18 resultados para Efficient Market Hypothesis

em CentAUR: Central Archive University of Reading - UK


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Using UK equity index data, this paper considers the impact of news on time varying measures of beta, the usual measure of undiversifiable risk. The empirical model implies that beta depends on news about the market and news about the sector. The asymmetric response of beta to news about the market is consistent across all sectors considered. Recent research is divided as to whether abnormalities in equity returns arise from changes in expected returns in an efficient market or over-reactions to new information. The evidence suggests that such abnormalities may be due to changes in expected returns caused by time-variation and asymmetry in beta.

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It has been frequently observed that office markets are subject to particularly high fluctuations in rents and vacancy levels, thus exposing real estate investors to considerable risk regarding expected future income streams. This paper analyzes the determinants of office rents and their variability over time and across sub-markets to gain insight into the rent price formation and its stability across space and over time. No support is found for the single-market hypothesis which states that arbitrage opportunities effectively align real estate pricing schemes in various parts of city. Instead, the results suggest that the importance of hedonic pricing factors varies both over time and across submarkets.

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An efficient market incorporates news into prices immediately and fully. Tests for efficiency in financial markets have been undermined by information leakage. We test for efficiency in sports betting markets – real-world markets where news breaks remarkably cleanly. Applying a novel identification to high-frequency data, we investigate the reaction of prices to goals scored on the ‘cusp’ of half-time. This strategy allows us to separate the market's response to major news (a goal), from its reaction to the continual flow of minor game-time news. On our evidence, prices update swiftly and fully.

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This article demonstrates that the design and nature of agricultural support schemes has an influence on farmers' perception of their level of dependence on agricultural support. While direct aid payments inform farmers about the extent to which they are subsidised, indirect support mechanisms veil the level of subsidisation, and therefore they are not fully aware of the extent to which they are supported. To test this hypothesis, we applied data from a survey of 4,500 farmers in three countries: the United Kingdom, Germany and Portugal. It is demonstrated that indirect support, such as that provided through artificially high consumer prices, gives an illusion of free and competitive markets among farmers. This 'visibility' hypothesis is evaluated against an alternative hypothesis that assumes farmers have complete, or at least a fairly comprehensive level of, information on agricultural support schemes. Our findings show that this alternative hypothesis can be ruled out.

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Event-related functional magnetic resonance imaging (efMRI) has emerged as a powerful technique for detecting brains' responses to presented stimuli. A primary goal in efMRI data analysis is to estimate the Hemodynamic Response Function (HRF) and to locate activated regions in human brains when specific tasks are performed. This paper develops new methodologies that are important improvements not only to parametric but also to nonparametric estimation and hypothesis testing of the HRF. First, an effective and computationally fast scheme for estimating the error covariance matrix for efMRI is proposed. Second, methodologies for estimation and hypothesis testing of the HRF are developed. Simulations support the effectiveness of our proposed methods. When applied to an efMRI dataset from an emotional control study, our method reveals more meaningful findings than the popular methods offered by AFNI and FSL. (C) 2008 Elsevier B.V. All rights reserved.

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This paper discusses the design, implementation and synthesis of an FFT module that has been specifically optimized for use in the OFDM based Multiband UWB system, although the work is generally applicable to many other OFDM based receiver systems. Previous work has detailed the requirements for the receiver FFT module within the Multiband UWB ODFM based system and this paper draws on those requirements coupled with modern digital architecture principles and low power design criteria to converge on our optimized solution. The FFT design obtained in this paper is also applicable for implementation of the transmitter IFFT module therefore only needing one FFT module for half-duplex operation. The results from this paper enable the baseband designers of the 200Mbit/sec variant of Multiband UWB systems (and indeed other OFDM based receivers) using System-on-Chip (SoC), FPGA and ASIC technology to create cost effective and low power solutions biased toward the competitive consumer electronics market.

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Economic mechanisms enhance technological solutions by setting the right incentives to reveal information about demand and supply accurately. Market or pricing mechanisms are ones that foster information exchange and can therefore attain efficient allocation. By assigning a value (also called utility) to their service requests, users can reveal their relative urgency or costs to the service. The implementation of theoretical sound models induce further complex challenges. The EU-funded project SORMA analyzes these challenges and provides a prototype as a proof-of-concept. In this paper the approach within the SORMA-project is described on both conceptual and technical level.

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Investments in direct real estate are inherently difficult to segment compared to other asset classes due to the complex and heterogeneous nature of the asset. The most common segmentation in real estate investment analysis relies on property sector and geographical region. In this paper, we compare the predictive power of existing industry classifications with a new type of segmentation using cluster analysis on a number of relevant property attributes including the equivalent yield and size of the property as well as information on lease terms, number of tenants and tenant concentration. The new segments are shown to be distinct and relatively stable over time. In a second stage of the analysis, we test whether the newly generated segments are able to better predict the resulting financial performance of the assets than the old dichotomous segments. Applying both discriminant and neural network analysis we find mixed evidence for this hypothesis. Overall, we conclude from our analysis that each of the two approaches to segmenting the market has its strengths and weaknesses so that both might be applied gainfully in real estate investment analysis and fund management.

