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Lower respiratory tract infections (LRTI) are a leading cause of morbidity and mortality globally, and the rise of Antimicrobial Resistance (AMR) complicates their treatment. To achieve the best patient outcomes and avoid contributing to the rise of AMR, timely and appropriate antimicrobial treatment needs to be prescribed. However, the current gold standard for aetiological investigation of LRTIs (microbiological culture) is too slow to guide initial therapy. Clinical metagenomics (CMg) has emerged as a potential solution to this problem; however, existing methods are too laborious. In this study, we optimise our previously published CMg pipeline to achieve a sensitive workflow with a 3.5 hour turnaround time. Evaluating the workflow, we show efficient depletion (>99.8%) of host DNA with our new 15 minute host depletion method. Sensitivity and specificity are 90.5% and 62.5%, respectively, rising to 96.6% and 100% when qPCR is used to investigate discordance. We also show that 30 minutes of sequencing is sufficient to make an accurate pathogen call. For pathogen surveillance, targeted sequencing approaches are more appropriate. Sequencing of SARS-CoV-2 for genomic epidemiology became a valuable tool during the ongoing COVID-19 pandemic. However, early on, methods were low-throughput and inflexible. We responded to this by developing a high-throughput library preparation method, CoronaHiT, which can be used for sequencing SARS-CoV-2 on Illumina or Oxford Nanopore Technologies platforms. The method was shown to be cheap and accurate, while also being more robust for samples with lower viral loads. CoronaHiT has subsequently been used to sequence hundreds of thousands of SARS-CoV-2 genomes in the UK. In conclusion, we have developed and optimised two different approaches for investigating respiratory infections (CMg and targeted) for two different applications, demonstrating the potential of rapid sequencing. Methods like these will continue to reshape diagnostics and public health in the future. more...

The aim of this research is to investigate a novel Multiple-Input-Multiple-Output (MIMO) sensor system for automotive applications. Compared to traditional phased arrays, a MIMO array can achieve the same fine angular resolution, but with a drastically less amount of sensor elements. For example, a MIMO array of 10 elements can deliver the same resolution as a phased array of 25 elements. The other highlight of this technology is that it can operate at short ranges, which is physically impossible with a phased array. Therefore, a MIMO system can potentially provide very high angular resolutions at short ranges. These properties make such a system attractive for a number of automotive applications, including parking aids, short-range cruise control, speed-over-ground estimation, pedestrian detection etc. Research started with the verification of application of conventional MIMO techniques for radar context. MIMO techniques were tested with the existing RF equipment in laboratory environment. Beamforming capabilities were verified, range and angular resolutions were compared to equivalent phased arrays and multiple-target resolving capabilities were confirmed. Nearfield focusing algorithms for MIMO arrays were developed and verified via experiments in the anechoic chamber with the same equipment. A technology demonstrator based on ultrasonic equipment was built and then tested in an anechoic chamber and the findings were compared to computed performance parameters. Further performance optimisations via aperiodic MIMO configurations were explored via use of heuristic optimisation algorithms. An optimised configuration then was tested in anechoic chamber and its performance was confirmed in experimentally. Finally using radio equipment again, an initial study on MTI applications was done. Platform motion compensation methods were developed and tested in order to make up for vehicular motion and to compensate for its possible effects. Both stationary platforms and a moving platform was used to experimentally confirm the MTI capabilities on both in an indoor setup and an outdoor setup. more...

