VictorJuiz/thesis huggingface dataset:
Two Essays on Asset Pricing
Keywords: Asset pricing
Stock returns

This dissertation contains two essays that study the implications of information arrival on asset prices. In the first essay, I study an important aspect of the firm-level information structure - the quantity of information - and its effect on the cross-section of stock returns. The main contribution of this essay is to propose a new proxy for information intensity (monthly information quantity) and establish a link between information intensity and stock returns. I find that higher information intensity reduces expected uncertainty and leads to a lower expected return, after controlling for a variety of traditional risk factors and asset pricing anomalies. An information-intensity-based long-short portfolio generates an abnormal return of 4.44% per year. My findings suggest that, as a key component of information structure, information quantity is of first order importance in determining stock returns, and more generally, that investor learning plays an important role in financial markets with incomplete information. The second essay, based on a joint work with John Maheu and Tom McCurdy, studies the asset-pricing implication of market-level information arrival, which can lead to large movements (jumps) in the market index. Deviating from the literature that studies the impact of jumps through option pricing and motivated by a nonlinear pricing kernel associated with general preferences, we focus on the pricing impact of jumps through the pricing of higher-order moments. We find that three components of a modeling device, including: a 2-component GARCH model for diffusive volatility, an autoregressive model for jump intensity, and a higher order moment specification of the equity premium, are particularly important for asset pricing with jumps. This modeling device enables us to be the first to uncover significant pricing of both diffusive risk and jump risk, using only a time series of equity return data. We find that the risk premium due to jumps is a significant part of the overall equity premium. Our results also suggest the existence of a significant skewness premium and offer a potential resolution to sometimes conflicting results on the intertemporal risk-return relationship. Furthermore, taking jumps into account improves the out-of-sample performance of a portfolio allocation application.
Part I: Morphology Transformation of Block Copolymer Micelles containing Quantum Dots in the Corona Part II: The Synthesis and Self-assembly of New Polyferrocenylsilane Block Copolymers
Keywords: block copolymer
micelle
polyferrocenylsilane
quantum dot

My Ph.D. thesis is presented in two parts. In the first part, I describe the preparation of organic-inorganic hybrid micelles formed from poly(styrene-b-4-vinylpyridine) (PS-b-P4VP) block copolymers and CdSe quantum dots (QDs). Several distinct morphologies were observed including, spheres, finite-sized wormlike networks and clusters of hollow vesicles. A series of experiments were carried out to explore whether these hybrid colloids were thermodynamically stable or formed under kinetic control. Upon addition of 2-propanol (2-PrOH) to a chloroform solution containing a mixture of PS404-b-P4VP76 plus CdSe QDs (2-PrOH is a good solvent for P4VP block and a precipitant for PS block and QDs), uniform spherical micelles formed almost instantly, with a PS core and a thin P4VP corona to which the QDs were attached. Vigorous stirring of this solution for two days led to the formation of three-dimensional wormlike networks consisted of Y-junctions and cylindrical struts, terminated by bulbous spherical end-caps. Even more profound structural changes occurred when the solution was subjected to prolonged magnetic stirring (e.g. 1 month). ii In contrast, manipulating the chemical composition of the initial block copolymer could trigger a spontaneous structural transition from sphere to network of wormlike micelles over 2 h without the need of stirring. The second part of the thesis begins by describing a modular approach for preparing polyferrocenyldimethylsilane (PFS) block copolymers via a Cu-catalyzed alkyne/azide coupling reaction to covalently combine two homopolymers synthesized separately. This strategy opens the door to a broad library of novel functional PFS block copolymers, for example, poly(ferrocenyldimethylsilane-b-N-isopropyl acrylamide) (PFS-b-PNIPAM). In an attempt to expand our understanding of PFS block copolymer self-assembly in polar solvents, I investigated the self-assembly of a new polymer (PFS26-b-PNIPAM105) in alcohol solvents. When the block polymer was dissolved in methanol, ethanol and 2-propanol, it formed long fiber-like micelles with uniform width. I also showed that micelles of this polymer underwent seeded growth in methanol, leading to cylindrical micelles that were nearly mono- dispersed in length.
Reducing the Area and Energy of Coherence Directories in Multicore Processors
Keywords: computer science
multiprocessors
computer architecture
cache coherence

