High Frequency Trading and Herding

In financial markets, the potential tendency of traders to follow some type of consensus action is referred to as herding. Traders might herd intentionally (i.e. they intend to mimic others’ behaviour or follow the market consensus), or they might herd unintentionally (spurious herding). The literature shows mixed evidence of herding which mainly focuses on human traders, while herding evidence from non-human traders such as algorithmic traders and high frequency traders is absent from the herding literature. Therefore, in this thesis, the role of high frequency trading (hereafter HFT) in herding is discussed in the context of a single market and the most popular exchanges around the world. The thesis employs quotes and trade volumes to proxy HFT in the US equity market and provide evidence that HFT induces spurious herding when trading intensity is high. Moreover, the colocation start date and HFT effective date are used from ten of the most popular global exchanges to proxy the emergence of HFT and estimate the effect of HFT on herding. Again, it is shown empirically that the emergence of HFT induces herding even during the financial crisis period. Finally, the implementation of MiFID II from the beginning of 2018 allows access to data which flags algorithmic trading under different traders. Instead of using different methods to proxy algorithmic trading, we can therefore identify each algorithmic trade and estimate the effect of different traders (i.e., human traders, algorithmic traders, and market makers) on herding. The results also demonstrate significant evidence of herding. Overall, the thesis shows that HFT induces herding, given the increasing trading intensity. To best of my knowledge, this is the first time the herding literature has examined HFT and algorithmic trading or shown such findings

Using Markov Models and Statistics to Learn, Extract, Fuse, and Detect Patterns in Raw Data

Many systems are partially stochastic in nature. We have derived data driven approaches for extracting stochastic state machines (Markov models) directly from observed data. This chapter provides an overview of our approach with numerous practical applications. We have used this approach for inferring shipping patterns, exploiting computer system side-channel information, and detecting botnet activities. For contrast, we include a related data-driven statistical inferencing approach that detects and localizes radiation sources.Comment: Accepted by 2017 International Symposium on Sensor Networks, Systems and Securit

Interatomic potentials for atomistic simulations of the Ti-Al system

Semi-empirical interatomic potentials have been developed for Al, alpha-Ti, and gamma-TiAl within the embedded atomic method (EAM) by fitting to a large database of experimental as well as ab-initio data. The ab-initio calculations were performed by the linear augmented plane wave (LAPW) method within the density functional theory to obtain the equations of state for a number of crystal structures of the Ti-Al system. Some of the calculated LAPW energies were used for fitting the potentials while others for examining their quality. The potentials correctly predict the equilibrium crystal structures of the phases and accurately reproduce their basic lattice properties. The potentials are applied to calculate the energies of point defects, surfaces, planar faults in the equilibrium structures. Unlike earlier EAM potentials for the Ti-Al system, the proposed potentials provide reasonable description of the lattice thermal expansion, demonstrating their usefulness in the molecular dynamics or Monte Carlo studies at high temperatures. The energy along the tetragonal deformation path (Bain transformation) in gamma-TiAl calculated with the EAM potential is in a fairly good agreement with LAPW calculations. Equilibrium point defect concentrations in gamma-TiAl are studied using the EAM potential. It is found that antisite defects strongly dominate over vacancies at all compositions around stoichiometry, indicating that gamm-TiAl is an antisite disorder compound in agreement with experimental data.Comment: 46 pages, 6 figures (Physical Review B, in press

Scale-free memory model for multiagent reinforcement learning. Mean field approximation and rock-paper-scissors dynamics

A continuous time model for multiagent systems governed by reinforcement learning with scale-free memory is developed. The agents are assumed to act independently of one another in optimizing their choice of possible actions via trial-and-error search. To gain awareness about the action value the agents accumulate in their memory the rewards obtained from taking a specific action at each moment of time. The contribution of the rewards in the past to the agent current perception of action value is described by an integral operator with a power-law kernel. Finally a fractional differential equation governing the system dynamics is obtained. The agents are considered to interact with one another implicitly via the reward of one agent depending on the choice of the other agents. The pairwise interaction model is adopted to describe this effect. As a specific example of systems with non-transitive interactions, a two agent and three agent systems of the rock-paper-scissors type are analyzed in detail, including the stability analysis and numerical simulation. Scale-free memory is demonstrated to cause complex dynamics of the systems at hand. In particular, it is shown that there can be simultaneously two modes of the system instability undergoing subcritical and supercritical bifurcation, with the latter one exhibiting anomalous oscillations with the amplitude and period growing with time. Besides, the instability onset via this supercritical mode may be regarded as "altruism self-organization". For the three agent system the instability dynamics is found to be rather irregular and can be composed of alternate fragments of oscillations different in their properties.Comment: 17 pages, 7 figur

