994 resultados para Future commodity returns
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This paper reviews extant research on commodity price dynamics and commodity derivatives pricing models. In the first half, we provide an overview of stylized facts of commodity price behavior that have been explored and documented in the theoretical and empirical literature. In the second half, we review existing derivatives pricing models and discuss how the peculiarities of commodity markets have been integrated in these models. We conclude the paper with a brief outlook on important research questions that need to be addressed in the future.
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Thirty years on from the seminal works on human resource management (HRM) by Beer et al., we examine how the subject has developed. We offer a normative review, based on that model and critique the assumption that the business of HRM is solely to improve returns to owners and shareholders. We identify the importance of a wider view of stakeholders to practitioners and how academic studies on the periphery of HRM are beginning to adopt such a view. We argue that the HRM studies so far have given us much valuable learning but that the subject has now reached a point where we need to take a wider, more contextual, more multilayered approach founded on the long-term needs of all relevant stakeholders. The original Beer et al. model remains a valuable guide to the next 30 years of HRM.
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We use both Granger-causality and instrumental variables (IV) methods to examine the impact of index fund positions on price returns for the main US grains and oilseed futures markets. Our analysis supports earlier conclusions that Granger-causal impacts are generally not discernible. However, market microstructure theory suggests trading impacts should be instantaneous. IV-based tests for contemporaneous causality provide stronger evidence of price impact. We find even stronger evidence that changes in index positions can help predict future changes in aggregate commodity price indices. This result suggests that changes in index investment are in part driven by information which predicts commodity price changes over the coming months.
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Nesta Tese foram apresentadas algumas alternativas de antecipação do preço futuro do aço a partir do emprego de modelos econométricos. Estes modelos foram definidos em função da análise do comportamento, no longo prazo, entre as séries de preços do aço no Brasil vis-à-vis seus respectivos preços no exterior. A verificação deste comportamento de longo prazo foi realizada através do teste de cointegração. A partir da constatação da não cointegração dessas séries, foram definidos dois modelos, cujas previsões, para diversos períodos, foram aqui apresentadas. Foi feita uma análise comparativa, onde foram identificados o melhor modelo e para quais temporalidades de previsão são melhor empregados. Como foi aqui comprovado, o aço é um insumo primordial nos empreendimentos industriais. Considerando que, atualmente, os preços são demandados de forma firme, ou seja, sem possibilidade de alteração, faz-se necessária a identificação de mecanismos de antecipação dos movimentos futuros desta commodity, de modo que se possa considerá-los na definição do preço ofertado, reduzindo assim perdas por suas flutuações inesperadas.
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The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.
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A produção de etanol e a dominação da indústria, historicamente, tem sido uma fonte de discórdia para seus dois principais produtores. Os EUA com seu etanol de milho e o Brasil com sua etanol de cana, são os dois maiores produtores mundiais de etanol (1º EUA; 2º Brasil) e tem competido pela participação de mercado mundial há décadas. A partir de Dezembro de 2011, os EUA levantaram as tarifas e os subsídios que foram instalados para proteger sua indústria de etanol, o que muda o campo de jogo da produção mundial de etanol para o futuro. Atualmente em todo o mundo, o etanol é usado em uma proporção muito menor comparativamente a outros combustíveis. Esta pesquisa analisa o nível potencial de colaboração entre os EUA e o Brasil, facilitando um diálogo entre os stakeholders em etanol. A pesquisa consiste principalmente de conversas e entrevistas, com base em um conjunto de perguntas destinadas a inspirar conversas detalhadas e expansivas sobre os temas de relações Brasil-EUA e etanol. Esta pesquisa mostra que o etanol celulósico, que é também conhecido como etanol de segunda geração, oferece mais oportunidades de parceria entre os EUA e o Brasil, como há mais oportunidades para pesquisa e desenvolvimento em conjunto e transferência de tecnologia nesta área. Enquanto o etanol de cana no Brasil ainda é uma indústria próspera e crescente, o milho e a cana são muito diferentes geneticamente para aplicar as mesmas inovações exatas de um etanol de primeira geração, por outro. As semelhanças entre os processos de fermentação e destilação entre as matérias-primas utilizadas nos EUA e no Brasil para o etanol de segunda geração torna o investimento conjunto nesta área mais sensível. De segunda geração é uma resposta para a questão "alimentos versus combustíveis". Esta pesquisa aplica o modelo de co-opetição como um quadro de parceria entre os EUA e o Brasil em etanol celulósico. A pesquisa mostra que enquanto o etanol pode não ser um forte concorrente com o petróleo no futuro imediato, ele tem melhores perspectivas de ser desenvolvido como um complemento ao petróleo, em vez de um substituto. Como os EUA e o Brasil tem culturas de misturar etanol com petróleo, algo da estrutura para isso já está em vigor, a relação de complementaridade seria fortalecido através de uma política de governo clara e de longo prazo. A pesquisa sugere que apenas através desta colaboração, com toda a partilha de conhecimentos técnicos e estratégias econômicas e de desenvolvimento, o etanol celulósico será um commodity negociado mundialmente e uma alternativa viável a outros combustíveis. As entrevistas com os interessados em que esta pesquisa se baseia foram feitas ao longo de 2012. Como a indústria de etanol é muito dinâmica, certos eventos podem ter ocorrido desde esse tempo para modificar ou melhorar alguns dos argumentos apresentados.
