881 resultados para Trade Price Index


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Includes bibliography

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Pós-graduação em Economia - FCLAR

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This paper analyses three aspects of the share market operated by the Lima Stock Exchange: (i) the short-term relationship between the pricing, direction and volume of order flows; (ii) the components of the spread and the equilibrium point of the limit order book per share, and (iii) the pricing, order direction and trading volume dynamic resulting from shocks in the same variables when lagged. The econometric results for intraday data from 2012 show that the short-run dynamic of the most and least liquid shares in the General Index of the Lima Stock Exchange is explained by the direction of order flow, whose price impact is temporary in both cases.

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With external conditions sluggish and highly uncertain as the global economy still struggles to shake off the effects of the economic crisis of 2008-2009, the Latin American and Caribbean region is not isolated from these effects and is projected to record a small drop in gross domestic product (GDP) in 2015, followed by a weak recovery in 2016. Against this backdrop, 2015 will be the third consecutive year of increasing declines in regional export values; a state of affairs not seen since the Great Depression of the 1930s. This poor performance reflects the end of the commodity price boom, the slowdown of the Chinese economy, the weak recovery of the eurozone and the lacklustre economic activity in the region, particularly in South America.

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This study evaluated a nonlinear programming excel workbook PPFR (http://www.fmva.unesp.br/ppfr) for determining the optimum nutrient density and maximize margins. Two experiments were conducted with 240 one-day-old female chicks and 240 one-day-old male chicks distributed in 48 pens (10 chicks per pen, 4 replicates) in a completely randomized design. The treatments include the average price history (2009s and 2010s) for broiler increased and decreased by 25% or 50% (5 treatments to nonlinear feed formulation) and 1 linear feed formulation. Body gain, feed intake, feed conversion were measured at 21, 42 and 56 d of age. Chicks had ad libitum access to feed and water in floor pens with wood shavings as litter. The bio-economic Energy Conversion [BEC= (Total energy intake*Feed weighted cost per kg)/ (Weight gain*kg live chicken cost)] was more sensitive for measuring the bio-economic performance for broilers, and especially with better magnitude. This allowed a better assessment of profitability, the rate of growth and not just energy consumption, the production of broilers, by incorporating energy consumption, allowing for more sensitivity to the new index (BEC). The BEC was demonstrated that the principle of nonlinear formulation minimizes losses significantly (P<0.05), especially under unfavorable conditions the price of chicken in the market. Thus, when considering that a diet of energy supply shows up as the most expensive item of a formulation, it should compose necessarily the formula proposed for a bio-economic index. Thus, there is need to evaluate more accurately, not only the ingredients of a ration, but the impact of nutrients on the stability of a solution, mainly due to the energy requirement. This strategy promotes better accuracy for decision making under conditions of uncertainty, to find alternative post-formulation. From the above, both weight gain and feed conversion, as traditional performance indicators, cannot finalize or predict a performance evaluation of an economic system creating increasingly intense and competitive. Thus, the energy concentration of the diet becomes more important definition to feed formulator, by directly impact profit activity by interactions with the density of nutrients. This allowed a better evaluation of profitability, the rate of energy performance for broilers, by incorporating the energy consumption formula, allowing more sensitivity to the new index (BEC). These data show that nonlinear feed formulation is a toll to offer new opportunities for poultry production to improved profitability.

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The objective of this paper is to present a benefit-cost ranking of 127 civil transport aircraft; this ranking was determined considering a new data envelopment analysis (DEA) approach, called triple index, which combines three assessment methods: 1) standard frontier, 2) inverted index; 3) cross-multiplicative index. The analysis used the following inputs: a) market price; b) direct operating costs; and as outputs: a) payload, b) cruise speed; c) maximum rate of climb with a single engine. To ensure the homogeneity of the units, the aircrafts were divided according to the propulsion system (jet and turboprop) and size (regional, narrow-body and wide-body); they were also evaluated according to different ranges in order to identify the aircraft with the best cost-benefit relationship for each option.

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The American Recovery and Reinvestment Act (ARRA) of 2009 has re-authorized and modified the Trade Adjustment Assistance for Farmers program. The statute authorizes an appropriation of not more than $90 million per year for the next three fiscal years. The TAA for Farmers program helps producers of raw agricultural commodities (farmers, ranchers or fishermen) who have experienced significant declines in price or production, adjust to the changing economic environment brought on by import competition. The program provides benefits to eligible producers in the form of educational assistance, as well as up to $12,000 per producer in cash benefits to help create and implement business adjustment plans.

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Study IReal Wage Determination in the Swedish Engineering Industry This study uses the monopoly union model to examine the determination of real wages and in particular the effects of active labour market programmes (ALMPs) on real wages in the engineering industry. Quarterly data for the period 1970:1 to 1996:4 are used in a cointegration framework, utilising the Johansen's maximum likelihood procedure. On a basis of the Johansen (trace) test results, vector error correction (VEC) models are created in order to model the determination of real wages in the engineering industry. The estimation results support the presence of a long-run wage-raising effect to rises in the labour productivity, in the tax wedge, in the alternative real consumer wage and in real UI benefits. The estimation results also support the presence of a long-run wage-raising effect due to positive changes in the participation rates regarding ALMPs, relief jobs and labour market training. This could be interpreted as meaning that the possibility of being a participant in an ALMP increases the utility for workers of not being employed in the industry, which in turn could increase real wages in the industry in the long run. Finally, the estimation results show evidence of a long-run wage-reducing effect due to positive changes in the unemployment rate. Study IIIntersectoral Wage Linkages in Sweden The purpose of this study is to investigate whether the wage-setting in certain sectors of the Swedish economy affects the wage-setting in other sectors. The theoretical background is the Scandinavian model of inflation, which states that the wage-setting in the sectors exposed to international competition affects the wage-setting in the sheltered sectors of the economy. The Johansen maximum likelihood cointegration approach is applied to quarterly data on Swedish sector wages for the period 1980:1–2002:2. Different vector error correction (VEC) models are created, based on assumptions as to which sectors are exposed to international competition and which are not. The adaptability of wages between sectors is then tested by imposing restrictions on the estimated VEC models. Finally, Granger causality tests are performed in the different restricted/unrestricted VEC models to test for sector wage leadership. The empirical results indicate considerable adaptability in wages as between manufacturing, construction, the wholesale and retail trade, the central government sector and the municipalities and county councils sector. This is consistent with the assumptions of the Scandinavian model. Further, the empirical results indicate a low level of adaptability in wages as between the financial sector and manufacturing, and between the financial sector and the two public sectors. The Granger causality tests provide strong evidence for the presence of intersectoral wage causality, but no evidence of a wage-leading role in line with the assumptions of the Scandinavian model for any of the sectors. Study IIIWage and Price Determination in the Private Sector in Sweden The purpose of this study is to analyse wage and price determination in the private sector in Sweden during the period 1980–2003. The theoretical background is a variant of the “Imperfect competition model of inflation”, which assumes imperfect competition in the labour and product markets. According to the model wages and prices are determined as a result of a “battle of mark-ups” between trade unions and firms. The Johansen maximum likelihood cointegration approach is applied to quarterly Swedish data on consumer prices, import prices, private-sector nominal wages, private-sector labour productivity and the total unemployment rate for the period 1980:1–2003:3. The chosen cointegration rank of the estimated vector error correction (VEC) model is two. Thus, two cointegration relations are assumed: one for private-sector nominal wage determination and one for consumer price determination. The estimation results indicate that an increase of consumer prices by one per cent lifts private-sector nominal wages by 0.8 per cent. Furthermore, an increase of private-sector nominal wages by one per cent increases consumer prices by one per cent. An increase of one percentage point in the total unemployment rate reduces private-sector nominal wages by about 4.5 per cent. The long-run effects of private-sector labour productivity and import prices on consumer prices are about –1.2 and 0.3 per cent, respectively. The Rehnberg agreement during 1991–92 and the monetary policy shift in 1993 affected the determination of private-sector nominal wages, private-sector labour productivity, import prices and the total unemployment rate. The “offensive” devaluation of the Swedish krona by 16 per cent in 1982:4, and the start of a floating Swedish krona and the substantial depreciation of the krona at this time affected the determination of import prices.