Interesting magnetic properties of Fe1−x_{1-x}Cox_xSi alloys

Solid solution between nonmagnetic narrow gap semiconductor FeSi and diamagnetic semi-metal CoSi gives rise to interesting metallic alloys with long-range helical magnetic ordering, for a wide range of intermediate concentration. We report various interesting magnetic properties of these alloys, including low temperature re-entrant spin-glass like behaviour and a novel inverted magnetic hysteresis loop. Role of Dzyaloshinski-Moriya interaction in the magnetic response of these non-centrosymmetric alloys is discussed.Comment: 11 pages and 3 figure

Charmless Exclusive Baryonic B Decays

We present a systematical study of two-body and three-body charmless baryonic B decays. Branching ratios for two-body modes are in general very small, typically less than $10^{-6}$, except that \B(B^-\to p \bar\Delta^{--})\sim 1\times 10^{-6}. In general, $\bar B\to N\bar\Delta>\bar B\to N\bar N$ due to the large coupling constant for $\Sigma_b\to B\Delta$. For three-body modes we focus on octet baryon final states. The leading three-dominated modes are $\bar B^0\to p\bar n\pi^-(\rho^-), n\bar p\pi^+(\rho^+)$ with a branching ratio of order $3\times 10^{-6}$ for $\bar B^0\to p\bar n\pi^-$ and $8\times 10^{-6}$ for $\bar B^0\to p\bar n\rho^-$. The penguin-dominated decays with strangeness in the meson, e.g., $B^-\to p\bar p K^{-(*)}$ and $\bar B^0\to p\bar n K^{-(*)}, n\bar n \bar K^{0(*)}$, have appreciable rates and the $N\bar N$ mass spectrum peaks at low mass. The penguin-dominated modes containing a strange baryon, e.g., $\bar B^0\to \Sigma^0\bar p\pi^+, \Sigma^-\bar n\pi^+$, have branching ratios of order $(1\sim 4)\times 10^{-6}$. In contrast, the decay rate of $\bar B^0\to\Lambda\bar p\pi^+$ is smaller. We explain why some of charmless three-body final states in which baryon-antibaryon pair production is accompanied by a meson have a larger rate than their two-body counterparts: either the pole diagrams for the former have an anti-triplet bottom baryon intermediate state, which has a large coupling to the $B$ meson and the nucleon, or they are dominated by the factorizable external $W$-emission process.Comment: 46 pages and 3 figures, to appear in Phys. Rev. D. Major changes are: (i) Calculations of two-body baryonic B decays involving a Delta resonance are modified, and (ii) Penguin-dominated modes B-> Sigma+N(bar)+p are discusse

CP violating neutrino oscillation and uncertainties in Earth matter density

We propose a statistical formulation to estimate possible errors in long baseline neutrino oscillation experiments caused by uncertainties in the Earth matter density. A quantitative investigation of the effect is made on the CP asymmetry in future neutrino factory experiments.Comment: Latex, 10 pages, 5 figure

Intraperitoneal delivery of paclitaxel by poly(ether-anhydride) microspheres effectively suppresses tumor growth in a murine metastatic ovarian cancer model

Intraperitoneal (IP) chemotherapy is more effective than systemic chemotherapy for treating advanced ovarian cancer, but is typically associated with severe complications due to high dose, frequent administration schedule, and use of non-biocompatible excipients/delivery vehicles. Here, we developed paclitaxel (PTX)-loaded microspheres composed of di-block copolymers of poly(ethylene glycol) and poly(sebacic acid) (PEG-PSA) for safe and sustained IP chemotherapy. PEG-PSA microspheres provided efficient loading (∼13 % w/w) and prolonged release (∼13 days) of PTX. In a murine ovarian cancer model, a single dose of IP PTX/PEG-PSA particles effectively suppressed tumor growth for more than 40 days and extended the median survival time to 75 days compared to treatments with Taxol® (47 days) or IP placebo particles (34 days). IP PTX/PEG-PSA was well tolerated with only minimal to mild inflammation. Our findings support PTX/PEG-PSA microspheres as a promising drug delivery platform for IP therapy of ovarian cancer and potentially other metastatic peritoneal cancers