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We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting the demand and supply activities. Our focus lies on sector-specific surveys targeting the players from the supply-side of both residential and non-residential real estate markets. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework, we test the efficacy of these indices by comparing them with other coincident indicators in predicting real estate returns. Overall, our analysis suggests that sentiment indicators convey important information which should be embedded in the modeling exercise to predict real estate market returns. Generally, sentiment indices show better information content than broad economic indicators. The goodness of fit of our models is higher for the residential market than for the non-residential real estate sector. The impulse responses, in general, conform to our theoretical expectations. Variance decompositions and out-of-sample predictions generally show desired contribution and reasonable improvement respectively, thus upholding our hypothesis. Quite remarkably, consistent with the theory, the predictability swings when we look through different phases of the cycle. This perhaps suggests that, e.g. during recessions, market players’ expectations may be more accurate predictor of the future performances, conceivably indicating a ‘negative’ information processing bias and thus conforming to the precautionary motive of consumer behaviour.

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In countries that have experienced rapid economic development, the need to establish more efficient markets in which private property can be constructed has induced some innovative solutions. One such solution is the phenomenon of a pre-sales market of the kind that can be observed in Taiwan, Korea, and more recently in China. Developers sell their property before building is started in order to acquire financing for the development companies. This paper discusses the process and, by recognising the analogy between the pre-sales market and forwards markets, analyses the implications for developers

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Data augmentation is a powerful technique for estimating models with latent or missing data, but applications in agricultural economics have thus far been few. This paper showcases the technique in an application to data on milk market participation in the Ethiopian highlands. There, a key impediment to economic development is an apparently low rate of market participation. Consequently, economic interest centers on the “locations” of nonparticipants in relation to the market and their “reservation values” across covariates. These quantities are of policy interest because they provide measures of the additional inputs necessary in order for nonparticipants to enter the market. One quantity of primary interest is the minimum amount of surplus milk (the “minimum efficient scale of operations”) that the household must acquire before market participation becomes feasible. We estimate this quantity through routine application of data augmentation and Gibbs sampling applied to a random-censored Tobit regression. Incorporating random censoring affects markedly the marketable-surplus requirements of the household, but only slightly the covariates requirements estimates and, generally, leads to more plausible policy estimates than the estimates obtained from the zero-censored formulation

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This paper investigates whether energy performance ratings, as measured by mandatory Energy Performance Certificates (EPCs), are reflected in the sale prices of residential properties. This is the first large-scale empirical study of this topic in the UK involving approximately 400,000 dwellings in the period from 1995 to 2011. Applying hedonic regression and an augmented repeat sales regression, we find a positive relationship between the energy efficiency rating of a dwelling and the transaction price per square metre. The price effects of superior energy performance tend to be higher for terraced dwellings and flats compared to detached and semi-detached dwellings. The evidence is less clear-cut for house price growth rates but remains supportive of an overall positive association. Overall, the results of this study appear to support the hypothesis that energy efficiency levels are reflected in UK house prices, at least in recent years.

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We report results from experimental water markets in which owners of two different sources of water supply water to households and farmers. The final water quality consumed by each type of consumer is determined through mixing of qualities from two different resources. We compare the standard duopolistic market structure with an alternative market clearing mechanism inspired by games with confirmed strategies (which have been shown to yield collusive outcomes). As in the static case, complex dynamic markets operating under a confirmed proposals protocol yield less efficient outcomes because coordination among independent suppliers has the usual effects of restricting output and increasing prices to the users. Our results suggest that, when market mechanisms are used to allocate water to its users, the rule of thumb used by competition authorities can also serve as a guide towards water market regulation.

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Globalization, either directly or indirectly (e.g. through structural adjustment reforms), has called for profound changes in the previously existing institutional order. Some changes adversely impacted the production and market environment of many coffee producers in developing countries resulting in more risky and less remunerative coffee transactions. This paper focuses on customization of a tropical commodity, fair-trade coffee, as an approach to mitigating the effects of worsened market conditions for small-scale coffee producers in less developed countries. fair-trade labeling is viewed as a form of “de-commodification” of coffee through product differentiation on ethical grounds. This is significant not only as a solution to the market failure caused by pervasive information asymmetries along the supply chain, but also as a means of revitalizing the agricultural-commodity-based trade of less developed countries (LDCs) that has been languishing under globalization. More specifically, fair-trade is an example of how the same strategy adopted by developed countries’ producers/ processors (i.e. the sequence product differentiation - institutional certification - advertisement) can be used by LDC producers to increase the reputation content of their outputs by transforming them from mere commodities into “decommodified” (i.e. customized and more reputed) goods. The resulting segmentation of the world coffee market makes possible to meet the demand by consumers with preference for this “(ethically) customized” coffee and to transfer a share of the accruing economic rents backward to the Fair-trade coffee producers in LDCs. It should however be stressed that this outcome cannot be taken for granted since investments are needed to promote the required institutional innovations. In Italy FTC is a niche market with very few private brands selling this product. However, an increase of FTC market share could be a big commercial opportunity for farmers in LDCs and other economic agents involved along the international coffee chain. Hence, this research explores consumers’ knowledge of labels promoting quality products, consumption coffee habits, brand loyalty, willingness to pay and market segmentation according to the heterogeneity of preferences for coffee products. The latter was assessed developing a D-efficient design where stimuli refinement was tested during two focus groups.