This study explores the potential use of mobile learning in higher education with a focus on student and academic staff requirements of a potential mobile application. The research examines the stakeholders’ new technology acceptance behaviour within a post-1992 university and examines how new mobile technologies are able to contribute to enhancement of the learning experience of students and additionally the roles of educators in facilitating enhancement of the learning experience. A post-positivistic paradigm has been used to explore a wider view of the stakeholders’ (academic staff and students) understanding of the new technologies and the potential benefits of mobile applications. An electronic questionnaire was sent to over 900 undergraduates for their views on the use of new mobile technologies and in what ways these could be used to support their learning needs. This was followed by individual interviews and questionnaires to academic staff (n=44) to identify whether they would be interested in the use of mobile applications in their teaching and learning. The research explores the learning, concepts, theories and models which influence mobile device adoption and proposes a mobile application that has the potential to support teaching and learning. The data collected provides an invaluable insight into the potential use of a mobile learning platform at the University’s Faculty of Business. The participants describe their uses of four distinct types of devices; potential frequency of specific use, and their views on the attraction and/or disadvantages of mobile use for learning. The research findings lead to the recommendation for a mobile learning trial within the Faculty with the potential for application to other academic subjects within the university. Two elements have emerged from the research carried out and comprise an original contribution of the study, namely: an enhancement of the Technology Acceptance Model and development of the existing PESTEL model into a PESTEEL model by including Educational Factors and hence identifying a number of areas currently not addressed by the PESTEL model. The uniqueness of the study and the development of this work`s original contribution to new knowledge was enhanced by approaching data collection and analysis within a Technology Acceptance Model and the PESTEEL model. This was also achieved by interpreting the gathered data within the broader concept of professionalism, sub-divided and conceptualised into examining the adherence of participants. It is acknowledged that a limiting factor is that the study examined only one academic school within an institution, but it is anticipated that future research will include a comparison with other similar academic institutions. more...

This thesis sets out to examine how local environmental movements mobilize to engage a new intertwined national and global context in which capitalist globalization has intensified major problems, in particular social and economic inequalities and ecological degradation. In their struggles, local movements mobilize beyond their local and/or national borders, inserting themselves into transnational networks. A representative of such struggles, as I argue in the thesis, is the Bergama movement. The Bergama Movement, a local environmental movement struggling against a transnational gold-mining company in Western Turkey, is analyzed based on an extensive field research reflecting the geographical scope of and the diversity of actors involved in the movement. The research aims to understand the interrelated dimensions of a social movement such as initial mobilization, mobilizing structures, framing, identity construction, and political opportunities; embedding it in a new political and social context in which structures and practices at varying levels of politics become enmeshed. Thus, the thesis shows that making clear-cut distinctions between the local, the national and the global, is inadequate in understanding local movements which challenge actors of capitalist globalization. The contribution of this thesis lies in using the case of the Bergama movement to unpack the interrelated dynamics involved in enmeshed scales of doing politics. In that regard, I show that national and transnational actors align themselves, as in the case of the state in Turkey and transnational mining corporations, in a pro-mine network, while the Bergama activists have formed an extensive movement network by forging links with global civil society actors, external political parties, supranational and international organizations and the media who challenge capitalist globalization. Witnessing that their national political context is being restructured under capitalist globalization, they extensively utilize transnational political opportunities and define themselves as part of a general anti-capitalist globalization struggle. more...

There are multiple sources of astrophysical evidence which support the presence of dark matter (DM), which stands out as one of the open questions in the standard model (SM) of particle physics. One avenue to look for DM production is at the Large Hadron Collider (LHC), where the production of DM can be detected as events with large missing transverse momentum (p_T^miss). This thesis documents a search for new DM particles using proton-proton collisions at the LHC, recorded with the Compact Muon Solenoid (CMS) detector, at a center of mass energy of 13 TeV. In this search, the target signature is a Higgs boson, produced via the Vector Boson Fusion (VBF) process, decaying into a pair of DM particles, resulting in two energetic jets and large p_T^miss in the final state. To estimate the background processes, multiple control regions are defined and a simultaneous fit to data over all regions is performed. The data for this search was collected in 2017 and 2018, during Run 2 of the LHC. A full result corresponding to an integrated luminosity of 137 fb^-1 is also obtained by statistically combining this analysis result with the already published 2016 analysis. No excess of events is observed over expected SM backgrounds. The results are interpreted in the context of Higgs-portal models, where upper bounds are set on the branching ratio for the SM Higgs boson decaying to invisible DM particles. more...

