Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions

In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.

Sum rules and correlations in asymmetric nuclear matter

The neutron and proton single-particle spectral functions in asymmetric nuclear matter fulfill energy-weighted sum rules. The validity of these sum rules within the self-consistent Green's function approach is investigated. The various contributions to these sum rules and their convergence as a function of energy provide information about correlations induced by the realistic interaction between the nucleons. The study of the sum rules in asymmetric nuclear matter exhibits the isospin dependence of the nucleon-nucleon correlations.

Selecting from amongst non–nested conditional variance models: information criteria and portfolio determination

We consider the finite sample properties of model selection by information criteria in conditionally heteroscedastic models. Recent theoretical results show that certain popular criteria are consistent in that they will select the true model asymptotically with probability 1. To examine the empirical relevance of this property, Monte Carlo simulations are conducted for a set of non–nested data generating processes (DGPs) with the set of candidate models consisting of all types of model used as DGPs. In addition, not only is the best model considered but also those with similar values of the information criterion, called close competitors, thus forming a portfolio of eligible models. To supplement the simulations, the criteria are applied to a set of economic and financial series. In the simulations, the criteria are largely ineffective at identifying the correct model, either as best or a close competitor, the parsimonious GARCH(1, 1) model being preferred for most DGPs. In contrast, asymmetric models are generally selected to represent actual data. This leads to the conjecture that the properties of parameterizations of processes commonly used to model heteroscedastic data are more similar than may be imagined and that more attention needs to be paid to the behaviour of the standardized disturbances of such models, both in simulation exercises and in empirical modelling.

Asymmetric response of demand-supply mismatch to investor's sentiment

We look through both the demand and supply side information to understand dynamics of price determination in the real estate market and examine how accurately investors’ attitudes predict the market returns and thereby flagging off extent of any demand-supply mismatch. Our hypothesis is based on the possibility that investors’ call for action in terms of their buy/sell decision and adjustment in reservation/offer prices may indicate impending demand-supply imbalances in the market. In the process, we study several real estate sectors to inform our analysis. The timeframe of our analysis (1995-2010) allows us to observe market dynamics over several economic cycles and in various stages of those cycles. Additionally, we also seek to understand how investors’ attitude or the sentiment affects the market activity over the cycles through asymmetric responses. We test our hypothesis variously using a number of measures of market activity and attitude indicators within several model specifications. The empirical models are estimated using Vector Error Correction framework. Our analysis suggests that investors’ attitude exert strong and statistically significant feedback effects in price determination. Moreover, these effects do reveal heterogeneous responses across the real estate sectors. Interestingly, our results indicate the asymmetric responses during boom, normal and recessionary periods. These results are consistent with the theoretical underpinnings.

Facets of the polytope of the asymmetric travelling salesman problem with replenishment arcs

The Asymmetric Travelling Salesman Problem with Replenishment Arcs (RATSP) is a new class of problems arising from work related to aircraft routing. Given a digraph with cost on the arcs, a solution of the RATSP, like that of the Asymmetric Travelling Salesman Problem, induces a directed tour in the graph which minimises total cost. However the tour must satisfy additional constraints: the arc set is partitioned into replenishment arcs and ordinary arcs, each node has a non-negative weight associated with it, and the tour cannot accumulate more than some weight limit before a replenishment arc must be used. To enforce this requirement, constraints are needed. We refer to these as replenishment constraints.

In this paper, we review previous polyhedral results for the RATSP and related problems, then prove that two classes of constraints developed in V. Mak and N. Boland [Polyhedral results and exact algorithms for the asymmetric travelling salesman problem with replenishment arcs, Technical Report TR M05/03, School of Information Technology, Deakin University, 2005] are, under appropriate conditions, facet-defining for the RATS polytope.

