64 resultados para stock prices


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The identification of the primary drivers of stock returns has been of great interest to both financial practitioners and academics alike for many decades. Influenced by classical financial theories such as the CAPM (Sharp, 1964; Lintner, 1965) and APT (Ross, 1976), a linear relationship is conventionally assumed between company characteristics as derived from their financial accounts and forward returns. Whilst this assumption may be a fair approximation to the underlying structural relationship, it is often adopted for the purpose of convenience. It is actually quite rare that the assumptions of distributional normality and a linear relationship are explicitly assessed in advance even though this information would help to inform the appropriate choice of modelling technique. Non-linear models have nevertheless been applied successfully to the task of stock selection in the past (Sorensen et al, 2000). However, their take-up by the investment community has been limited despite the fact that researchers in other fields have found them to be a useful way to express knowledge and aid decision-making...

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The benefits of applying tree-based methods to the purpose of modelling financial assets as opposed to linear factor analysis are increasingly being understood by market practitioners. Tree-based models such as CART (classification and regression trees) are particularly well suited to analysing stock market data which is noisy and often contains non-linear relationships and high-order interactions. CART was originally developed in the 1980s by medical researchers disheartened by the stringent assumptions applied by traditional regression analysis (Brieman et al. [1984]). In the intervening years, CART has been successfully applied to many areas of finance such as the classification of financial distress of firms (see Frydman, Altman and Kao [1985]), asset allocation (see Sorensen, Mezrich and Miller [1996]), equity style timing (see Kao and Shumaker [1999]) and stock selection (see Sorensen, Miller and Ooi [2000])...

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Teachers of construction economics and estimating have for a long time recognised that there is more to construction pricing than detailed calculation of costs (to the contractor). We always get to the point where we have to say "of course, experience or familiarity of the market is very important and this needs judgement, intuition, etc". Quite how important is the matter in construction pricing is not known and we tend to trivialise its effect. If judgement of the market has a minimal effect, little harm would be done, but if it is really important then some quite serious consequences arise which go well beyond the teaching environment. Major areas of concern for the quantity surveyor are in cost modelling and cost planning - neither of which pay any significant attention to the market effect. There are currently two schools of thought about the market effect issue. The first school is prepared to ignore possible effects until more is known. This may be called the pragmatic school. The second school exists solely to criticise the first school. We will call this the antagonistic school. Neither the pragmatic nor the antagonistic schools seem to be particularly keen to resolve the issue one way or the other. The founder and leader of the antagonistic school is Brian Fine whose paper in 1974 is still the basic text on the subject, and in which he coined the term 'socially acceptable' price to describe what we now recognise as the market effect. Mr Fine's argument was then, and is since, that the uncertainty surrounding the contractors' costing and cost estimating process is such that the uncertainty surrounding the contractors' cost that it logically leads to a market-orientated pricing approach. Very little factual evidence, however, seems to be available to support these arguments in any conclusive manner. A further, and more important point for the pragmatic school, is that, even if the market effect is as important as Mr Fine believes, there are no indications of how it can be measured, evaluated or predicted. Since 1974 evidence has been accumulating which tends to reinforce the antagonists' view. A review of the literature covering both contractors' and designers' estimates found many references to the use of value judgements in construction pricing (Ashworth & Skitmore, 1985), which supports the antagonistic view in implying the existence of uncertainty overload. The most convincing evidence emerged quite by accident in some research we recently completed with practicing quantity surveyors in estimating accuracy (Skitmore, 1985). In addition to demonstrating that individual quantity surveyors and certain types of buildings had significant effect on estimating accuracy, one surprise result was that only a very small amount of information was used by the most expert surveyors for relatively very accurate estimates. Only the type and size of building, it seemed, was really relevant in determining accuracy. More detailed information about the buildings' specification, and even a sight to the drawings, did not significantly improve their accuracy level. This seemed to offer clear evidence that the constructional aspects of the project were largely irrelevant and that the expert surveyors were somehow tuning in to the market price of the building. The obvious next step is to feed our expert surveyors with more relevant 'market' information in order to assess its effect. The problem with this is that our experts do not seem able to verbalise their requirements in this respect - a common occurrence in research of this nature. The lack of research into the nature of market effects on prices also means the literature provides little of benefit. Hence the need for this study. It was felt that a clearer picture of the nature of construction markets would be obtained in an environment where free enterprise was a truly ideological force. For this reason, the United States of America was chosen for the next stage of our investigations. Several people were interviewed in an informal and unstructured manner to elicit their views on the action of market forces on construction prices. Although a small number of people were involved, they were thought to be reasonably representative of knowledge in construction pricing. They were also very well able to articulate their views. Our initial reaction to the interviews was that our USA subjects held very close views to those held in the UK. However, detailed analysis revealed the existence of remarkably clear and consistent insights that would not have been obtained in the UK. Further evidence was also obtained from literature relating to the subject and some of the interviewees very kindly expanded on their views in later postal correspondence. We have now analysed all the evidence received and, although a great deal is of an anecdotal nature, we feel that our findings enable at least the basic nature of the subject to be understood and that the factors and their interrelationships can now be examined more formally in relation to construction price levels. I must express my gratitude to the Royal Institution of Chartered Surveyors' Educational Trust and the University of Salford's Department of Civil Engineering for collectively funding this study. My sincere thanks also go to our American participants who freely gave their time and valuable knowledge to us in our enquiries. Finally, I must record my thanks to Tim and Anne for their remarkable ability to produce an intelligible typescript from my unintelligible writing.