Collecting a sufficient amount of data and centralizing them are both costly and privacy-concerning operations. These practical concerns arise due to the communication costs between data collecting devices and data being personal such as text messages of an end user. The goal is to train generalizable machine learning models with constraints on data without sharing or transferring the data. In this thesis, we will present solutions to several aspects of learning with data constraints, such as processing and supervision. We focus on federated learning, online learning, and learning generalizable representations and provide setting-specific training recipes. In the first scenario, we tackle a federated learning problem where data is decentralized through different users and should not be centralized. Traditional approaches either ignore the heterogeneity problem or increase communication costs to handle it. Our solution carefully addresses the heterogeneity issue of user data by imposing a dynamic regularizer that adapts to the heterogeneity of each user without extra transmission costs. Theoretically, we establish convergence guarantees. We extend our ideas to personalized federated learning, where the model is customized to each end user, and heterogeneous federated learning, where users support different model architectures. As a next scenario, we consider online meta-learning, where there is only one user, and the data distribution of the user changes over time. The goal is to adapt new data distributions with very few labeled data from each distribution. A naive way is to store data from different distributions to train a model from scratch with sufficient data. Our solution efficiently summarizes the information from each task data so that the memory footprint does not scale with the number of tasks. Lastly, we aim to train generalizable representations given a dataset. We consider a setting where we have access to a powerful teacher (more complex) model. Traditional methods do not distinguish points and force the model to learn all the information from the powerful model. Our proposed method focuses on the learnable input space and carefully distills attainable information from the teacher model by discarding the over-capacity information. We compare our methods with state-of-the-art methods in each setup and show significant performance improvements. Finally, we discuss potential directions for future work. more...

Solid-state quantum systems based on Josephson junctions, electronic spins and nuclear spins are among the leading candidates for realizing quantum bits (qubits) in a scalable manner. Despite recent demonstrations of few-qubit quantum registers with these systems, efficient photon-mediated entanglement generation between remote quantum registers remains an outstanding challenge. In this thesis, we develop a platform based on diamond color centers coupled to nanophotonic devices to address this challenge. To realize coherent atom-photon interactions, we first develop an improved understanding of the impact of the solid-state environment on the optical transitions of nitrogen-vacancy (NV) and silicon-vacancy (SiV) color centers in diamond. By investigating the interaction of defect orbitals with phonons and electric fields, we identify the necessary symmetry and temperature conditions at which atom-like, transform-limited optical transitions can be achieved. We show that the inversion symmetry of the SiV center results in a vanishing static electric dipole moment and protects optical transitions from electric field fluctuations arising from the solid-state environment. The reduced sensitivity to electric field noise results in spectrally-stable optical transitions for SiV centers, even in nanostructures. We use these properties and bright zero-phonon line emission to efficiently generate indistinguishable photons from separate SiV centers. These results establish SiV centers as superior optical emitters compared with NV centers both in terms of brightness and spectral stability. We next integrate SiV centers into diamond nanophotonic structures and demonstrate strong atom-photon interactions in the high-cooperativity regime of cavity quantum electrodynamics. We use ion implantation to create SiV centers with coherent optical transitions in diamond photonic crystal cavities. The strongly coupled SiV-cavity system is used to realize a quantum-optical switch that is nonlinear at the single-photon level. Finally, we demonstrate entanglement generation between two SiV centers in a single diamond waveguide based on detection of indistinguishable photons., Physics, Quantum optics; Diamond color centers; Silicon-vacancy centers; Nanophotonics; Spectroscopy more...

This thesis presents the results of a finite element study of the behavior of the shear links with reduced web sections subjected to cyclic and monotonic loading protocols, for use in seismic-resistant steel Eccentrically Braced Frames (EBFs). The capacity design philosophy for EBFs relies on the principle that the link, where inelastic deformation is intended to occur in an earthquake, must be the weakest element in the frame. One approach to satisfying capacity design requirements of EBFs is to decrease the strength of the links. Removing some portion of the link web is one method to reduce the shear capacity of the link. Twenty-one finite element models were analyzed under cyclic and monotonic loading protocols. Finite element models were based on a W18x40 shear link, without web holes, tested in an actual experiment. Modeling techniques and material definitions were validated using the same experimental findings. The finite element shear link models with various hole patterns, locations, and percent web removal were then analyzed to investigate the effect of removing material from the web on the behavior of the shear link in terms of strength and rotation capacity. This study suggests that shear links with reduced web sections provide a potentially viable method to reduce link shear strength. more...