A key challenge in architecting a multicore processor is efficiently maintaining cache coherence. Directory protocols offer a scalable, bandwidth-efficient solution to this problem, but unfortunately they incur significant area overheads. This dissertation proposes three novel coherence directory designs that address the challenge of maintaining coherence in multicore processors, while reducing the area and energy overheads of the directory structure. Firstly, I propose the Phantom directory that leverages the abundance of storage in large shared caches to reduce the area devoted to a dedicated coherence directory. This approach faces a significant challenge since an access to the shared cache typically requires more energy than for a smaller dedicated directory. Phantom attempts to overcome this challenge by exploiting the spatial locality common to most applications, and by utilizing a very small dedicated directory cache, but the costs of accessing the shared cache still outweigh Phantom's area savings. Building upon the simple observation that at any point in time, large, continuous chunks of memory are often accessed by only a single core, my second proposed design, the multi-grain directory (MGD), takes advantage of this common application behaviour to reduce the directory size by tracking coherence at multiple different granularities. I demonstrate that a practical dual-grain directory (DGD) provides a robust solution, reducing directory area by 41% while maintaining good performance across a variety of workloads. While MGD provides a practical approach to reducing directory area, my third proposed design, the Tagless directory, takes a more innovative approach to achieving true scalability. Tagless embraces imprecision by embedding sharing information in a number of space-efficient Bloom filters. Careful consideration produces an elegant design with robust performance comparable to an ideal coherence directory. For a sixteen core processor, Tagless reduces directory area by up to 70% while reducing cache and directory energy consumption. My analysis also indicates that Tagless continues to provide an area and energy efficient directory as processors scale to tens or even hundreds of cores. These three innovative designs advance the state-of-the-art by providing more area and energy efficient coherence directories to allow multicore processors to scale to tens or hundreds of cores.
Strategic Entry Decisions, Accounting Signals, and Risk Management Disclosure
Keywords: Hedge accounting
Proprietary costs
Disclosure
U.S. airline industry
SFAS 133
SFAS 161
Entry game
Economic consequences

This dissertation investigates the economic consequences from hedge accounting signals and risk management disclosure. I first examine the product market consequences to these accounting signals and related disclosure in Chapter 1, then stock market reactions to disclosure requirements in Chapter 2. Chapter 1 examines potential entrants’ strategic entry decisions in response to incumbents’ accounting information and related disclosure. I predict that potential entrants are more likely to enter markets in which the incumbents’ accounting information suggests higher future production costs that are specific to the incumbents themselves. I further hypothesize that the relation is stronger when the accounting signals are accompanied by more disclosure. Using detailed U.S. airline industry data and hedge accounting disclosure under SFAS 133, I find that potential entrants are more likely to enter routes in which the incumbents’ lower accumulated other comprehensive income from fuel hedges suggests their higher future production costs. This entry pattern is stronger when incumbents have more transparent annual report disclosure regarding their fuel hedge programs. The entry pattern is also stronger after a systematic increase in risk management disclosure requirements following the (exogenous) adoption of SFAS 161. Chapter 2 analyzes stock returns of U.S. airlines around events leading up to the adoption of SFAS 161. SFAS 161 enhanced the disclosure requirements for derivatives and hedging activities. I find that U.S. airlines experienced statistically significant positive returns around the key events leading up to the adoption of SFAS 161. I then examine the cross-sectional variation of the returns around these events. Regression results provide initial support for the real effects theory that greater disclosure requirements could distort firms’ hedging and production decisions and lead to suboptimal behavior. In summary, this dissertation provides evidence that competitors use hedge accounting signals and related disclosure in making product market decisions. Meanwhile, additional risk-management disclosures may also distort firms’ hedging and production behavior, leading to suboptimal decisions. This dissertation sheds light on the ongoing projects by the FASB and the IASB on hedge accounting and disclosure and informs the regulators that costs and benefits should be weighted in hedge accounting policy setting.
The Relationship of Right: A Constitutive Vindication of Human Rights
Keywords: Human Rights
Immanuel Kant
Rights Theory
Justice
Coherentism

What is the fundamental justification of the idea of human rights? In this dissertation I argue that human rights are justified in virtue of the special role they play in practical thought: they function as the constitutive conditions of the relationship of right. This answer has two distinctive features: it justifies human rights non-instrumentally and relationally, as those claim rights universally necessary for relating to each other as juridical equals, as lacking authority over one another. This constitutive argument for human rights contrasts with the predominant theories of human rights, which tend to justify human rights instrumentally as means for the protection of an independently intelligible (and non-relational) purpose (e.g., basic needs, urgent interests, autonomy, capacity-development). A strong reason for endorsing the account proposed here is that it explains better than its instrumentalist competitors the universal validity of human rights while offering a more robust response against the human rights skeptic. Furthermore, this constitutive argument gives us the resources for seeing how human rights form an indivisible whole comprising civil, political, social, economic and cultural rights and how human rights structure an international order of peace. My account thus promises to offer a much-needed defense of the ideals enshrined in the Universal Declaration of Human Rights.
Quantum Control of Vibrational States in an Optical Lattice
Keywords: Quantum Control
Optical Lattice
Vibrational States