Asymmetric recognition of good and bad news at Malaysian capital market : a pre and crisis analysis

The aim of this paper is to analyze the asymmetric recognition of good and bad news on reported earnings of Malaysian-listed firms. The study uses both descriptive and regression analyses to ascertain whether there is a contemporaneous relationship between news (good and bad) and reported earnings. The analysis is based on a sample of 150 firms listed on the Bursa Malaysia Index over a period of 10 years, from 1990 to 2000. Two regression models were adopted based on Basu (1997) and Giner and Rees (2001). The first model aims to capture asymmetric recognition of good and bad news into reported earnings while the latter model is developed to capture both asymmetric recognition of information shock and permanent earnings effect on contemporaneous earnings. The evidence from this study reported the steady increase in earnings per share till 1997. However, a drastic decline was observed for the period 1997 to 1999 because of Asian financial crisis. The findings from the regression model one suggested that the asymmetric recognition of good news was more prominent during the good time compare to bad time and vice versa. The findings from model two also suggested that autoregressive effect of permanent effect was very prominent both for crisis and non crisis periods.

Asymmetric self-learning for tackling Twitter spam drift

Spam has become a critical problem on Twitter. In order to stop spammers, security companies apply blacklisting services to filter spam links. However, over 90% victims will visit a new malicious link before it is blocked by blacklists. To eliminate the limitation of blacklists, researchers have proposed a number of statistical features based mechanisms, and applied machine learning techniques to detect Twitter spam. In our labelled large dataset, we observe that the statistical properties of spam tweets vary over time, and thus the performance of existing ML based classifiers are poor. This phenomenon is referred as 'Twitter Spam Drift'. In order to tackle this problem, we carry out deep analysis of 1 million spam tweets and 1 million non-spam tweets, and propose an asymmetric self-learning (ASL) approach. The proposed ASL can discover new information of changed tweeter spam and incorporate it into classifier training process. A number of experiments are performed to evaluate the ASL approach. The results show that the ASL approach can be used to significantly improve the spam detection accuracy of using traditional ML algorithms.

Asymmetric drift and halo flattening in disk galaxies

The main result in this work is the solution of the Jeans equations for an axisymmetric galaxy model containing a baryonic component (distributed according to a Miyamoto-Nagai profile) and a dark matter halo (described by the Binney logarithmic potential). The velocity dispersion, azimuthal velocity and some other interesting quantities such as the asymmetric drift are studied, along with the influence of the model parameters on these (observable) quantities. We also give an estimate for the velocity of the radial flow, caused by the asymmetric drift. Other than the mathematical beauty that lies in solving a model analytically, the interest of this kind of results can be mainly found in numerical simulations that study the evolution of gas flows. For example, it is important to know how certain parameters such as the shape (oblate, prolate, spherical) of a dark matter halo, or the flattening of the baryonic matter, or the mass ratio between dark and baryonic matter, have an influence on observable quantities such as the velocity dispersion. In the introductory chapter, we discuss the Jeans equations, which provide information about the velocity dispersion of a system. Next we will consider some dynamical quantities that will be useful in the rest of the work, e.g. the asymmetric drift. In Chapter 2 we discuss in some more detail the family of galaxy models we studied. In Chapter 3 we give the solution of the Jeans equations. Chapter 4 describes and illustrates the behaviour of the velocity dispersion, as a function of the several parameters, along with asymptotic expansions. In Chapter 5 we will investigate the behaviour of certain dynamical quantities for this model. We conclude with a discussion in Chapter 6.

Exact Solutions to the Symmetric and Asymmetric Vehicle Routing Problem with Simultaneous Delivery and Pick-Up

In reverse logistics networks, products (e.g., bottles or containers) have to be transported from a depot to customer locations and, after use, from customer locations back to the depot. In order to operate economically beneficial, companies prefer a simultaneous delivery and pick-up service. The resulting Vehicle Routing Problem with Simultaneous Delivery and Pick-up (VRPSDP) is an operational problem, which has to be solved daily by many companies. We present two mixed-integer linear model formulations for the VRPSDP, namely a vehicle-flow and a commodity-flow model. In order to strengthen the models, domain-reducing preprocessing techniques, and effective cutting planes are outlined. Symmetric benchmark instances known from the literature as well as new asymmetric instances derived from real-world problems are solved to optimality using CPLEX 12.1.