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There is growing regulatory pressure on firms worldwide to address the under-representation of women in senior positions. Regulators have taken a variety of approaches to the issue. We investigate a jurisdiction that has issued recommendations and disclosure requirements, rather than implementing quotas. Much of the rhetoric surrounding gender diversity centres on whether diversity has a financial impact. In this paper we take an aggregate (market-level) approach and compare the performance of portfolios of firms with gender diverse boards to those without. We also investigate whether having multiple women on the board is linked to performance, and if there is a within-industry effect. Overall, we do not find evidence of an association between diversity and performance. We find some weak evidence of a negative correlation between having multiple women on the board and performance, but that in some industries diversity is positively correlated with performance.

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We estimated the heritability and correlations between body and carcass weight traits in a cultured stock of giant freshwater prawn (GFP) (Macrobrachium rosenbergii) selected for harvest body weight in Vietnam. The data set consisted of 18,387 body and 1,730 carcass records, as well as full pedigree information collected over four generations. Variance and covariance components were estimated by restricted maximum likelihood fitting a multi-trait animal model. Across generations, estimates of heritability for body and carcass weight traits were moderate and ranged from 0.14 to 0.19 and 0.17 to 0.21, respectively. Body trait heritabilities estimated for females were significantly higher than for males whereas carcass weight trait heritabilities estimated for females and males were not significantly different (P>. 0.05). Maternal effects for body traits accounted for 4 to 5% of the total variance and were greater in females than in males. Genetic correlations among body traits were generally high in the mixed sexes. Genetic correlations between body and carcass weight traits were also high. Although some issues remain regarding the best statistical model to be fitted to GFP data, our results suggest that selection for high harvest body weight based on breeding values estimated by fitting an animal model to the data can significantly improve mean body and carcass weight in GFP.

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Sweden’s protest against the Vietnam War was given tangible form in 1969 through the decision to give economic aid to the Government of North Vietnam. The main outcome was an integrated pulp and paper mill in the Vinh Phu Province north-west of Hanoi. Known as Bai Bang after its location, the mill became the most costly, one of the longest lasting and the most controversial project in the history of Swedish development cooperation. In 1996 Bai Bang produced at its full capacity. Today the mill is exclusively managed and staffed by the Vietnamese and there are plans for future expansion. At the same time a substantial amount of money has been spent to reach these achievements. Looking back at the cumbersome history of the project the results are against many’s expectations. To learn more about the conditions for sustainable development Sida commissioned two studies of the Bai Bang project. Together they touch upon several important issues in development cooperation over a period of almost 30 years: the change of aid paradigms over time, the role of foreign policy in development cooperation, cultural obstacles, recipient responsibility versus donor led development etc. The two studies were commissioned by Sida’s Department for Evaluation and Internal Audit which is an independent department reporting directly to Sida’s Board of Directors. One study assesses the financial and economic viability of the pulp and paper mill and the broader development impact of the project in Vietnam. It has been carried out by the Centre for International Economics, an Australian private economic research agency. The other study analyses the decision-making processes that created and shaped the project over a period of two decades, and reflects on lessons from the project for development cooperation in general. This study has been carried out by the Chr. Michelsen Institute, a Norweigan independent research institution.

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The aims of this project is to develop demand side response model which assists electricity consumers who are exposed to the market price through aggregator to manage the air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimise the energy cost caused by the air-conditioning load considering the electricity market price and network overload. The model is tested with selected characteristics of the room, Queensland electricity market data from Australian Energy Market Operator and data from the Bureau of Statistics on temperatures in Brisbane, during weekdays on hot days from 2011 - 2012.

