Security Analysts and Market Reaction:Caveat for Monitoring

Security analysts, analyst forecast and market reaction are anecdotal in restructuring transactions, sometime conflicting and some other time imperative to the process of transaction. This article attempts to highlight a consistent association between analyst, market reaction and corporate restructuring. A close intermediation between those themes is analysed in this article, implying the relationship is contiguous. However issues of delayed price adjustment, conglomerate stock break-ups and negative earnings surprises are not discussed in this paper, though such factors are ingeniously important and crucial to the process of corporate restructuring.Security Analysts, Forecasting and Agency Cost

Neural Networks: Is it hermeneutic?

This paper proposes a synoptic methodology to evaluate the determinants of audit fees by utilising Neural Networks. First, a brief discussion is presented to highlight the significant application of Neural Network in the areas of financial management; second the framework of proposed methodology has been outlined to examine the implication of audit fees on target sample. The underlying rational of this paper is to establish NNs as a diagnostic tool to assess the effect of audit fees on firms, which indeed warrants further empirical investigation. The importance of NNs emerges from the fact that if external and internal audit fees can be disseminated by employing this methodology which is perceived more significantly robust than other econometric models, then accounting standards can be improved.Neural Networks and Audit Fee

Genetic Algorithms: Genesis of Stock Evaluation

The uncertainty of predicting stock prices emanates pre-eminent concerns around the functionality of the stock market. The possibility of utilising Genetic Algorithms to forecast the momentum of stock price has been previously explored by many optimisation models that have subsequently addressed much of the scepticism. In this paper the author proposes a methodology based on Genetic Algorithms and individual data maximum likelihood estimation using logit model arguing that forecasting discrepancy can be rationalised by combined approximation of both the approaches. Thus this paper offers a methodological overture to further investigate the anomalies surrounding stock market. In the main, this paper attempts to provide a temporal dimension of the methods transposed on recurrent series of data over a fixed window conjecturereGenetic Algorithms, Individual Maximum Likelihood Estimation, Stock Price

Estimation of biomass density and carbon storage in the forests of Andhra Pradesh, India, with emphasis on their deforestation and degradation conditions

The current study evaluates the growing stock, biomass and carbon content of Andhra Pradesh state’s forest (India) along with its current status of forest degradation and loss. For this purpose, the study used the growing stock data collected by state forest department in 2010 for the calculation of biomass and carbon storage using the standard conversion and expansion factors given by IPCC. The analysis shows low biomass and carbon values for the state’s forest in comparison to the mean values recorded in different studies made for Andhra Pradesh. It is also observed to be lower when compared with the average carbon and biomass for Indian forests. Overall, the analysis showed degradation and loss of forest in the state, coupled with reduction in biomass and carbon sink

Dynamics of circular arrangements of vorticity in two dimensions

The merger of two like-signed vortices is a well-studied problem, but in a turbulent flow, we may often have more than two like-signed vortices interacting. We study the merger of three or more identical co-rotating vortices initially arranged on the vertices of a regular polygon. At low to moderate Reynolds numbers, we find an additional stage in the merger process, absent in the merger of two vortices, where an annular vortical structure is formed and is long-lived. Vortex merger is slowed down significantly due to this. Such annular vortices are known at far higher Reynolds numbers in studies of tropical cyclones, which have been noticed to a break down into individual vortices. In the pre-annular stage, vortical structures in a viscous flow are found here to tilt and realign in a manner similar to the inviscid case, but the pronounced filaments visible in the latter are practically absent in the former. Interestingly at higher Reynolds numbers, the merger of an odd number of vortices is found to proceed very differently from that of an even number. The former process is rapid and chaotic whereas the latter proceeds more slowly via pairing events. The annular vortex takes the form of a generalised Lamb-Oseen vortex (GLO), and diffuses inwards until it forms a standard Lamb-Oseen vortex. For lower Reynolds number, the numerical (fully nonlinear) evolution of the GLO vortex follows exactly the analytical evolution until merger. At higher Reynolds numbers, the annulus goes through instabilities whose nonlinear stages show a pronounced difference between even and odd mode disturbances. It is hoped that the present findings, that multiple vortex merger is qualitatively different from the merger of two vortices, will motivate studies on how multiple vortex interactions affect the inverse cascade in two-dimensional turbulence.Comment: Abstract truncated. Paper to appear in Physical Review

Flooding attacks to internet threat monitors (ITM): Modeling and counter measures using botnet and honeypots

The Internet Threat Monitoring (ITM),is a globally scoped Internet monitoring system whose goal is to measure, detect, characterize, and track threats such as distribute denial of service(DDoS) attacks and worms. To block the monitoring system in the internet the attackers are targeted the ITM system. In this paper we address flooding attack against ITM system in which the attacker attempt to exhaust the network and ITM's resources, such as network bandwidth, computing power, or operating system data structures by sending the malicious traffic. We propose an information-theoretic frame work that models the flooding attacks using Botnet on ITM. Based on this model we generalize the flooding attacks and propose an effective attack detection using Honeypots