In this thesis, I present an experimental study of quantum control techniques for transferring population between vibrational states of atoms trapped in an optical lattice. Results from a range of techniques are compared, including techniques tested previously in the same system. In the study of the Adiabatic Rapid Passage (ARP) technique, control of population transfer is realized through varying the chirp rate and modulation amplitude of a frequency-chirped sinusoidal displacement of the lattice. Meanwhile, dependence of population transfer on the chirp direction is observed, which is explained by a model of ARP in a 3-level system. In the study of the coherent control technique, interference between a one-phonon transition at 2\omega and a two-phonon transition at omega is experimentally demonstrated. The omega and 2\omega transitions are realized by sinusoidally displacing the optical lattice at omega and sinusoidally modulating the lattice depth at 2\omega, respectively. The branching ratio of transitions to the first excited state and to higher excited states is controlled by varying the relative phase between these two pathways. The highest measured branching ratio of 17\pm2 is achieved among all the experiments using this coherent control scheme. In the study of the GRadient Ascent Pulse Engineering (GRAPE) technique, a "pulse" involving both displacement and depth-modulation of the lattice is used to transfer population. This pulse is theoretically engineered with the GRAPE algorithm to optimize the fidelity between the first excited state and the final state, when the lattice Hamiltonian without gravity for a specific lattice depth is considered. The experimental result shows that there is almost no excitation into higher excited states during population transfer from the ground to the first excited state, even when this process is affected by gravity and inhomogeneous broadening in reality. By comparing all the techniques, the GRAPE technique is found to be the best in terms of increasing population transfer into the first excited state while reducing excitation into higher excited states. On the other hand, the ARP technique creates the highest normalized population inversion, a ratio of the difference to the sum of the ground and the first excited state populations.
Predictive Gaussian Classification of Functional MRI Data
Keywords: fMRI
data analysis
principal components analysis
machine learning

This thesis presents an evaluation of algorithms for classification of functional MRI data. We evaluated the performance of probabilistic classifiers that use a Gaussian model against a popular non-probabilistic classifier (support vector machine, SVM). A pool of classifiers consisting of linear and quadratic discriminants, linear and non-linear Gaussian Naive Bayes (GNB) classifiers, and linear SVM, was evaluated on several sets of real and simulated fMRI data. Performance was measured using two complimentary metrics: accuracy of classification of fMRI volumes within a subject, and reproducibility of within-subject spatial maps; both metrics were computed using split-half resampling. Regularization parameters of multivariate methods were tuned to optimize the out-of-sample classification and/or within-subject map reproducibility. SVM showed no advantage in classification accuracy over Gaussian classifiers. Performance of SVM was matched by linear discriminant, and at times outperformed by quadratic discriminant or nonlinear GNB. Among all tested methods, linear and quadratic discriminants regularized with principal components analysis (PCA) produced spatial maps with highest within-subject reproducibility. We also demonstrated that the number of principal components that optimizes the performance of linear / quadratic discriminants is sensitive to the mean magnitude, variability and connectivity of simulated active signal. In real fMRI data, this number is correlated with behavioural measures of post-stroke recovery , and, in a separate study, with behavioural measures of self-control. Using the data from a study of cognitive aspects of aging, we accurately predicted the age group of the subject from within-subject spatial maps created by our pool of classifiers. We examined the cortical areas that showed difference in recruitment in young versus older subjects; this difference was demonstrated to be primarily driven by more prominent recruitment of task-positive network in older subjects. We conclude that linear and quadratic discriminants with PCA regularization are well-suited for fMRI data classification, particularly for within-subject analysis.
Psychology and the Social Scientific Construction of Prejudice: Lay Encounters with the Implicit Association Test
Keywords: prejudice
implicit association test
history and theory of psychology
public understanding of science

