The Role of ETFs in Asset Pricing, Mutual Fund Performance, and Market Prediction

This thesis investigates the various roles that the information provided by Exchange Traded Funds (ETFs) could play in asset pricing and market prediction. The empirical analysis contains three parts: The first part extracts information from the US ETFs market and constructs explanatory returns to price the Fama-French portfolios. It aims to provide a parsimonious model (the ETF-factor model) that is able to compete with the five-factor model of Fama and French (2015) and the q-factor model of Hou, Xue, and Zhang (2015). The second part applies the ETF-factor model, along with other conventional pricing models, to measure US equity fund performance. In addition, it attempts to develop relative pricing models as passive benchmarks for measuring US fixed-income fund performance by using information from bond ETFs. The purpose of the third part is to develop a new measure of Chinese investor behaviour that has predictive power for the Chinese market by using the information provided by respective ETFs. The results suggest that ETFs deserve more attention in academic research. In line with conventional financial theory, ETFs’ market dramatically increases the investment universe and securitizes illiquid assets. It comes as no surprise that the risk factors developed from ETFs have explanatory power for a cross-section of stock returns. In addition, a proxy for the bond market can be developed from bond ETFs. This avoids the subjective selection of the bond index as a passive benchmark and can provide a unique pricing model for bonds. Furthermore, research on ETFs contributes to the behavioural finance literature. Investor sentiment is a very important concept in behavioural finance. This thesis finds evidence that the investor behaviour that uses information from ETFs explains and predicts the Chinese market. In addition, it could lead to a profitable high-frequency trading strategy in actual trading. Overall, this thesis researches ETFs from a new perspective. It does not view the ETFs as an investment vehicle but consider ETFs as a type of fundamental asset in the economy. The findings of this thesis contribute to the literature of asset pricing, behavioral finance, and market prediction, and identifies new areas for future research

Developing new fluorophores for applications in protease detection and protein labeling

Master'sMASTER OF SCIENC

Stereoselective synthesis and iterative coupling of Csp3 boronates for automating small molecule synthesis

Small molecules perform many important functions in nature, medicine, and technology. However, efforts to discover and optimize new small molecule function are often impeded by limitations in synthetic access to this class of compounds. In contrast to peptide and oligonucleotide syntheses, small molecule syntheses typically employ strategies and purification methods that are highly customized for each target. A broadly applicable automated process for the synthesis of different classes of small molecules has thus far remained elusive. To enable the more generalized automation of small molecule synthesis, a common building block-based strategy and a common purification process for the preparation of many different types of small molecules are needed. Towards this goal, we focused on expanding the scope of a building block-based strategy involving the iterative coupling of boronate building blocks to include Csp3-rich linear and polycyclic small molecules. The first approach undertaken was the discovery of a pinene-derived iminodiacetic acid (PIDA) ligand which enabled the stereoselective synthesis of a wide range of new types of Csp3 boronates. The utility of these Csp3 boronates was demonstrated in the synthesis of a pharmaceutically relevant target using a previously undescribed iterative Csp3-Csp2 coupling. In order to access Csp3-rich cyclic and polycyclic molecules via the same building block-based iterative coupling process, a linear-to-cyclized strategy inspired by the biosynthesis of polycyclic natural products was formulated. Iterative coupling of Csp3 boronates generates linear precursors which can then be polycyclized to give the complex topology found in many polycyclic natural products. This strategy was utilized in the synthesis of four natural products and natural product-like cores from boronate building blocks. This building block-based approach to synthesis was successfully automated with the discovery of a new type of catch-and-release purification protocol applicable to the boronate intermediates used in synthesis. 14 distinct classes of small molecules were constructed from boronate building blocks on a small molecule synthesizer using the same iterative coupling process. The synthesis-enabled advances in automating small molecule synthesis described in this dissertation now stands to better enable the scientific community to bring the substantial power of small molecule synthesis to bear upon many important unsolved problems in society

Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems

Combining the strengths of model-based iterative algorithms and data-driven deep learning solutions, deep unrolling networks (DuNets) have become a popular tool to solve inverse imaging problems. While DuNets have been successfully applied to many linear inverse problems, nonlinear problems tend to impair the performance of the method. Inspired by momentum acceleration techniques that are often used in optimization algorithms, we propose a recurrent momentum acceleration (RMA) framework that uses a long short-term memory recurrent neural network (LSTM-RNN) to simulate the momentum acceleration process. The RMA module leverages the ability of the LSTM-RNN to learn and retain knowledge from the previous gradients. We apply RMA to two popular DuNets -- the learned proximal gradient descent (LPGD) and the learned primal-dual (LPD) methods, resulting in LPGD-RMA and LPD-RMA respectively. We provide experimental results on two nonlinear inverse problems: a nonlinear deconvolution problem, and an electrical impedance tomography problem with limited boundary measurements. In the first experiment we have observed that the improvement due to RMA largely increases with respect to the nonlinearity of the problem. The results of the second example further demonstrate that the RMA schemes can significantly improve the performance of DuNets in strongly ill-posed problems

Inflammasomes in Alveolar Bone Loss

Bone remodeling is tightly controlled by osteoclast-mediated bone resorption and osteoblast-mediated bone formation. Fine tuning of the osteoclast–osteoblast balance results in strict synchronization of bone resorption and formation, which maintains structural integrity and bone tissue homeostasis; in contrast, dysregulated bone remodeling may cause pathological osteolysis, in which inflammation plays a vital role in promoting bone destruction. The alveolar bone presents high turnover rate, complex associations with the tooth and periodontium, and susceptibility to oral pathogenic insults and mechanical stress, which enhance its complexity in host defense and bone remodeling. Alveolar bone loss is also involved in systemic bone destruction and is affected by medication or systemic pathological factors. Therefore, it is essential to investigate the osteoimmunological mechanisms involved in the dysregulation of alveolar bone remodeling. The inflammasome is a supramolecular protein complex assembled in response to pattern recognition receptors and damage-associated molecular patterns, leading to the maturation and secretion of pro-inflammatory cytokines and activation of inflammatory responses. Pyroptosis downstream of inflammasome activation also facilitates the clearance of intracellular pathogens and irritants. However, inadequate or excessive activity of the inflammasome may allow for persistent infection and infection spreading or uncontrolled destruction of the alveolar bone, as commonly observed in periodontitis, periapical periodontitis, peri-implantitis, orthodontic tooth movement, medication-related osteonecrosis of the jaw, nonsterile or sterile osteomyelitis of the jaw, and osteoporosis. In this review, we present a framework for understanding the role and mechanism of canonical and noncanonical inflammasomes in the pathogenesis and development of etiologically diverse diseases associated with alveolar bone loss. Inappropriate inflammasome activation may drive alveolar osteolysis by regulating cellular players, including osteoclasts, osteoblasts, osteocytes, periodontal ligament cells, macrophages, monocytes, neutrophils, and adaptive immune cells, such as T helper 17 cells, causing increased osteoclast activity, decreased osteoblast activity, and enhanced periodontium inflammation by creating a pro-inflammatory milieu in a context- and cell type-dependent manner. We also discuss promising therapeutic strategies targeting inappropriate inflammasome activity in the treatment of alveolar bone loss. Novel strategies for inhibiting inflammasome signaling may facilitate the development of versatile drugs that carefully balance the beneficial contributions of inflammasomes to host defense