Dynamics of Multivariate Return Series of U.S. Automotive Stock Companies in Conditions of Crisis

This article contains an analysis of dynamic interrelations between log-returns series of three automotive companies listed on the New York Stock Exchange: GM, F and DAI. We consider two periods: before and during crisis. We apply DiagBEKK model and we calculate dynamic conditional correlations. As a result of our research we found that in conditions of crisis there were strong connections between considered stock companies.DiagBEKK model, dynamic conditional correlation.

Cuntz-Krieger algebras associated with Hilbert C∗C^*-quad modules of commuting matrices

Let ${\cal O}_{{\cal H}^{A,B}_\kappa}$ be the $C^*$-algebra associated with the Hilbert $C^*$-quad module arising from commuting matrices $A,B$ with entries in $\{0,1\}$. We will show that if the associated tiling space $X_{A,B}^\kappa$ is transitive, the $C^*$-algebra ${\cal O}_{{\cal H}^{A,B}_\kappa}$ is simple and purely infinite. In particulr, for two positive integers $N,M$, the $K$-groups of the simple purely infinite $C^*$-algebra ${\cal O}_{{\cal H}^{[N],[M]}_\kappa}$ are computed by using the Euclidean algorithm.Comment: 19 page

Construction and validation of the self-conscious emotions at work scale

The present study reports on the construction and validation of a new assessment instrument for self-conscious emotions in the work context, namely the Self-Conscious Emotions at Work Scale (SCEWS). In eight typical self-conscious work scenarios respondents have to indicate their emotional reaction in terms of 20 appraisals, subjective experiences, and action tendencies that are relevant and representative for the domain of self-conscious emotions. In total 512 students and 467 working adults completed the SCEWS and reported the frequency of positive emotions, anger, anxiety and sadness. In both samples a three-factorial structure emerged with a guilt, a shame/humiliation, and an anger in self-conscious situations factor. These three self-conscious emotion factors correlated differentially and in a predicted way with the frequency of emotions. Guilt-proneness was predicted to be psychologically constructive and correlated to the frequency of positive emotions. The proneness to shame/humiliation was expected to relate to internalising psychopathological tendencies, and positively correlated to a frequency of anxiety and sadness. Proneness to anger in self-conscious situations was expected to relate to externalising psychopathological tendencies and correlated with the frequency of anger in general. The present study demonstrates that self-conscious emotions can be validly measured in the work context. The new instrument allows for the systematic study of the role of self-conscious emotions in work and organisational behaviour

Properties which normal operators share with normal derivations and related operators

Let $S$ and $T$ be (bounded) scalar operators on a Banach space \scr X and let $C(T,S)$ be the map on \scr B(\scr X), the bounded linear operators on \scr X, defined by $C(T,S)(X)=TX-XS$ for $X$ in \scr B(\scr X). This paper was motivated by the question: to what extent does $C(T,S)$ behave like a normal operator on Hilbert space? It will be shown that $C(T,S)$ does share many of the special properties enjoyed by normal operators. For example, it is shown that the range of $C(T,S)$ meets its null space at a positive angle and that $C(T,S)$ is Hermitian if $T$ and $S$ are Hermitian. However, if \scr X is a Hilbert space then $C(T,S)$ is a spectral operator if and only if the spectrum of $T$ and the spectrum of $S$ are both finite

Large gap asymptotics for random matrices

We outline an approach recently used to prove formulae for the multiplicative constants in the asymptotics for the sine-kernel and Airy-kernel determinants appearing in random matrix theory and related areas.Comment: 7 page

Some results on two-sided LIL behavior

Let {X,X_n;n\geq 1} be a sequence of i.i.d. mean-zero random variables, and let S_n=\sum_{i=1}^nX_i,n\geq 1. We establish necessary and sufficient conditions for having with probability 1, 0<lim sup_{n\to \infty}|S_n|/\sqrtnh(n)<\infty, where h is from a suitable subclass of the positive, nondecreasing slowly varying functions. Specializing our result to h(n)=(\log \log n)^p, where p>1 and to h(n)=(\log n)^r, r>0, we obtain analogues of the Hartman-Wintner LIL in the infinite variance case. Our proof is based on a general result dealing with LIL behavior of the normalized sums {S_n/c_n;n\ge 1}, where c_n is a sufficiently regular normalizing sequence.Comment: Published at http://dx.doi.org/10.1214/009117905000000198 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

Solitons and vortices in ultracold fermionic gases

We investigate the possibilities of generation of solitons and vortices in a degenerate gas of neutral fermionic atoms. In analogy with, already experimentally demonstrated, technique applied to gaseous Bose-Einstein condensate we propose the phase engineering of a Fermi gas as a practical route to excited states with solitons and vortices. We stress that solitons and vortices appear even in a noninteracting fermionic gas. For solitons, in a system with sufficiently large number of fermions and appropriate trap configuration, the Pauli blocking acts as the interaction between particles.Comment: 4 pages, 5 figures many new result