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This study explores the accuracy and valuation implications of the application of a comprehensive list of equity multiples in the takeover context. Motivating the study is the prevalent use of equity multiples in practice, the observed long-run underperformance of acquirers following takeovers, and the scarcity of multiplesbased research in the merger and acquisition setting. In exploring the application of equity multiples in this context three research questions are addressed: (1) how accurate are equity multiples (RQ1); which equity multiples are more accurate in valuing the firm (RQ2); and which equity multiples are associated with greater misvaluation of the firm (RQ3). Following a comprehensive review of the extant multiples-based literature it is hypothesised that the accuracy of multiples in estimating stock market prices in the takeover context will rank as follows (from best to worst): (1) forecasted earnings multiples, (2) multiples closer to bottom line earnings, (3) multiples based on Net Cash Flow from Operations (NCFO) and trading revenue. The relative inaccuracies in multiples are expected to flow through to equity misvaluation (as measured by the ratio of estimated market capitalisation to residual income value, or P/V). Accordingly, it is hypothesised that greater overvaluation will be exhibited for multiples based on Trading Revenue, NCFO, Book Value (BV) and earnings before interest, tax, depreciation and amortisation (EBITDA) versus multiples based on bottom line earnings; and that multiples based on Intrinsic Value will display the least overvaluation. The hypotheses are tested using a sample of 147 acquirers and 129 targets involved in Australian takeover transactions announced between 1990 and 2005. The results show that first, the majority of computed multiples examined exhibit valuation errors within 30 percent of stock market values. Second, and consistent with expectations, the results provide support for the superiority of multiples based on forecasted earnings in valuing targets and acquirers engaged in takeover transactions. Although a gradual improvement in estimating stock market values is not entirely evident when moving down the Income Statement, historical earnings multiples perform better than multiples based on Trading Revenue or NCFO. Third, while multiples based on forecasted earnings have the highest valuation accuracy they, along with Trading Revenue multiples for targets, produce the most overvalued valuations for acquirers and targets. Consistent with predictions, greater overvaluation is exhibited for multiples based on Trading Revenue for targets, and NCFO and EBITDA for both acquirers and targets. Finally, as expected, multiples based Intrinsic Value (along with BV) are associated with the least overvaluation. Given the widespread usage of valuation multiples in takeover contexts these findings offer a unique insight into their relative effectiveness. Importantly, the findings add to the growing body of valuation accuracy literature, especially within Australia, and should assist market participants to better understand the relative accuracy and misvaluation consequences of various equity multiples used in takeover documentation and assist them in subsequent investment decision making.

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The occurrence of extreme movements in the spot price of electricity represents a significant source of risk to retailers. A range of approaches have been considered with respect to modelling electricity prices; these models, however, have relied on time-series approaches, which typically use restrictive decay schemes placing greater weight on more recent observations. This study develops an alternative, semi-parametric method for forecasting, which uses state-dependent weights derived from a kernel function. The forecasts that are obtained using this method are accurate and therefore potentially useful to electricity retailers in terms of risk management.

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Several studies published in the last few decades have demonstrated a low price-elasticity for residential water use. In particular, it has been shown that there is a quantity of water demanded that remains constant regardless of prices and other economic factors. In this research, we characterise residential water demand based on a Stone-Geary utility function. This specification is not only theory-compatible but can also explicitly model a minimum level of consumption not dependent on prices or income. This is described as minimum threshold or nondiscretionary water use. Additionally, the Stone-Geary framework is used to model the subsistence level of water consumption that is dependent on the temporal evolution of consumer habits and stock of physical capital. The main aim of this study is to analyse the impact of water-saving habits and water-efficient technologies on residential water demand, while additionally focusing attention on nondiscretionary uses. This is informed by an empirical application using data from a survey conducted among residents of Brisbane City Council, Australia. The results will be especially useful in the design of water tariffs and other water-saving policies.

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The application of artificial intelligence in finance is relatively new area of research. This project employed artificial neural networks (ANNs) that use both fundamental and technical inputs to predict future prices of widely held Australian stocks and use these predicted prices for stock portfolio selection over a long investment horizon. The research involved the creation and testing of a large number of possible network configurations and draws conclusions about ANN architectures and their overall suitability for the purpose of stock portfolio selection.

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The aim of the current study was to estimate heritabilities and correlations for body traits at different ages (Weeks 10 and 18 after stocking) in a giant freshwater prawn (Macrobrachium rosenbergii) population selected for fast growth rate in Vietnam. The dataset consisted of 4650 body records (2432 and 2218 records collected at Weeks 10 and 18, respectively) in the full pedigree comprising a total of 18 387 records. Variance and covariance components were estimated using restricted maximum likelihood fitting a multi-trait animal model. Estimates of heritability for body traits (bodyweight, body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width) were moderate and ranged from 0.06 to 0.11 and from 0.11 to 0.22 at Weeks 10 and 18, respectively. Body-trait heritabilities estimated at Week 10 were not significantly lower than at Week 18. Genetic correlations between body traits within age and genetic correlations for body traits between ages were generally high. Our results suggested that selection for high growth rate in GFP can be undertaken successfully before full market size has been reached.

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The application of artificial neural networks (ANN) in finance is relatively new area of research. We employed ANNs that used both fundamental and technical inputs to predict future prices of widely held Australian stocks and used these predicted prices for stock portfolio selection over a 10-year period (2001-2011). We found that the ANNs generally do well in predicting the direction of stock price movements. The stock portfolios selected by the ANNs with median accuracy are able to generate positive alpha over the 10-year period. More importantly, we found that a portfolio based on randomly selected network configuration had zero chance of resulting in a significantly negative alpha but a 27% chance of yielding a significantly positive alpha. This is in stark contrast to the findings of the research on mutual fund performance where active fund managers with negative alphas outnumber those with positive alphas.