Implicit prejudice, and in particular, the Implicit Association Test (IAT), are paradigmatic examples of psychological concepts and research methods that have recently enjoyed great publicity and accessibility. However, little is known about the possible reflexive consequences of this popularization for the public understanding of prejudice, and by implication, for the formulation of social policy aimed at the reduction of prejudice and racism. Specifically, how does the public interpret and contextualize the claims of the IAT and implicit prejudice? With what social and political preoccupations does this operationalization of implicit prejudice resonate? Furthermore, how do members of the public experience and interpret the IAT as both a scientific instrument and as a bearer of psychological truth? In answer to these questions, this dissertation comprises a report of two empirical studies of public encounters with the IAT and the concepts of implicit prejudice. The first of these focused on popular responses to IAT research in the New York Times. Employing a discourse analytic approach to reader comments, it identified the social and psychological concerns against which the public makes sense of the IAT. In responding to the IAT, readers drew on skeptical and confessional discourses to position themselves reflexively in relation to its claims. I argue that these discourses constitute a space within which strong injunctions to self-scrutiny, impartiality and objectivity are established as moral-psychological ideals. Building on these findings, the second study examined the IAT as a discursive practice through a focus on the lived experience of taking the test. Recruited participants took the IAT, and were subsequently interviewed to elicit moment-by-moment accounts of this process. Hermeneutic-phenomenological analysis of these accounts revealed thematic concerns that both resonated with and augmented those in the analysis of public discourse. In particular, the IAT was experienced as a vivid demonstration of the operationalization of "implicit bias". I argue that the test embodies and communicates this paradigm to test-takers, and therefore functions as a psychological pedagogical tool. The dissertation closes by discussing the implications of these analyses for public understandings of, and responses to, prejudice.
Frequency-shifted Interferometry for Fiber-optic Sensing
Keywords: fiber-optics
fiber-optic sensing
cavity ring-down
sensor multiplexing

This thesis studies frequency-shifted interferometry (FSI), a useful and versatile technique for fiber-optic sensing. I first present FSI theory by describing practical FSI configurations and discussing the parameters that affect system performance. Then, I demonstrate the capabilities of FSI in fiber-optic sensor multiplexing and high sensitivity chemical analysis. We implemented a cryogenic liquid level sensing system in which an array of 3 fiber Bragg grating (FBG) based sensors was interrogated by FSI. Despite sensors' spectral overlap, FSI is able to separate sensor signals according to their spatial locations and to measure their spectra, from which whether a sensor is in liquid or air can be unambiguously determined. I showed that a broadband source paired with a fast tunable filter can be used in FSI systems as the light source. An array of 9 spectrally overlapping FBGs was successfully measured by such a system, indicating the potential of system cost reduction as well as measurement speed improvement. I invented the the FSI-CRD technique, a highly sensitive FSI-based fiber cavity ring-down (CRD) method capable of deducing minuscule loss change in a fiber cavity from the intensity decay rate of continuous-wave light circulating in the cavity. As a proof-of-principle experiment, I successfully measured the fiber bend loss introduced in the fiber cavity with FSI-CRD, which was found to be 0.172 dB/m at a bend radius of 12.5 mm. We then applied FSI-CRD to evanescent-field sensing. We incorporated fiber tapers as the sensor head in the system and measured the concentration of 1-octyne solutions. A minimum detectable 1-octyne concentration of 0.29% was achieved with measurement sensitivity of 0.0094 dB/% 1-octyne. The same system also accurately detected the concentration change of sodium chloride (NaCl) and glucose solutions. Refractive index sensitivity of 1 dB/RIU with a measurement error of 1*10^-4 dB was attined for NaCl solutions. Finally, I proposed a theoretical model to study the polarization effects in FSI systems. Preliminary results show that the model can already explain the experimental observations. It not only provides insight into how to improve system performance but also suggests potential new applications of the technique.
Energy Transfer at the Molecular Scale: Open Quantum Systems Methodologies
Keywords: quantum dynamics
open quantum system
Markovian process
energy transfer
master equations
path integral

Understanding energy transfer at the molecular scale is both essential for the design of novel molecular level devices and vital for uncovering the fundamental properties of non-equilibrium open quantum systems. In this thesis, we first establish the connection between molecular scale devices -- molecular electronics and phononics -- and open quantum system models. We then develop theoretical tools to study various properties of these models. We extend the standard master equation method to calculate the steady state thermal current and conductance coefficients. We then study the scaling laws of the thermal current with molecular chain size and energy, and apply this tool to investigate the onset of nonlinear thermal current - temperature characteristics, thermal rectification and negative differential conductance. Our master equation technique is valid in the ``on-resonance" regime, referring to the situation in which bath modes in resonance with the subsystem modes are thermally populated. In the opposite ``off-resonance" limit, we develop the Energy Transfer Born-Oppenheimer method to obtain the thermal current scaling without the need to solve for the subsystem dynamics. Finally, we develop a mapping scheme that allows the dynamics of a class of open quantum systems containing coupled subsystems to be treated by considering the separate dynamics in different subsections of the Hilbert space. We combine this mapping scheme with path integral numerical simulations to explore the rich phenomenon of entanglement dynamics within a dissipative two-qubit model. The formalisms developed in this thesis could be applied for the study of energy transfer in different realizations, including molecular electronic junctions, donor-acceptor molecules, artificial solid state qubits and cold-atom lattices.