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The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.
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Three groups of steers--one theoretical group and two experimental groups—were evaluated for marketing cattle live, as boxed beef, and grade and yield when the live price was $71 to $73/cwt, grade and yield price $125/cwt for Choice yield grade 3 carcasses with $20/cwt discount for Select carcasses, and in a commodity-trim or close-trim boxed beef market. The results show that the value of highyielding steers can be significantly increased if sold in a close-trim boxed beef market. The close-trim premiums ranged from $5.06 per head for Select close-trim yield grade 4 carcasses to $87.18 per head for close-trim Choice yield grade 1 carcasses. A group of experimental steers averaging 82% Choice and 60% yield grades 1 and 2 returned an additional $104 in the close-trim boxed market compared with selling live for $73/cwt. Another group of experimental steers averaging 21% Choice, 18% Standard, and 93% yield grades 1 and 2 had $29 per head greater return than if the steers had been sold live for $71/cwt. These comparisons emphasize the importance of knowing how cattle will potentially grade before selecting an alternative marketing strategy. This prior knowledge is most important when the spread in price between Choice and Select is high. Producers need to learn more about their cattle to predict how the cattle may grade for a specified value-based market.
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In this paper, we present a revolutionary vision of 5G networks, in which SDN programs wireless network functions, and where Mobile Network Operators (MNO), Enterprises, and Over-The-Top (OTT) third parties are provided with NFV-ready Network Store. The proposed Network Store serves as a digital distribution platform of programmable Virtualized Network Functions (VNFs) that enable 5G application use-cases. Currently existing application stores, such as Apple's App Store for iOS applications, Google's Play Store for Android, or Ubuntu's Software Center, deliver applications to user specific software platforms. Our vision is to provide a digital marketplace, gathering 5G enabling Network Applications and Network Functions, written to run on top of commodity cloud infrastructures, connected to remote radio heads (RRH). The 5G Network Store will be the same to the cloud as the application store is currently to a software platform.
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Our paper asks the question: Does mode of instruction format (live or online format) effect test scores in the principles of macroeconomics classes? Our data are from several sections of principles of macroeconomics, some in live format, some in online format, and all taught by the same instructor. We find that test scores for the online format, when corrected for sample selection bias, are four points higher than for the live format, and the difference is statistically significant. One possible explanation for this is that there was slightly higher human capital in the classes that had the online format. A Oaxaca decomposition of this difference in grades was conducted to see how much was due to human capital and how much was due to the differences in the rates of return to human capital. This analysis reveals that 25% of the difference was due to the higher human capital with the remaining 75% due to differences in the returns to human capital. It is possible that for the relatively older student with the appropriate online learning skill set, and with schedule constrains created by family and job, the online format provides them with a more productive learning environment than does the alternative traditional live class format. Also, because our data are limited to the student s academic transcript, we recommend future research include data on learning style characteristics, and the constraints formed by family and job choices.
