An investigation into the characteristics of equity volatility and its implications for derivative strategies

The development of an e¤ective mechanism for pricing options has inspired a large volume of academic research and has ultimately changed the landscape of the �nancial markets. Since the publication of Black and Scholes�(1973) seminal paper on option pricing, the �nance literature has explored and at least partially resolved many of the limitations associated with the original model. The reality of stochastic volatility contradicts a key assumption of the Black-Scholes model and addressing this has motivated the development of more appropriate volatility models. The improved speci�cation and forecasting of asset price volatility has been influenced by the demands of risk management and portfolio functions. The increased use of quantitative methods in portfolio management is due, in part at least, to successful academic research into asset volatility. Existing research is extended in this thesis by �rst examining the forecasting power of implied volatilities from traded UK equity options. Composite implied volatilities are created using weighting techniques that efficiently capture the predictive information in traded options. These implied volatilities are benchmarked against subsequently realized stock price volatility estimated from high-frequency stock price data. The predictive information provided by the options market is compared against that available from sophisticated statistical models such as the generalized autoregressive conditional heteroskedastic (GARCH) model and the exponential-GARCH (E-GARCH) model. Comparison of implied and statistical forecasts is carried out over a number of forecasting horizons using regression analysis as well as robust pairwise tests. The second part of this thesis uses semi-parametric techniques to examine the long-run dynamics of UK equity volatility. The nature of volatility persistence found in both the implied and realized volatility series of a number of companies is carefully examined. Testing the time-domain properties of the volatility series identities the extent to which structural breaks in volatility contribute to observed levels of persistence in our sample of companies. The nature of the long-run relationship between implied and realized volatility is also examined. The relevance of these empirically observed volatility characteristics is examined in the final part of this thesis. Using dynamic programming techniques together with Monte Carlo simulation, optimal portfolio weights are determined for a derivative strategy implemented in discrete time. The derivative strategy is activated across a six-month investment horizon and rebalancing occurs at the beginning of each month. The creation of a series of variance grid points at each time step makes the dynamic programming approach computationally feasible. Progressing backwards from the end of the investment horizon, optimal portfolio weights are found for each of the variance grid points. The optimisation procedure assumes that volatility is driven by a short-memory affine process. The economic cost associated with omitting long-memory effects is isolated by simulating a fractionally integrated process across the same investment horizon and applying the previously assigned weights at each time step. The relevance of omitting possible regime shifts in the volatility process are evaluated in the same manner. Portfolio outcomes are derived for the optimal case, that is, when actual volatility follows a short memory process. Outcomes are also derived for the alternative conditions, that is, a 'true' long memory, fractionally integrated process as well as the 'spurious' long memory or regime-switching case. The impact of volatility mis-specification is captured in the characteristics of the portfolio's terminal wealth distribution

A thrombospondin in the anthozoan Nematostella vectensis is associated with the nervous system and upregulated during regeneration

Thrombospondins are multimeric extracellular matrix glycoproteins that play important roles in development, synaptogenesis and wound healing in mammals. We previously identified four putative thrombospondins in the genome of the starlet sea anemone Nematostella vectensis. This study presents the first analysis of these thrombospondins, with the goals of understanding fundamental roles of thrombospondins in the Eumetazoa. Reverse transcriptase PCR showed that each of the N. vectensis thrombospondins (Nv85341, Nv22035, Nv168100 and Nv30790) is transcribed. Three of the four thrombospondins include an RGD or KGD motif in their thrombospondin type 3 repeats at sites equivalent to mammalian thrombospondins, suggesting ancient roles as RGD integrin ligands. Phylogenetic analysis based on the C-terminal regions demonstrated a high level of sequence diversity between N. vectensis thrombospondins. A full-length cDNA sequence was obtained for Nv168100 (NvTSP168100), which has an unusual domain organization. Immunohistochemistry with an antibody to NvTSP168100 revealed labeling of neuron-like cells in the mesoglea of the retractor muscles and the pharynx. In situ hybridization and quantitative PCR showed that NvTSP168100 is upregulated during regeneration. Immunohistochemistry of the area of regeneration identified strong immunostaining of the glycocalyx, the carbohydrate-rich matrix coating the epidermis, and electron microscopy identified changes in glycocalyx organization during regeneration. Thus, N. vectensis thrombospondins share structural features with thrombospondins from mammals and may have roles in the nervous system and in matrix reorganization during regeneration

PGC-1α is coupled to HIF-1α-dependent gene expression by increasing mitochondrial oxygen consumption in skeletal muscle cells

Mitochondrial biogenesis occurs in response to increased cellular ATP demand. The mitochondrial electron transport chain requires molecular oxygen to produce ATP. Thus, increased ATP generation after mitochondrial biogenesis results in increased oxygen demand that must be matched by a corresponding increase in oxygen supply. We found that overexpression of peroxisome proliferator-activated receptor-γ coactivator 1α (PGC-1α), which increases mitochondrial biogenesis in primary skeletal muscle cells, leads to increased expression of a cohort of genes known to be regulated by the dimeric hypoxia-inducible factor (HIF), a master regulator of the adaptive response to hypoxia. PGC-1α-dependent induction of HIF target genes under physiologic oxygen concentrations is not through transcriptional coactivation of HIF or up-regulation of HIF-1α mRNA but through HIF-1α protein stabilization. It occurs because of intracellular hypoxia as a result of increased oxygen consumption after mitochondrial biogenesis. Thus, we propose that at physiologic oxygen concentrations, PGC-1α is coupled to HIF signaling through the regulation of intracellular oxygen availability, allowing cells and tissues to match increased oxygen demand after mitochondrial biogenesis with increased oxygen supply