The most lethal of all brain tumors today is known as glioblastoma multiforme(GBM). Able to resist almost all treatments today with a high chance for recurrence, GBM is known for its extreme resilience. This inability to treat the tumor comes from the characteristics of GBM itself, composing of a diffuse edged tumor with infiltrations, heterogeneous cell population consisting of both normal and stem-like cancer cells, numerous regions of hypoxia, and accessibility issues due to the blood-brain barrier(BBB). To treat GBM with its delivery issues as well as multiple cell populations, we developed a targeted multicomponent nanoparticle with an iron core as well as mesoporous silica shell that can deliver drugs across the BBB. In addition, when exposed to an alternating radiofrequency field, the magnetic core of the iron attempts to align and causes release of massive doses of drug molecules. Although one drug treatments of tumors failed to yield any significant effect in survival, the combination of one cytotoxic agent and one cancer stem cell inhibitor succeeded in delivering long term survival and slowed progression in mouse models of glioblastoma multiforme more...

When he began his journal seaman Hugh Calhoun had high hopes for the outward-bound voyage ahead of him. Ship-of-the-Line Ohio was back from the Siege of Veracruz, being prepared for her next mission, and the War was at its height. The cruize, as he called it, did not turn out as eventful as he expected it to be and yet he was nevertheless able to produce a book which bountifully embodies a short but fruitful chapter of maritime literary history. Serio-Comic Journal of a Cruize, On Board of the U. S. Ship Ohio, Commencing from New York June 23d 1847, with its full name, is a shipboard diary kept by an ordinary seaman during the Mexican-American War. The 148-page manuscript volume, located at the archives of the Massachusetts Historical Society in Boston, is a product of the maturity phase of American sea writing as Calhoun, self-consciously a Jack Tar and an American, was representing a trained, well-read and well-influenced generation of sailor-authors who lived and recorded the final years of America under sail. The past three decades have seen a progressive conceptual expansion of the themes involving the ways in which literate sailors viewed the world they lived in. Scholars of early American literature, maritime history and culture have explored the meanings and information provided in the textual products of seamen. Upon comparison with similar material found at the archives of maritime museums and historical societies, and discussions with leading maritime historians, Serio-Comic Journal proved to be a meaningful source text which, through scholarly treatment, can benefit research in multiple disciplines due to the significance of its production date and the diversity of the topics and literary forms found in it. This edition aims to provide related fields of study with a historically contextualized shipboard document in the light of these latest findings. The transcription of the complete text is presented with glossarial, historiographical and geographical notes, whereas the introductory chapters discuss several key subjects to form a framework for the better evaluation of not only the source text of the edition but the sea journal genre as a whole. more...

Many common electrical materials used in the current sensing applications suffer from structural and functional issues related to high operating temperatures (750°-1600°C), alternating reducing/oxidizing atmospheres, high pressures and corrosive environments. Therefore, there is a need for development of new materials, which are capable to operate under high-temperature and harsh-environments to provide real-time, accurate sensing during industrial processes such as coal gasification and power generation. In this study, electroconductive ceramic composites were fabricated by incorporating the 20-90 vol% of transition metal silicides (MoSi2, WSi2, NbSi2, TaSi 2, CrSi2) within refractory oxides (Al2O 3, ZrO2, Cr2O3), followed by sintering at 1370°-1600°C in argon. The densification, microstructural evolution, phase development and thermal stability of the composites were studied after sintering and further annealing by Archimedes, Scanning electron microscopy (SEM) and X-ray diffraction/Rietveld (XRD) techniques. Their non-isothermal and isothermal oxidation behavior was studied under ambient air using a thermogravimetric analyzer (TGA) at 50°-870°C to understand the key parameters influencing their high-temperature oxidation. The selected composites were also preoxidized at 1000°-1200°C for 10-120 minutes to better understand their high-temperature oxidation kinetics and surface layer formation, and hence, to enhance their oxidation resistance by forming a protective surface layer. XRD, Raman spectroscopy and X-ray photoelectron spectroscopy (XPS) were used for structural and surface characterization. In addition, their 4-point DC electrical conductivities were measured up to 800°-1000°C to study their electrical performance as a function of the composition and processing. A microstructural image analysis method was also developed for quantitatively characterizing the degree of distribution (homogeneity) within the composites. Lastly, thick-film embedded thermocouples (e.g. MoSi2-Al2O3//WSi 2-Al2O3) were fabricated using selected composites by a screen printing technique. Their thermoelectric properties were measured in argon by a typical hot-cold junction temperature measurements, while their structural and microstructural analyses were performed by XPS, XRD and SEM. more...

Field of nanoplasmonics study the interaction of light with nanoscale metallic structures and it possesses the great potential of being the key element in future, highly integrated, on-chip nanophotonic aevices. Several major breakthroughs have been demonstrated in the past decade regarding the utilization of plasmonics for purposes ranging from optical nanoantennas to enhanced biochemical sensing platforms. So far, studies are generally focused on two-dimensional (2D) arrangement of plasmonic nanostructures. However, engineering of materials in three dimensions (3D) by integrating different kinds of plasmonic resonances in multi-layers, offers additional degrees of freedom in our design space, resulting in remarkable effects This thesis research investigates the outcomes of the tailoring of electromagnetic interactions between multiple plasmonic structures in three-dimensions. We are mainly focused on a coherence phenomenon termed as Farro resonance. Farro resonances are generally studied in atomic physics, which occur due to an interference between multiple excitation pathways where a discrete resonant state is coupled to a broad continuum. Fano resonances are inherently linked to an atomic physics concept termed as Electromagnetically Induced Transparency (EIT). Recently, a plasmonic analogue of the EIT effect was proposed and drew great attention. Plasmon Induced Transparency (PIT) enables one to mimic the extremely dispersive spectral characteristics of EIT, on-chip and without any stringent requirements. In the first two parts of this work, we show that by a precise engineering of the near-field interactions of plasmonic elements, PIT effect can be carried simultaneously to multiple spectral domains. This effect has many potential applications ranging from enhanced non-linearities to novel optical communication systems. In the third part, we investigate a multi-spectral Fano resonant plasmonic structure's non-linear response by embedding a nanoscale Kerr medium to the design. We show that a unique set of effects can be achieved through the interplay of Fano resonances and embedded optical non-linearity. In the last part, we develop a unifying theory to describe Fano resonances in both purely plasmonic structures and also in other systems which are comprised of plasmonic structures coupled to molecular resonances. The developed theory provides an invaluable intuition to Fano resonances and their utilization in applications such as biosensing and spectroscopy. more...

In addressing the propensity of steel building structures to experience progressive collapse due to extreme loading conditions (e.g., blast), current design guidelines propose the use of a threat-independent approach that is commonly referred to in the literature as “the missing column scenario”. Under this scenario, a column from a given story is assumed to be removed and the resulting structure is analyzed to determine if it could sustain the loads by activating one or more alternate load carrying mechanisms, with the idea of mitigating the potential for progressive structural collapse. This study specifically focuses on the ability of ductile steel beams to carry loads by transitioning from flexural behavior to cable-like behavior. Theoretical fundamentals of this behavior are described for rectangular and W-shaped steel beams with idealized boundary conditions and presumed fully ductile behavior. Two theoretical analysis approaches are used to model the beam behavior: rigid-plastic analysis and cable analysis. The main factors affecting the behavior, such as material and geometric properties as well as boundary conditions are described and corroborating nonlinear finite element (FE) analyses are presented and compared to the theoretical results. Open System for Earthquake Engineering Simulation, OpenSees was used in the FE analysis studies. Based upon theoretical and FE analysis results, a set of equations are proposed that can be used to predict the deflection at the onset of pure cable behavior. Additionally, the effect of elastic boundary restraints on the beam behavior was studied using FE analysis. An approach to evaluate the boundary restraints offered by the surrounding members in a given frame is also presented. It is shown that axial restraints have a much more significant effect on the behavior than rotational restraints. The theory presented in this thesis can serve as basis for designing ductile steel beams undergoing transition from flexural to cable-like behavior. more...