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The development of improved technology for agricultural production and its diffusion to farmers is a process requiring investment and time. A large number of studies of this process have been undertaken. The findings of these studies have been incorporated into a quantitative policy model projecting supplies of commodities (in terms of area and crop yields), equilibrium prices, and international trade volumes to the year 2020. These projections show that a “global food crisis,” as would be manifested in high commodity prices, is unlikely to occur. The same projections show, however, that in many countries, “local food crisis,” as manifested in low agricultural incomes and associated low food consumption in the presence of low food prices, will occur. Simulations show that delays in the diffusion of modern biotechnology research capabilities to developing countries will exacerbate local food crises. Similarly, global climate change will also exacerbate these crises, accentuating the importance of bringing strengthened research capabilities to developing countries.
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The agricultural and energy industries are closely related, both biologically and financially. The paper discusses the relationship and the interactions on price and volatility, with special focus on the covolatility spillover effects for these two industries. The interaction and covolatility spillovers or the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset, between the energy and agricultural industries is the primary emphasis of the paper. Although there has already been significant research on biofuel and biofuel-related crops, much of the previous research has sought to find a relationship among commodity prices. Only a few published papers have been concerned with volatility spillovers. However, it must be emphasized that there have been numerous technical errors in the theoretical and empirical research, which needs to be corrected. The paper not only considers futures prices as a widely-used hedging instrument, but also takes an interesting new hedging instrument, ETF, into account. ETF is regarded as index futures when investors manage their portfolios, so it is possible to calculate an optimal dynamic hedging ratio. This is a very useful and interesting application for the estimation and testing of volatility spillovers. In the empirical analysis, multivariate conditional volatility diagonal BEKK models are estimated for comparing patterns of covolatility spillovers. The paper provides a new way of analyzing and describing the patterns of covolatility spillovers, which should be useful for the future empirical analysis of estimating and testing covolatility spillover effects.
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In this Working Paper, based on nearly 20 papers produced by the Centre for European Policy Studies, Slovak Governance Institute and the Conference Board Europe, we examine whether the current trends in the areas of education and skills are pushing the European Union, towards convergence or polarisation. We cover a wide range of questions related to this main issue. No easy answers, but several cross-cutting messages emerged from the research. We demonstrated that there is increasing complexity in what a ‘low-skilled’ person is and how well (or poorly) s/he fares in the labour market. There are undoubtedly powerful forces pushing for more polarisation, particularly in the labour market. Our research confirmed that early childhood education plays an important role, and it also appears to be increasingly uncontested as a policy prescription. However, the other frequently emphasised remedy to inequality – less selection in secondary education, particularly later division of children into separate tracks – is more problematic. Its effectiveness depends on the country in question and the target group, while education systems are extremely difficult to shift even on a long-term basis. A different, more-nuanced type of warning to policy-makers is delivered in our research on returns to higher education by field of study, which showed hidden rationality in how students choose their major.
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Measuring human capital has been a significant challenge for economists because the main variable of interest is intangible and not directly observable. In the Middle Eastern and Northern African region the task is further complicated by the general scarcity of comparable and reliable data. This study overcomes these challenges by relying on a unique international survey that covers most of the region and by deriving a market-based measure that uses returns to education and various labour market factors as guidance. The results show that private returns to schooling are relatively low in most southern Mediterranean countries (SMC). Israel and Turkey are clear outliers, surpassing even the EU-MED averages. In Algeria and Jordan, the returns are almost flat, implying that earnings do not respond significantly to education levels. Despite high attainment levels, Greece, Spain and Portugal also perform badly; only marginally surpassing some of the bottom-ranked SMC, providing evidence of problems in absorption capacity. The baseline scenarios for 2030 show substantial sensitivity to current estimates on returns to education. In particular, improving attainment levels can produce measurable gains in the future only when the returns to education are already high. Such is the case for Egypt, Morocco and Turkey, which substantially improve their human capital stocks under the baseline scenarios, surpassing several EU-MED countries with little or no room for improvement.
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Academic researchers have followed closely the interest of companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? Firstly, it appears that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example in assembly operations. Secondly, the increased tendency towards specialization has forced other, upstream, parts of industrial networks to introduce advanced manufacturing technologies to supply niche markets. Thirdly, the capital market for investments in capacity, and the trade in manufacturing as a commodity, dominates resource allocation to a larger extent than previously was the case. Fourthly, there is a continuous move towards more loosely connected entities that comprise manufacturing networks. More traditional concepts, such as the “keiretsu” and “chaibol” networks of some Asian economies, do not sufficiently support the demands now being placed on networks. Research should address these four fundamental challenges to prepare for the industrial networks of 2020 and beyond.