35 resultados para Adjusted Spread


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Research into the topic of liquidity has greatly benefited from the availability of data. Although bid-ask spreads were inaccessible to researchers, Roll (1984) provided a conceptual model that estimated the effective bid-ask prices from regular time series data, recorded on a daily or longer interval. Later data availability improved and researchers were able to address questions regarding the factors that influenced the spreads and the relationship between spreads and risk, return and liquidity. More recently transaction data have been used to measure the effective spread and researchers have been able to refine the concepts of liquidity to include the impact of transactions on price movements (Clayton and McKinnon, 2000) on a trade-by-trade analysis. This paper aims to use techniques that combine elements from all three approaches and, by studying US data over a relatively long time period, to throw light on earlier research as well as to reveal the changes in liquidity over the period controlling for extraneous factors such as market, age and size of REIT. It also reveals some comparable results for the UK market over the same period.

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The “case for real estate” in the mixed-asset portfolio is a topic of continuing interest to practitioners and academics. The argument is typically made by comparing efficient frontiers of portfolio with real estate to those that exclude real estate. However, most investors will have held inefficient portfolios. Thus, when analysing the real estate’s place in the mixed-asset portfolio it seems illogical to do so by comparing the difference in risk-adjusted performance between efficient portfolios, which few if any investor would have held. The approach adopted here, therefore, is to compare the risk-adjusted performance of a number of mixed-asset portfolios without real estate (which may or not be efficient) with a very large number of mixed-asset portfolios that include real estate (which again may or may not be efficient), to see the proportion of the time when there is an increase in risk-adjusted performance, significant or otherwise using appraisal-based and de-smoothed annual data from 1952-2003. So to the question how often does the addition of private real estate lead to increases the risk-adjusted performance compared with mixed-asset portfolios without real estate the answer is almost all the time. However, significant increases are harder to find. Additionally, a significant increase in risk-adjusted performance can come from either reductions in portfolio risk or increases in return depending on the investors’ initial portfolio structure. In other words, simply adding real estate to a mixed-asset portfolio is not enough to ensure significant increases in performance as the results are dependent on the percentage added and the proper reallocation of the initial portfolio mix in the expanded portfolio.

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This article expresses the price of a spread option as the sum of the prices of two compound options. One compound option is to exchange vanilla call options on the two underlying assets and the other is to exchange the corresponding put options. This way we derive a new closed form approximation for the price of a European spread option and a corresponding approximation for each of its price, volatility and correlation hedge ratios. Our approach has many advantages over existing analytical approximations, which have limited validity and an indeterminacy that renders them of little practical use. The compound exchange option approximation for European spread options is then extended to American spread options on assets that pay dividends or incur costs. Simulations quantify the accuracy of our approach; we also present an empirical application to the American crack spread options that are traded on NYMEX. For illustration, we compare our results with those obtained using the approximation attributed to Kirk (1996, Correlation in energy markets. In: V. Kaminski (Ed.), Managing Energy Price Risk, pp. 71–78 (London: Risk Publications)), which is commonly used by traders.

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Research on the topic of liquidity has greatly benefited from the improved availability of data. Researchers have addressed questions regarding the factors that influence bid-ask spreads and the relationship between spreads and risk, return and liquidity. Intra-day data have been used to measure the effective spread and researchers have been able to refine the concepts of liquidity to include the price impact of transactions on a trade-by-trade analysis. The growth in the creation of tax-transparent securities has greatly enhanced the visibility of securitized real estate, and has naturally led to the question of whether the increased visibility of real estate has caused market liquidity to change. Although the growth in the public market for securitized real estate has occurred in international markets, it has not been accompanied by universal publication of transaction data. Therefore this paper develops an aggregate daily data-based test for liquidity and applies the test to US data in order to check for consistency with the results of prior intra-day analysis. If the two approaches produce similar results, we can apply the same technique to markets in which less detailed data are available and offer conclusions on the liquidity of a wider set of markets.