Human obesity is a multi-factorial trait regulated by environmental and genetic factors and is considered to be a global epidemic associated with mortality. Therefore, understanding the molecular pathways controlling the energy homeostasis is of great importance in order to develop pharmaceutical agents to treat obesity. This thesis work includes four separate research projects with the common intention of exploring the central control of energy homeostasis using three distinct research approaches. Leptin-melanocortin axis is the major central regulator of energy homeostasis where MC4R and POMC play key roles in transmitting the anorexigenic signal of the adipocyte secreted hormone leptin. In a genetic linkage study, we demonstrated that naturally occurring MC4R mutations but not the POMC or MC3R mutations are strongly associated with human obesity. Secondly, in an attempt to determine an alternative signaling pathway to leptin, the inhibition of Gi protein signaling in the POMC neurons decreased the energy expenditure in a transgenic mouse model. Finally, we scrutinized the molecular mechanism underlying the physiologically relevant constitutive activity of MC4R. The data supports the evolutionary role of the N-terminal domain in the activity regulation of the G protein-coupled receptors. Overall, our findings provide essential pieces to the bigger puzzle of the melanocortin system, and contribute to the biomedical research in the pursuit of understanding the regulation of energy homeostasis in humans. more...

Periodontal diseases are inflammatory diseases of the oral cavity that can be confined only to the gingiva as in gingivitis or exceed beyond that to result in soft and hard tissue loss which would affect the attachment of the teeth to the alveolar bone as in periodontitis. An inflammatory process that has been discussed for decades of its nature, risk factors, and whether it has specific or non-specific etiological factors including the underlying microbiology. The National Institute of Dental and Craniofacial Research refer to periodontal diseases as the most common cause of tooth loss in adults. Studies have also suggested that periodontal disease is the most common reason for tooth loss. Mandibular incisors are most frequently lost due to periodontal diseases followed by maxillary incisors and molars. The objectives of this study were: • Determine the prevalence of periodontitis using bitewings radiographs among the patients enrolled in the clinics at HSDM and addressing risk factors associated with the disease (i.e. sex, age, BMI, etc.). • Predict annual alveolar bone loss in a subpopulation of patients with CVD adjusting for associated systemic diseases and risk factors. • Predict annual alveolar bone loss in a subpopulation of elderly patients who were taking oral bisphosphonate adjusting for systemic diseases and associated risk factors. Alveolar bone loss was measured on the mesial and distal sites of first and second mandibular and maxillary premolars and molars using the calibrated measuring tool of Emago® (Oral Diagnostic Systems, Amsterdam, Netherlands) software– the radiographic imaging software at Harvard School Dental Medicine., Dental Public Health more...

This thesis has three essays which are empirical studies at the intersection of finance and macroeconomics. The topics include low interest rates and financial markets, debt contracts and corporate borrowing constraints, and expectations in finance and macro. The essays hope to provide empirical evidence, using diverse approaches, to better understand the connections as well as differences between classic theories and economic activities in practice., Business Economics, Empirical analyses; macro-finance more...

