959 resultados para trading hour


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In 2008 pub closing times were restricted from 5 am to 3:30 am in the central business district (CBD) of Newcastle, Australia. A previous study showed a one-third reduction in assaults in the 18 months following the restriction. We assessed whether the assault rate remained lower over the following 3.5 years and whether the introduction of a 'lockout' in nearby Hamilton was associated with a reduction in assaults there.

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This paper uses the natural experiment offered by the Shanghai Stock Exchange to investigate the impact of opening call auction transparency on market liquidity. We find that the dissemination of indicative trade information during the pre-open call auction session leads to an overall improvement in stock liquidity in the continuous trading session. Bid-ask spreads narrow in the first trading hour because adverse selection risk fell significantly and there is less price volatility in the continuous market. This effect is greater for actively traded securities than illiquid securities. Our findings are robust for different lengths of sample period, different lengths of trading hours after market open, and stocks that had (and had not) reformed the share split structure during our research period.

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Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

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Data was collected to measure shopper’s attitudes toward the proposed Sunday and limited public holiday trading in Dalby. Survey questionnaires were conducted between 29th August to 31st August at Coles Dalby and Dalby Shoppingtown Plaza. In total, 150 respondents participated in the survey. Overall, the findings suggest that most respondents, especially males, couples with children, fulltime workers and those under the age of 49 years, embrace the proposed Sunday and limited holiday trading in Dalby. While there are concerns over increasing competition for smaller retailers who already trade on Sundays, a majority of respondents indicated it would suit their lifestyle, be convenient, provide more jobs, increase trade for smaller retailers within the area, reduce queues and congestion observed on Saturdays. The majority of those shoppers that indicated they currently did some shopping on a Sunday reported they would continue to support smaller retailers who currently trade on Sundays and some public holidays, if changes came about. Those opposed to changes to trading hours indicated a belief that existing trading hours were sufficient. Most people indicated the proposed extension of trading hours would not harm the community or have a negative, detrimental effect on themselves or their family. The main findings presented in the report are as follows: - 96.8% of respondents surveyed reported to be local, permanent residents of Dalby. - Residents of Dalby visited shopping centres and stores on average 2.8 times per week. This frequency is proportionately higher than the average Australian shopping behaviour at 2.5 times per week (Roy Morgan Supermarket Monitor). - It was determined that weekday evenings (after 5 pm) were the busiest times for shopping, with Saturday the next most popular day to shop. - 68% of respondents support the proposal of the extended trading hours at supermarkets, department stores and the shopping centre in Dalby, 26% oppose and 6% are unsure. - 90% of the respondents agreed that residents of Dalby should be allowed the same choice as other regional towns and cities in supporting/opposing changes to trading hours. The remaining 10% expressed a disagreement. - A larger percentage of males supported the proposal for Sunday and limited holiday trading. Of all the males surveyed, 80% were in support, 15% were opposed and 5% unsure. 60% of female respondents support the proposal, while 33% oppose it and 5% were unsure. - The highest percentage of support exists in fulltime workers with 90% of those respondents supporting the proposal. - In contrast, the lowest percentage of support was found in the non-working (retired/unemployed) respondents, where 67% opposed the application. - It was noted that 71% of respondents employed casually also indicated opposition against proposed changes. Further questioning identified an underlying concern from casually employed persons that Sunday trade would force them onto Sunday work rosters. - 92% of shared households expressed support for Sunday and limited public holiday trading, while 83% of both couples with children and single parent with children at home also supported the application. - 72% of the respondents often find it necessary to do some grocery shopping in Dalby on a Sunday. 76% of shoppers who indicated they already undertook some shopping on Sunday, indicated would continue to shop and support smaller retailers. - Of the respondents surveyed, 44% have travelled outside of Dalby on a Sunday to shop. This indicates that such residents find it necessary to undertake some shopping on a Sunday and in order to do so, drive an hour to Toowoomba in order to access a range of retailers. - The most cited reasons for supporting Sunday and limited public holiday trade were; ‘More choice about when I shop and that is convenient’ (69%), ‘Sunday trade will create job opportunities’ (71%), ‘Sunday trade will be helpful when preparing school lunches and getting ready for the working week’ (62%), and ‘Sunday trade will reduce shopping congestion during peak shopping periods’ (62%) - The most cited reasons for opposing the proposed changes are that ‘Sunday trade may increase competition for small retailers who already trade on Sunday’ (41%), ‘Shops are already open 6 days a week which is enough’ (31%), and ‘Sunday is a day of rest or a religious day and shopping should not be allowed’ (23%). - 97% of respondents indicated they would not change their sporting or social commitment if changes to trading hours were implemented.

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Classical negotiation models are weak in supporting real-world business negotiations because these models often assume that the preference information of each negotiator is made public. Although parametric learning methods have been proposed for acquiring the preference information of negotiation opponents, these methods suffer from the strong assumptions about the specific utility function and negotiation mechanism employed by the opponents. Consequently, it is difficult to apply these learning methods to the heterogeneous negotiation agents participating in e‑marketplaces. This paper illustrates the design, development, and evaluation of a nonparametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. According to our empirical testing, the novel knowledge discovery method can speed up the negotiation processes while maintaining negotiation effectiveness. To the best of our knowledge, this is the first nonparametric negotiation knowledge discovery method developed and evaluated in the context of multi-issue bargaining over e‑marketplaces.

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The 48 hour game making challenge has been running since its inception at the NEXT LEVEL Festival in 2004. It is curated by Truna aka j. Turner and Lubi Thomas and sees teams of both future game makers and industry professionals going head to head under pressure to produce playable games within the time period. The 48 hour is supported by the International Game Developers Association (Brisbane Chapter)and the Creative Industries Precincts as part of their public programs. It is a curated event which engages industry with Brisbane educational institutes and which fosters the Australian Games Industry