Discourse or dialogue? Habermas, the Bakhtin Circle, and the question of concrete utterances

This is the author's accepted manuscript. The final publication is available at Springer via the link below.This article argues that the Bakhtin Circle presents a more realistic theory of concrete dialogue than the theory of discourse elaborated by Habermas. The Bakhtin Circle places speech within the “concrete whole utterance” and by this phrase they mean that the study of everyday language should be analyzed through the mediations of historical social systems such as capitalism. These mediations are also characterized by a determinate set of contradictions—the capital-labor contradiction in capitalism, for example—that are reproduced in unique ways in more concrete forms of life (the state, education, religion, culture, and so on). Utterances always dialectically refract these processes and as such are internal concrete moments, or concrete social forms, of them. Moreover, new and unrepeatable dialogic events arise in these concrete social forms in order to overcome and understand the constant dialectical flux of social life. But this theory of dialogue is different from that expounded by Habermas, who tends to explore speech acts by reproducing a dualism between repeatable and universal “abstract” discursive processes (commonly known as the ideal speech situation) and empirical uses of discourse. These critical points against Habermas are developed by focusing on six main areas: sentences and utterances; the lifeworld and background language; active versus passive understandings of language; validity claims; obligation and relevance in language; and dialectical universalism

Neutral-Current Atmospheric Neutrino Flux Measurement Using Neutrino-Proton Elastic Scattering in Super-Kamiokande

Recent results show that atmospheric $\nu_\mu$ oscillate with $\delta m^2 \simeq 3 \times 10^{-3}$ eV$^2$ and $\sin^2{2\theta_{atm}} \simeq 1$, and that conversion into $\nu_e$ is strongly disfavored. The Super-Kamiokande (SK) collaboration, using a combination of three techniques, reports that their data favor $\nu_\mu \to \nu_\tau$ over $\nu_\mu \to \nu_{sterile}$. This distinction is extremely important for both four-neutrino models and cosmology. We propose that neutrino-proton elastic scattering ($\nu + p \to \nu + p$) in water \v{C}erenkov detectors can also distinguish between active and sterile oscillations. This was not previously recognized as a useful channel since only about 2% of struck protons are above the \v{C}erenkov threshold. Nevertheless, in the present SK data there should be about 40 identifiable events. We show that these events have unique particle identification characteristics, point in the direction of the incoming neutrinos, and correspond to a narrow range of neutrino energies (1-3 GeV, oscillating near the horizon). This channel will be particularly important in Hyper-Kamiokande, with $\sim 40$ times higher rate. Our results have other important applications. First, for a similarly small fraction of atmospheric neutrino quasielastic events, the proton is relativistic. This uniquely selects $\nu_\mu$ (not $\bar{\nu}_\mu$) events, useful for understanding matter effects, and allows determination of the neutrino energy and direction, useful for the $L/E$ dependence of oscillations. Second, using accelerator neutrinos, both elastic and quasielastic events with relativistic protons can be seen in the K2K 1-kton near detector and MiniBooNE.Comment: 10 pages RevTeX, 8 figure

Detection of Supernova Neutrinos by Neutrino-Proton Elastic Scattering

We propose that neutrino-proton elastic scattering, $\nu + p \to \nu + p$, can be used for the detection of supernova neutrinos in scintillator detectors. Though the proton recoil kinetic energy spectrum is soft, with $T_p \simeq 2 E_\nu^2/M_p$, and the scintillation light output from slow, heavily ionizing protons is quenched, the yield above a realistic threshold is nearly as large as that from $\bar{\nu}_e + p \to e^+ + n$. In addition, the measured proton spectrum is related to the incident neutrino spectrum, which solves a long-standing problem of how to separately measure the total energy and temperature of $\nu_\mu$, $\nu_\tau$, $\bar{\nu}_\mu$, and $\bar{\nu}_\tau$. The ability to detect this signal would give detectors like KamLAND and Borexino a crucial and unique role in the quest to detect supernova neutrinos.Comment: 10 pages, 9 figures, revtex

A Proposal for a Three Detector Short-Baseline Neutrino Oscillation Program in the Fermilab Booster Neutrino Beam

A Short-Baseline Neutrino (SBN) physics program of three LAr-TPC detectors located along the Booster Neutrino Beam (BNB) at Fermilab is presented. This new SBN Program will deliver a rich and compelling physics opportunity, including the ability to resolve a class of experimental anomalies in neutrino physics and to perform the most sensitive search to date for sterile neutrinos at the eV mass-scale through both appearance and disappearance oscillation channels. Using data sets of 6.6e20 protons on target (P.O.T.) in the LAr1-ND and ICARUS T600 detectors plus 13.2e20 P.O.T. in the MicroBooNE detector, we estimate that a search for muon neutrino to electron neutrino appearance can be performed with ~5 sigma sensitivity for the LSND allowed (99% C.L.) parameter region. In this proposal for the SBN Program, we describe the physics analysis, the conceptual design of the LAr1-ND detector, the design and refurbishment of the T600 detector, the necessary infrastructure required to execute the program, and a possible reconfiguration of the BNB target and horn system to improve its performance for oscillation searches.Comment: 209 pages, 129 figure

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal