify), Must-Abstain, and Uncertain, based on the quantity and clarity of visual information in an image and further divided into eight categories. All samples have a gold human perception label; even Uncertain (severely blurry) sample labels were obtained via crowd-sourcing. The validity of our dataset is verified by sampling theory, statistical theories related to survey design, and experts in the related fields. Using our dataset, we analyze the visual alignment and reliability of five popular visual perception models and seven abstention methods. Our code and data is available at \url{https://github.com/jiyounglee-0523/VisAlign}

Development and evaluation of gellan gum/silk fibroin/chondroitin sulfate ternary injectable hydrogel for cartilage tissue engineering

Hydrogel is in the spotlight as a useful biomaterial in the field of drug delivery and tissue engineering due to its similar biological properties to a native extracellular matrix (ECM). Herein, we proposed a ternary hydrogel of gellan gum (GG), silk fibroin (SF), and chondroitin sulfate (CS) as a biomaterial for cartilage tissue engineering. The hydrogels were fabricated with a facile combination of the physical and chemical crosslinking method. The purpose of this study was to find the proper content of SF and GG for the ternary matrix and confirm the applicability of the hydrogel in vitro and in vivo. The chemical and mechanical properties were measured to confirm the suitability of the hydrogel for cartilage tissue engineering. The biocompatibility of the hydrogels was investigated by analyzing the cell morphology, adhesion, proliferation, migration, and growth of articular chondrocytes-laden hydrogels. The results showed that the higher proportion of GG enhanced the mechanical properties of the hydrogel but the groups with over 0.75% of GG exhibited gelling temperatures over 40 °C, which was a harsh condition for cell encapsulation. The 0.3% GG/3.7% SF/CS and 0.5% GG/3.5% SF/CS hydrogels were chosen for the in vitro study. The cells that were encapsulated in the hydrogels did not show any abnormalities and exhibited low cytotoxicity. The biochemical properties and gene expression of the encapsulated cells exhibited positive cell growth and expression of cartilage-specific ECM and genes in the 0.5% GG/3.5% SF/CS hydrogel. Overall, the study of the GG/SF/CS ternary hydrogel with an appropriate content showed that the combination of GG, SF, and CS can synergistically promote articular cartilage defect repair and has considerable potential for application as a biomaterial in cartilage tissue engineering.This research was supported by the International Research and Development Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2017K1A3A7A03089427) and by the bilateral cooperation Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2019K2A9A1A06098563)

Metabolically-Healthy Obesity and Coronary Artery Calcification

ObjectivesThe purpose of this study was to compare the coronary artery calcium (CAC) scores of metabolically-healthy obese (MHO) and metabolically healthy normal-weight individuals in a large sample of apparently healthy men and women.BackgroundThe risk of cardiovascular disease among obese individuals without obesity-related metabolic abnormalities, referred to as MHO, is controversial.MethodsWe conducted a cross-sectional study of 14,828 metabolically-healthy adults with no known cardiovascular disease who underwent a health checkup examination that included estimation of CAC scores by cardiac tomography. Being metabolically healthy was defined as not having any metabolic syndrome component and having a homeostasis model assessment of insulin resistance <2.5.ResultsMHO individuals had a higher prevalence of coronary calcification than normal weight subjects. In multivariable-adjusted models, the CAC score ratio comparing MHO with normal-weight participants was 2.26 (95% confidence interval: 1.48 to 3.43). In mediation analyses, further adjustment for metabolic risk factors markedly attenuated this association, which was no longer statistically significant (CAC score ratio 1.24; 95% confidence interval: 0.79 to 1.96). These associations did not differ by clinically-relevant subgroups.ConclusionsMHO participants had a higher prevalence of subclinical coronary atherosclerosis than metabolically-healthy normal-weight participants, which supports the idea that MHO is not a harmless condition. This association, however, was mediated by metabolic risk factors at levels below those considered abnormal, which suggests that the label of metabolically healthy for obese subjects may be an artifact of the cutoff levels used in the definition of metabolic health

Ethanol extract of Scutellaria baicalensis Georgi prevents oxidative damage and neuroinflammation and memorial impairments in artificial senescense mice

Aging is a progressive process related to the accumulation of oxidative damage and neuroinflammation. We tried to find the anti-amnesic effect of the Scutellaria baicalens Georgia (SBG) ethanol extract and its major ingredients. The antioxidative effect of SBG on the mice model with memory impairment induced by chronic injection of D-galactose and sodium nitrate was studied. The Y-maze test was used to evaluate the learning and memory function of mice. The activities of superoxide dismutase, catalase and the content of malondialdehyde in brain tissue were used for the antioxidation activities. Neuropathological alteration and expression of bcl-2 protein were investigated in the hippocampus by immunohistochemical staining. ROS, neuroinflammation and apoptosis related molecules expression such as Cox-2, iNOS, procaspase-3, cleaved caspase-3, 8 and 9, bcl-2 and bax protein and the products of iNOS and Cox-2, NO, PGE2, were studied using LPS-activated Raw 264.7 cells and microglia BV2 cells. The cognition of mice was significantly improved by the treatment of baicalein and 50 and 100 mg/kg of SBG in Y-maze test. Both SBG groups showed strong antioxidation, antiinflammation effects with significantly decreased iNOS and Cox-2 expression, NO and PGE2 production, increased bcl-2 and decreased bax and cleaved caspase-3 protein expression in LPS induced Raw 264.7 and BV2 cells. We also found that apoptotic pathway was caused by the intrinsic mitochondrial pathway with the decreased cleaved caspase-9 and unchanged cleaved caspase-8 expression. These findings suggest that SBG, especially high dose, 100 mg/kg, improved the memory impairments significantly and showed antioxidation, antiinflammation and intrinsic caspase-mediated apoptosis effects