999 resultados para price limit


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THE Obama administration's decision to officially designate the Haqqani Network a terrorist organisation and place it on the State Department's list of Foreign Terrorist Organisations would have been very difficult to make because of its far-reaching implications for US-Pakistan relations.

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Newspaper article examining the implications of the increasing price of justice at a state and federal level in Australia and the United States. Focuses largely on research examining the Queensland and Alabama prosecutions of Gabe Watson for hte death of his wife, Tina Thomas, on their honeymoon in October 2003.

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Realized price for paintings auctioned can systematically differ from prior estimates. We need to understand why experts get it wrong. This paper uses an econometric approach to investigate how pre-sales price estimates are formed and the impact that they have in determining auction prices for Australian paintings.

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The core goal of this study is to empirically investigate whether there is a “world price” of corporate sustainability. This is assessed in the context of standard asset pricing models—in particular, by asking whether a risk premium attaches to a sustainability factor after controlling for the Fama–French factors. Both time-series and cross-sectional tests are formulated and applied. The results show that (1) global Fama–French factors have strong power to explain global equity returns and (2) sustainability investments have no significant impact on global equity returns. The absence of a significant relationship between sustainability and returns implies that large institutional investors are free to implement sustainability mandates without fear of breaching their fiduciary duties from realising negative returns due to incorporating a sustainability investment process.

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Limiting gestational weight gain (GWG) to recommended levels is important to optimize health outcomes for mother and baby. Surprisingly, a recent review revealed that theory-based interventions to limit GWG were less effective than interventions that did not report a theory-base; however, strict criteria were used to identify theory-informed studies. We extended this review and others by systematically evaluating the theories of behaviour change informing GWG interventions using a generalized health psychology perspective, and meta-analysing behaviour change techniques reported in the interventions. Interventions designed to limit GWG were searched for using health, nursing and psychology databases. Papers reporting an underpinning theory were identified and the CALO-RE taxonomy was used to determine individual behaviour change techniques. Nineteen studies were identified for inclusion. Eight studies were informed by a behaviour change theory; six reported favourable effects on GWG. Overall, studies based on theory were as effective as non–theory-based studies at limiting GWG. Furthermore, the provision of information, motivational interviewing, behavioural self-monitoring and providing rewards contingent on successful behaviour appear to be key strategies when intervening in GWG. Combining these behaviour change techniques with dietary interventions may be most effective. Future research should focus on determining the exact combination of behaviour change techniques, or which underpinning theories, are most useful for limiting GWG.

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In this paper we propose a cross-sectional model of the determinants of asset price bubbles. Using 589 firms listed on the NYSE, we find conclusive evidence that trading volume and share price volatility have statistically significant effects on asset price bubbles. However, evidence from sector-based stocks is mixed. We find that for firms belonging to electricity, energy, financial, and banking sectors, and for the smallest size firms, trading volume has a statistically significant and positive effect on bubbles. We do not discover any robust evidence of a statistically significant effect of share price volatility on bubbles at the sector-level.

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Stock price forecast has long been received special attention of investors and financial institutions. As stock prices are changeable over time and increasingly uncertain in modern financial markets, their forecasting becomes more important than ever before. A hybrid approach consisting of two components, a neural network and a fuzzy logic system, is proposed in this paper for stock price prediction. The first component of the hybrid, i.e. a feedforward neural network (FFNN), is used to select inputs that are highly relevant to the dependent variables. An interval type-2 fuzzy logic system (IT2 FLS) is employed as the second component of the hybrid forecasting method. The IT2 FLS’s parameters are initialized through deployment of the k-means clustering method and they are adjusted by the genetic algorithm. Experimental results demonstrate the efficiency of the FFNN input selection approach as it reduces the complexity and increase the accuracy of the forecasting models. In addition, IT2 FLS outperforms the widely used type-1 FLS and FFNN models in stock price forecasting. The combination of the FFNN and the IT2 FLS produces dominant forecasting accuracy compared to employing only the IT2 FLSs without the FFNN input selection.

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The goal of this article is to examine evidence of stock price clustering on the South Pacific Stock Exchange, located in Fiji, and explore its determinants. We find that stock prices cluster at the decimal of 0 and 5, with almost half of prices settling on these two decimals. Upon investigating the determinants of price clustering on the South Pacific Stock Exchange we find that price level and volume of trade have a statistically significant positive effect on price clustering. We also propose and test a ‘panic trading’ hypothesis which states political instability induces price clustering. We find evidence that political instability in Fiji induces price clustering behaviour.