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This paper presents the first full-fledged branch-and-price (bap) algorithm for the capacitated arc-routing problem (CARP). Prior exact solution techniques either rely on cutting planes or the transformation of the CARP into a node-routing problem. The drawbacks are either models with inherent symmetry, dense underlying networks, or a formulation where edge flows in a potential solution do not allow the reconstruction of unique CARP tours. The proposed algorithm circumvents all these drawbacks by taking the beneficial ingredients from existing CARP methods and combining them in a new way. The first step is the solution of the one-index formulation of the CARP in order to produce strong cuts and an excellent lower bound. It is known that this bound is typically stronger than relaxations of a pure set-partitioning CARP model.rnSuch a set-partitioning master program results from a Dantzig-Wolfe decomposition. In the second phase, the master program is initialized with the strong cuts, CARP tours are iteratively generated by a pricing procedure, and branching is required to produce integer solutions. This is a cut-first bap-second algorithm and its main function is, in fact, the splitting of edge flows into unique CARP tours.

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Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

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Market liberalization in Tanzania has eroded the monopoly of the cooperative unions by allowing private coffee buyers (PCBs) to compete with them on equal footing. Similarly, farmers groups and primary societies are now allowed to sell coffee at auction. Thus, farmers have various options for selling their coffee. Similarly, the coffee industry has experienced large fluctuations in prices and stagnation in production. How do farmers react to these changes? Can and do farmers profit from different market conditions and sell to different traders at the lower end of the value chain, or do they remain with cooperatives or farmers groups? This study was conducted in Mruwia and Mshiri villages in Moshi Rural district. Whereas Mshiri village remains attached to the Kilimanjaro Native Cooperative Union (KNCU), Mruwia has detached from this organization and sells coffee independently. The sample (103) was randomly selected from the coffee farmers in the two villages. Data were collected through surveys, focus group discussions (FGDs), and socio-anthropological methods (participant-observation, biographies, and thematic interviews). Results indicate that the selection of whom to sell coffee depends largely on farmers’ dependence on coffee and prices, other benefits accrued, and whether the initial costs are covered by buyers. Additionally, most respondents did not sell coffee to PCBs. Thus, prices, the institutional infrastructure, and the structure of local communities were important when making decisions about how and with whom to trade.

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Porcine reproductive and respiratory syndrome virus (PRRSV) is wide-spread in pig populations globally. In many regions of Europe with intensive pig production and high herd densities, the virus is endemic and can cause disease and production losses. This fuels discussion about the feasibility and sustainability of virus elimination from larger geographic regions. The implementation of a program aiming at virus elimination for areas with high pig density is unprecedented and its potential success is unknown. The objective of this work was to approach pig population data with a simple method that could support assessing the feasibility of a sustainable regional PRRSV elimination. Based on known risk factors such as pig herd structure and neighborhood conditions, an index characterizing individual herds' potential for endemic virus circulation and reinfection was designed. This index was subsequently used to compare data of all pig herds in two regions with different pig- and herd-densities in Lower Saxony (North-West Germany) where PRRSV is endemic. Distribution of the indexed herds was displayed using GIS. Clusters of high herd index densities forming potential risk hot spots were identified which could represent key target areas for surveillance and biosecurity measures under a control program aimed at virus elimination. In an additional step, for the study region with the higher pig density (2463 pigs/km(2) farmland), the potential distribution of PRRSV-free and non-free herds during the implementation of a national control program aiming at national virus elimination was modeled. Complex herd and trade network structures suggest that PRRSV elimination in regions with intensive pig farming like that of middle Europe would have to involve legal regulation and be accompanied by important trade and animal movement restrictions. The proposed methodology of risk index mapping could be adapted to areas varying in size, herd structure and density. Interpreted in the regional context, this could help to classify the density of risk and to accordingly target resources and measures for elimination.