Tameness and Artinianness of Graded Generalized Local Cohomology Modules

Let $R=\bigoplus_{n\geq 0}R_n$, \fa\supseteq \bigoplus_{n> 0}R_n and $M$ and $N$ be a standard graded ring, an ideal of $R$ and two finitely generated graded $R$-modules, respectively. This paper studies the homogeneous components of graded generalized local cohomology modules. First of all, we show that for all $i\geq 0$, H^i_{\fa}(M, N)_n, the $n$-th graded component of the $i$-th generalized local cohomology module of $M$ and $N$ with respect to \fa, vanishes for all $n\gg 0$. Furthermore, some sufficient conditions are proposed to satisfy the equality \sup\{\en(H^i_{\fa}(M, N))| i\geq 0\}= \sup\{\en(H^i_{R_+}(M, N))| i\geq 0\}. Some sufficient conditions are also proposed for tameness of H^i_{\fa}(M, N) such that i= f_{\fa}^{R_+}(M, N) or i= \cd_{\fa}(M, N), where f_{\fa}^{R_+}(M, N) and \cd_{\fa}(M, N) denote the $R_+$-finiteness dimension and the cohomological dimension of $M$ and $N$ with respect to \fa, respectively. We finally consider the Artinian property of some submodules and quotient modules of H^j_{\fa}(M, N), where $j$ is the first or last non-minimax level of H^i_{\fa}(M, N).Comment: 18pages, with some revisions and correction

Phishing Email Detection based on Entity Recognition

Phishing je vážný problém, který způsobuje nezanedbatelné finanční ztráty mnoha organizacím po celém světě. Současné metody pro detekci phishingu pro český jazyk jsou nedostatečné. Rozpoznávaní entit (NER) bylo úspěšně použito pro detekci phishing emailů v anglickém i jiných jazycích. Cílem této práce je použít NER pro určení cíle potenciálního phishing emailu a použít tuto informaci k detekci phishingu. Vyvinuli jsme rešení schopné detekovat cíl potenciálního phishing emailu. Naše řešení funguje dobře pro významné phishing cíle jako třeba finanční a technické společnosti. Dokázali jsme, že detekce phishing cíle je zdrojem cenných informací o phishing emailu a může být použita pro detekci phishingu. Náše řešení pro rozpoznání phishingu dosáhlo 86.9% úspěšnosti při použití pouze jedné vlastnosti vygenerované pomocí detekce phishing cíle. Při použití bežně používaných vlastností naše řešení dosáhlo 97.7% úspěšnosti. Přidání vlastností založených na detekci phishing cíle způsobilo malé zlepšení. Rešení dosáhlo 98% úspěšnosti. Pro rozpoznávání entit jsme použili Nametag, současně nepřekonaný NER pro český jazyk. Natrénovali jsme vlastní modely pro Nametag, použili jsme původní a vlastní přidaná data. NER jsme použili pro rozpoznání entit v emailu. Použili jsme vlastní řešení pro mapování jmen organizací na domény pomocí dat z ARES a Firmy.cz. Namapované domény jsme použili pro určení cíle potenciálního phishing útoku. Model pro Nametag byl otestován proti datům pro úkol z CoNLL2003 zabývající se rozpoznáváním entit. Detekce phishing cíle byla otestována pomocí 2628 emailů z dat od Email.cz. Nakonec jsme naše řešení pro detekci phishingu otestovali pomocí datasetu obsahujícího 3744 emailů z veřejných i neveřejných zdrojů.Phishing is a serious problem that causes a significant financial loss to many companies wolrdwide. Current phishing detection methods for Czech language are not satisfactory. Named entity recognition (NER) was successfully used for phishing email detection in English and other languages. The goal of this thesis is to use NER to determine target of the potential phishing email and use this information to detect phishing emails. We have developed a solution that can detect target of the potential phishing email. Our solution works well for major phishing targets such as financial and technology organizations. We have proved that target detection gives a significant amount of information about the email and can be used to detect phishing. Our recognizer achieved 86.9% accuracy when using only one feature generated using target detection. When using only commonly used features the recognizer achieved 97.7% accuracy. Adding target based features gave us minor improvement and achieved 98% accuracy. For Named entity recognition we use Nametag, the state of the art NER for Czech language. We have trained our own models for Nametag using both original and custom data. NER is used to recognize organizations in email. Custom solution is used to map organizations to domains using data from ARES and Firmy.cz. Mapped domains are used to determine target of the potential phishing email. Target and collected historical data about domains is used to generate features for random forest classifier. Random forest classifier is used to detect whether or not the email is phishing attack. Nametag model was tested against CoNLL2003 shared task on Named entity recognition. Target detection solution was tested using 2628 emails from Email.cz data. Finally the phishing detection recognizer was tested using dataset containing 3744 emails from both public and private sources