8 resultados para EQUITY PRICES

em Duke University


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Recent empirical findings suggest that the long-run dependence in U.S. stock market volatility is best described by a slowly mean-reverting fractionally integrated process. The present study complements this existing time-series-based evidence by comparing the risk-neutralized option pricing distributions from various ARCH-type formulations. Utilizing a panel data set consisting of newly created exchange traded long-term equity anticipation securities, or leaps, on the Standard and Poor's 500 stock market index with maturity times ranging up to three years, we find that the degree of mean reversion in the volatility process implicit in these prices is best described by a Fractionally Integrated EGARCH (FIEGARCH) model. © 1999 Elsevier Science S.A. All rights reserved.

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This article examines the behavior of equity trading volume and volatility for the individual firms composing the Standard & Poor's 100 composite index. Using multivariate spectral methods, we find that fractionally integrated processes best describe the long-run temporal dependencies in both series. Consistent with a stylized mixture-of-distributions hypothesis model in which the aggregate "news"-arrival process possesses long-memory characteristics, the long-run hyperbolic decay rates appear to be common across each volume-volatility pair.

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Many consumer durable retailers often do not advertise their prices and instead ask consumers to call them for prices. It is easy to see that this practice increases the consumers' cost of learning the prices of products they are considering, yet firms commonly use such practices. Not advertising prices may reduce the firm's advertising costs, but the strategic effects of doing so are not clear. Our objective is to examine the strategic effects of this practice. In particular, how does making price discovery more difficult for consumers affect competing retailers' price, service decisions, and profits? We develop a model in which a manufacturer sells its product through a high-service retailer and a low-service retailer. Consumers can purchase the retail service at the high-end retailer and purchase the product at the competing low-end retailer. Therefore, the high-end retailer faces a free-riding problem. A retailer first chooses its optimal service levels. Then, it chooses its optimal price levels. Finally, a retailer decides whether to advertise its prices. The model results in four structures: (1) both retailers advertise prices, (2) only the low-service retailer advertises price, (3) only the high-service retailer advertises price, and (4) neither retailer advertises price. We find that when a retailer does not advertise its price and makes price discovery more difficult for consumers, the competition between the retailers is less intense. However, the retailer is forced to charge a lower price. In addition, if the competing retailer does advertise its prices, then the competing retailer enjoys higher profit margins. We identify conditions under which each of the above four structures is an equilibrium and show that a low-service retailer not advertising its price is a more likely outcome than a high-service retailer doing so. We then solve the manufacturer's problem and find that there are several instances when a retailer's advertising decisions are different from what the manufacturer would want. We describe the nature of this channel coordination problem and identify some solutions. © 2010 INFORMS.

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We show that "commodity currency" exchange rates have surprisingly robust power in predicting global commodity prices, both in-sample and out-of-sample, and against a variety of alternative benchmarks. This result is of particular interest to policy makers, given the lack of deep forward markets in many individual commodities, and broad aggregate commodity indices in particular. We also explore the reverse relationship (commodity prices forecasting exchange rates) but find it to be notably less robust. We offer a theoretical resolution, based on the fact that exchange rates are strongly forward-looking, whereas commodity price fluctuations are typically more sensitive to short-term demand imbalances. © 2010 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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Many factors such as poverty, ineffective institutions and environmental regulations may prevent developing countries from managing how natural resources are extracted to meet a strong market demand. Extraction for some resources has reached such proportions that evidence is measurable from space. We present recent evidence of the global demand for a single commodity and the ecosystem destruction resulting from commodity extraction, recorded by satellites for one of the most biodiverse areas of the world. We find that since 2003, recent mining deforestation in Madre de Dios, Peru is increasing nonlinearly alongside a constant annual rate of increase in international gold price (∼18%/yr). We detect that the new pattern of mining deforestation (1915 ha/year, 2006-2009) is outpacing that of nearby settlement deforestation. We show that gold price is linked with exponential increases in Peruvian national mercury imports over time (R(2) = 0.93, p = 0.04, 2003-2009). Given the past rates of increase we predict that mercury imports may more than double for 2011 (∼500 t/year). Virtually all of Peru's mercury imports are used in artisanal gold mining. Much of the mining increase is unregulated/artisanal in nature, lacking environmental impact analysis or miner education. As a result, large quantities of mercury are being released into the atmosphere, sediments and waterways. Other developing countries endowed with gold deposits are likely experiencing similar environmental destruction in response to recent record high gold prices. The increasing availability of satellite imagery ought to evoke further studies linking economic variables with land use and cover changes on the ground.

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Quantity-based regulation with banking allows regulated firms to shift obligations across time in response to periods of unexpectedly high or low marginal costs. Despite its wide prevalence in existing and proposed emission trading programs, banking has received limited attention in past welfare analyses of policy choice under uncertainty. We address this gap with a model of banking behavior that captures two key constraints: uncertainty about the future from the firm's perspective and a limit on negative bank values (e.g. borrowing). We show conditions where banking provisions reduce price volatility and lower expected costs compared to quantity policies without banking. For plausible parameter values related to U.S. climate change policy, we find that bankable quantities produce behavior quite similar to price policies for about two decades and, during this period, improve welfare by about a $1 billion per year over fixed quantities. © 2012 Elsevier B.V.