This dissertation focuses on three prominent areas of macroeconomic policy: fiscal stimulus, bail-outs and industrial policy, and monetary policy. In each case, I analyze the nature of the problem without intervention first before turning to why and how policy can be used to improve outcomes. In the first chapter, I study how relative demand shocks for different goods and services propagate through the economy to affect aggregate employment – and I use these insights to show how fiscal stimulus should be designed to achieve the greatest bang for buck in terms of employment. In the second chapter, I study how firm entry and exit in one industry can affect other industries and the economy as a whole through input-output relationships. I characterize which firms and industries are systemically important, show that the equilibrium is generically inefficient, and study when and how bailouts can be used to improve welfare. In the final paper, I provide a new microfoundation for downward wage rigidity, show that this microfoundation yields predictions that are consistent with the data, and study how monetary policy should behave given this microfoundation., Economics, Macroeconomics; Networks; Cascades; Monetary Policy; Bail outs; more...

This dissertation presents four essays. The first chapter builds a real-options, term structure model of the firm incorporating stochastic volatility and endogenous default to shed new light on the value premium, financial distress, momentum, and credit spread puzzles. The paper uses recently developed methodologies based on asymptotic expansions to solve the model. The second chapter, coauthored with Adam Guren, presents a model that shows how foreclosures can exacerbate a housing bust and delay the housing market's recovery. Quantitatively, the model successfully explains aggregate and retail price declines, the foreclosure share of volume, and the number of foreclosures both nationwide and across MSAs. The third and fourth chapters, coauthored with Stephen W. Salant and Jason Winfree, discuss the economics of untraceable experience goods in a variety of settings. The third chapter drops the "small country" assumption in the trade literature on collective reputation and shows how large exporters like China can address severe problems assuring the quality of its exports. The fourth chapter demonstrates how regulations in the formal sector of developing countries can lead to a quality gap between formal and informal sector goods. It moreover investigates how changes in regulation affect quality, price, aggregate production, and the number of firms in each sector., Economics more...

This dissertation consists of four essays that study normative questions on issues related to financial markets and the macroeconomy., Economics

This dissertation analyzes trading behavior in financial markets from multiple perspectives. In chapter 1, "Exploratory Trading," I investigate the mechanisms underlying high-frequency traders' capacity to profitably anticipate price movements. I develop a model of how a trader could gather valuable private information by using her own orders in an exploratory manner to learn about market conditions. The model's predictions are borne out empirically, and I find that this "exploratory trading" model helps to resolve several central open questions about high-frequency trading. Chapters 2 and 3 focus on the trading behavior of individuals. Chapter 2, "Foundations of the Disposition Effect: Experimental Evidence," (co-authored with Johanna Mollerstrom), presents and analyzes results from a laboratory experiment intended to examine if and how "regret aversion"--aversion to admitting mistakes--affects people's trading decisions. Although the experimental results resolve little about regret aversion specifically, they reveal some novel and unexpected effects, most importantly that subjects radically changed their trading decisions when they were compelled to devote a minimal amount of extra attention. In chapter 3, "Price Targets," I analyze how rational investors who privately observe information of indeterminate quality use prices to learn about whether or not their private information is valuable. I derive implications about trading behavior that not only help to explain a variety of empirical puzzles, but also generate several new testable predictions. Although these three essays differ considerably in methodology and focus, they all address the same basic issue of understanding the foundations of trading behavior., Economics more...

Prices in financial markets are primarily driven by the interaction of risk and time. The returns to financial assets over long time horizons are primarily driven by fundamental news regarding their promised cash flows. In contrast, short-run price variation is associated with a large degree of predictable, transient investor trading behavior unrelated to fundamental prospects. The quantity of long-run risk directly affects economic well-being, and its magnitude has varied significantly over the past century. The theoretical model presented here shows some success in quantifying the impact of news about future risks on asset prices. In particular, some investing strategies that appear to offer anomalously large returns are associated with high exposures to future long-run risks. The historical returns to these portfolios are partly a result of investors’ distaste for assets whose worth declines when uncertainty increases. The financial sector is tasked with pricing these risks in a way that properly allocates investment resources. Over the past thirty years, this sector has grown much more rapidly than the economy as a whole. As a result, asset prices appear to be more informative. However, the new information relates to short-term uncertainty, not long-run risk. This type of high-frequency information is unlikely to affect real investment in a way that would benefit broader economic growth. more...