Photochemically induced nuclear spin polarization in reaction centers of photosystem II observed by 13C-solid-state NMR reveals a strongly asymmetric electronic structure of the P680.+ primary donor chlorophyll

We report 13C magic angle spinning NMR observation of photochemically induced dynamic nuclear spin polarization (photo- CIDNP) in the reaction center (RC) of photosystem II (PS2). The light-enhanced NMR signals of the natural abundance 13C provide information on the electronic structure of the primary electron donor P680 (chlorophyll a molecules absorbing around 680 nm) and on the pz spin density pattern in its oxidized form, P680⨥. Most centerband signals can be attributed to a single chlorophyll a (Chl a) cofactor that has little interaction with other pigments. The chemical shift anisotropy of the most intense signals is characteristic for aromatic carbon atoms. The data reveal a pronounced asymmetry of the electronic spin density distribution within the P680⨥. PS2 shows only a single broad and intense emissive signal, which is assigned to both the C-10 and C-15 methine carbon atoms. The spin density appears shifted toward ring III. This shift is remarkable, because, for monomeric Chl a radical cations in solution, the region of highest spin density is around ring II. It leads to a first hypothesis as to how the planet can provide itself with the chemical potential to split water and generate an oxygen atmosphere using the Chl a macroaromatic cycle. A local electrostatic field close to ring III can polarize the electronic charge and associated spin density and increase the redox potential of P680 by stabilizing the highest occupied molecular orbital, without a major change of color. This field could be produced, e.g., by protonation of the keto group of ring V. Finally, the radical cation electronic structure in PS2 is different from that in the bacterial RC, which shows at least four emissive centerbands, indicating a symmetric spin density distribution over the entire bacteriochlorophyll macrocycle.

Asymmetric effects of online consumer reviews

Consumers tend to seek heuristic information cues to simplify the amount of information involved in tourist decisions. Accordingly, star ratings in online reviews are a critical heuristic element of the perceived evaluation of online consumer information. The objective of this article is to assess the effect of review ratings on usefulness and enjoyment. The empirical application is carried out on a sample of 5,090 reviews of 45 restaurants in London and New York. The results show that people perceive extreme ratings (positive or negative) as more useful and enjoyable than moderate ratings, giving rise to a U-shaped line, with asymmetric effects: the size of the effect of online reviews depends on whether they are positive or negative.

Entangled two-photon source using biexciton emission of an asymmetric quantum dot in a cavity

A semiconductor based scheme has been proposed for generating entangled photon pairs from the radiative decay of an electrically pumped biexciton in a quantum dot. Symmetric dots produce polarization entanglement, but experimentally realized asymmetric dots produce photons entangled in both polarization and frequency. In this work, we investigate the possibility of erasing the “which-path” information contained in the frequencies of the photons produced by asymmetric quantum dots to recover polarization-entangled photons. We consider a biexciton with nondegenerate intermediate excitonic states in a leaky optical cavity with pairs of degenerate cavity modes close to the nondegenerate exciton transition frequencies. An open quantum system approach is used to compute the polarization entanglement of the two-photon state after it escapes from the cavity, measured by the visibility of two-photon interference fringes. We explicitly relate the two-photon visibility to the degree of the Bell-inequality violation, deriving a threshold at which Bell-inequality violations will be observed. Our results show that an ideal cavity will produce maximally polarization-entangled photon pairs, and even a nonideal cavity will produce partially entangled photon pairs capable of violating a Bell-inequality.

Asymmetric Cipher Protocol Using Decomposition Problem

The asymmetric cipher protocol based on decomposition problem in matrix semiring M over semiring of natural numbers N is presented. The security parameters are defined and preliminary security analysis is presented.