8 resultados para Stock returns

em University of Queensland eSpace - Australia


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We use the consumption-based asset pricing model with habit formation to study the predictability and cross-section of returns from the international equity markets. We find that the predictability of returns from many developed countries' equity markets is explained in part by changing prices of risks associated with consumption relative to habit at the world as well as local levels. We also provide an exploratory investigation of the cross-sectional implications of the model under the complete world market integration hypothesis and find that the model performs mildly better than the traditional consumption-based model. the unconditional and conditional world CAPMs and a three-factor international asset pricing model. (C) 2004 Elsevier B.V. All rights reserved.

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This paper examines the economic significance of return predictability in Australian equities. In light of considerable model uncertainty, formal model-selection criteria are used to choose a specification for the predictive model. A portfolio-switching strategy is implemented according to model predictions. Relative to a buy-and-hold market investment, the returns to the portfolio-switching strategy are impressive under several model-selection criteria, even after accounting for transaction costs. However, as these findings are not robust across other model-selection criteria examined, it is difficult to conclude that the degree of return predictability is economically significant.

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This article examines the market valuation of announcements of new capital expenditure. Prior research suggests that the firm's growth opportunities and cash flow position condition the market response. This study jointly examines the role of growth and cash flow, and the interaction between them. Using a new data set of Australian firms that avoids problems associated with expectations models, the results are remarkably strong and support a positive association between growth opportunities and the market valuation, in addition to supporting the role of free cash flow. The findings have implications for the relationship between general investment information and stock prices.

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This paper examines the impact of multinational trade accords on the degree of stock market linkage using NAFTA as a case study. Besides liberalizing trade among the U.S., Canada and Mexico, NAFTA has also sought to strengthen linkage among stock markets of these countries. If successful, this could lessen the appeal of asset diversification across the North American region and promote a higher degree of market efficiency. We assess the possible impact of NAFTA on market linkage using cross-correlations, multivariate price cointegrating systems, speed of convergence, and generalized variance decompositions of unexpected stock returns. The evidence proves robust and consistently indicates intensified equity market linkage since the NAFTA accord. The results also suggest that interdependent goods markets in the region are a primary reason behind the stronger equity market linkage observed in the post-NAFTA period. (c) 2005 Elsevier Ltd. All rights reserved.

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In this analysis of investment manager performance, two questions are addressed. First, do managers that actively trade stocks create value for investors? Second, can the multifactor model of Gruber capture the cross-section of average fund returns for the Australian setting? The answers from this study are as follows: as an industry, investment managers destroyed value for superannuation investors for the period 1991 through 1999, under-performing passive portfolio returns by 2.80-4.00 per cent per annum on a risk-unadjusted basis and 0.50-0.93 per cent per annum on a risk-adjusted basis. Evidence is provided in support of the four-factor model of Gruber; however, the model fails to capture the impact of investment style for the Australian setting. The findings suggest that Australian superannuation investors would transform their retirement savings into retirement income more efficiently through the use of passive alternatives to the stock selection problem.

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Machine learning techniques for prediction and rule extraction from artificial neural network methods are used. The hypothesis that market sentiment and IPO specific attributes are equally responsible for first-day IPO returns in the US stock market is tested. Machine learning methods used are Bayesian classifications, support vector machines, decision tree techniques, rule learners and artificial neural networks. The outcomes of the research are predictions and rules associated With first-day returns of technology IPOs. The hypothesis that first-day returns of technology IPOs are equally determined by IPO specific and market sentiment is rejected. Instead lower yielding IPOs are determined by IPO specific and market sentiment attributes, while higher yielding IPOs are largely dependent on IPO specific attributes.