34 resultados para Default probability

em Deakin Research Online - Australia


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Abstract
This paper aims to investigate the effect of cash flow and free cash flow on corporate failure in the emerging market in particular Jordan using two samples; matched sample and a cross sectional time-series (panel data) sample representative of 167 Jordanian companies in 1989-2003. LOGIT models are used to outline the relationship between firms’ financial health and the probability of default. Our results show that there is firm’s free cash flow increases corporate failure. The result also shows that the firm’s cash flow decreases corporate failure. Firms’ capital structures are fund a mental in predicting default. Capital structure is seen as the main factor affecting the probability of default as it affects a firm’s ability to access external sources of funds. Jordanian firms depend on short-term debt for both short and long term financing.

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We study dynamic contracts between a lender and a borrower in the presence of costly state verification and hidden effort. We prove three results. Costly monitoring is employed by the lender to optimally limit history dependence and prevent future inefficient termination of the relationship. Due to interaction between costly monitoring and dynamic incentives, the probability of monitoring may fail to be monotone in the borrower's reservation utility. Finally, following the interpretation of the costly state verification literature, we distinguish two levels of bankruptcy: one associated with restructuring and the other with liquidation.

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Sixteen young (25±2.6 years) and 16 older individuals (69±4.4 years) walked normally then terminated walking rapidly. A visual stopping stimulus was presented 10 ms following ground contact (short delay) and in another condition, at 450 ms prior to toe-off (long delay). Stimulus probability was either high (80% of trials) or low (10%). The younger group stopped faster (463 vs. 574 ms) despite also walking faster (1.29 vs. 1.17 m s−1). Longer delay decreased one-step responses but older participants used significantly more (slower) two-step stopping, which increased stopping time and distance. The additional step may have been pre-planned to maintain medial–lateral stability.

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This article presents a profiling tools for identifying students knowledge in chance.

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Specific scales were developed for discriminating child sexual offenders with different classes of victim. The project demonstrates a method of individualising scores on actuarial risk assessment measured in a way that makes them more meaningful for those involved in decision-making about individual child sexual offenders. At present, the only quantifiable approach to specific decision-making relies on a general prediction of future behaviour, based on group data. The Bayesian approach is one method that can be used to assist decision-makers to use this information in ways that lead to the more appropriate management of risk. Ultimately, the better management of known child sexual offenders will lead to fewer offences and a reduction in the number of children who lives are profoundly affected by sexual victimisation.

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A dichotomy in female extrapair copulation (EPC) behavior, with some females seeking EPC and others not, is inferred if the observed distribution of extrapair young (EPY) over broods differs from a random process on the level of individual offspring (binomial, hypergeometrical, or Poisson). A review of the literature shows such null models are virtually always rejected, with often large effect sizes. We formulate an alternative null model, which assumes that 1) the number of EPC has a random (Poisson) distribution across females (broods) and that 2) the probability for an offspring to be of extrapair origin is zero without any EPC and increases with the number of EPC. Our brood-level model can accommodate the bimodality of both zero and medium rates of EPY typically found in empirical data, and fitting our model to EPY production of 7 passerine bird species shows evidence of a nonrandom distribution of EPY in only 2 species. We therefore argue that 1) dichotomy in extrapair mate choice cannot be inferred only from a significant deviation in the observed distribution of EPY from a random process on the level of offspring and that 2) additional empirical work on testing the contrasting critical predictions from the classic and our alternative null models is required.

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Both Flash crowds and DDoS (Distributed Denial-of-Service) attacks have very similar properties in terms of internet traffic, however Flash crowds are legitimate flows and DDoS attacks are illegitimate flows, and DDoS attacks have been a serious threat to internet security and stability. In this paper we propose a set of novel methods using probability metrics to distinguish DDoS attacks from Flash crowds effectively, and our simulations show that the proposed methods work well. In particular, these mathods can not only distinguish DDoS attacks from Flash crowds clearly, but also can distinguish the anomaly flow being DDoS attacks flow or being Flash crowd flow from Normal network flow effectively. Furthermore, we show our proposed hybrid probability metrics can greatly reduce both false positive and false negative rates in detection.

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The usage of Ecstasy and related drug (ERD) has increasingly been the focus of epidemiological and other public health-related research. One of the more promising methods is the use of the Internet as a recruitment and survey tool.However, there remain methodological concerns and questions about representativeness. Three samples of ERD users in Melbourne, Australia surveyed in 2004 are compared in terms of a number of key demographic and drug use variables. The Internet, face-to-face, and probability
sampling methods appear to access similar but not identical groups of ERD users. Implications and limitations of the study are noted and future research is recommended.

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There are the two common means for propagating worms: scanning vulnerable computers in the network and sending out malicious email attachments. Modeling the propagation of worms can help us understand how worms spread and devise effective defence strategies. Most traditional models simulate the overall scale of infected network in each time tick, making them invalid for examining deep inside the propagation procedure among individual nodes. For this reason, this paper proposes a novel probability matrix to model the propagation mechanism of the two main classes of worms (scanning and email worms) by concentrating on the propagation probability. The objective of this paper is to access the spreading and work out an effective scheme against the worms. In order to evaluate the effects of each major component in our probability model, we implement a series of experiments for both worms. From the results, the network administrators can make decision on how to reduce the number of vulnerable nodes to a certain threshold for scanning worms, and how to immunize the highly-connected node for preventing worm's propagation for email worms.