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Ensemble forecasting of nonlinear systems involves the use of a model to run forward a discrete ensemble (or set) of initial states. Data assimilation techniques tend to focus on estimating the true state of the system, even though model error limits the value of such efforts. This paper argues for choosing the initial ensemble in order to optimise forecasting performance rather than estimate the true state of the system. Density forecasting and choosing the initial ensemble are treated as one problem. Forecasting performance can be quantified by some scoring rule. In the case of the logarithmic scoring rule, theoretical arguments and empirical results are presented. It turns out that, if the underlying noise dominates model error, we can diagnose the noise spread.

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Gardner's popular model of perfect competition in the marketing sector is extended to a conjectural-variations oligopoly with endogenous entry. Revising Gardner's comparative statics on the "farm-retail price ratio," tests of hypotheses about food industry conduct are derived. Using data from a recent article by Wohlgenant, which employs Gardner's framework, tests are made of the validity of his maintained hypothesis-that the food industries are perfectly competitive. No evidence is found of departures from competition in the output markets of the food industries of eight commodity groups: (a) beef and veal, (b) pork, (c) poultry, (d) eggs, (e) dairy, (f) processed fruits and vegetables, (g) fresh fruit, and (h) fresh vegetables.

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We study the empirical performance of the classical minimum-variance hedging strategy, comparing several econometric models for estimating hedge ratios of crude oil, gasoline and heating oil crack spreads. Given the great variability and large jumps in both spot and futures prices, considerable care is required when processing the relevant data and accounting for the costs of maintaining and re-balancing the hedge position. We find that the variance reduction produced by all models is statistically and economically indistinguishable from the one-for-one “naïve” hedge. However, minimum-variance hedging models, especially those based on GARCH, generate much greater margin and transaction costs than the naïve hedge. Therefore we encourage hedgers to use a naïve hedging strategy on the crack spread bundles now offered by the exchange; this strategy is the cheapest and easiest to implement. Our conclusion contradicts the majority of the existing literature, which favours the implementation of GARCH-based hedging strategies.

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The emergence and spread of infectious diseases reflects the interaction of ecological and economic factors within an adaptive complex system. We review studies that address the role of economic factors in the emergence and spread of infectious diseases and identify three broad themes. First, the process of macro-economic growth leads to environmental encroaching, which is related to the emergence of infectious diseases. Second, there are a number of mutually reinforcing processes associated with the emergence/spread of infectious diseases. For example, the emergence and spread of infectious diseases can cause significant economic damages, which in turn may create the conditions for further disease spread. Also, the existence of a mutually reinforcing relationship between global trade and macroeconomic growth amplifies the emergence/spread of infectious diseases. Third, microeconomic approaches to infectious disease point to the adaptivity of human behavior, which simultaneously shapes the course of epidemics and responds to it. Most of the applied research has been focused on the first two aspects, and to a lesser extent on the third aspect. With respect to the latter, there is a lack of empirical research aimed at characterizing the behavioral component following a disease outbreak. Future research should seek to fill this gap and develop hierarchical econometric models capable of integrating both macro and micro-economic processes into disease ecology.

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The practice of partial depopulation or ‘thinning’, i.e. early removal of a proportion of birds from a commercial broiler flock, is a reported risk factor for Campylobacter colonization of residual birds because of the difficulty in maintaining biosecurity during the process. Therefore, the effect of this practice was studied in detail for 51 target flocks, each at a different growing farm belonging to one of seven major poultry companies throughout the United Kingdom. On 21 of these farms, the target flock was already colonized by Campylobacter and at slaughter all cecal samples examined were positive, with a mean of log10 8 cfu / g. A further 27 flocks became positive within 2 – 6 days of the start of thinning and had similarly high levels of cecal carriage at slaughter. Just prior to the thinning process, Campylobacter could be isolated frequently from the farm driveways, transport vehicles, equipment and personnel. Strains from seven such farms on which flocks became colonized after thinning were examined by PFGE typing. The study demonstrated an association between strains occurring at specific sampling sites and those isolated subsequently from the thinned flocks. There were also indications that particular strains had spread from one farm to another, when the farms were jointly company-owned and served by the same bird-catching teams and / or vehicles. The results highlighted the need for better hygiene control in relation to catching equipment and personnel, and more effective cleaning and disinfection of vehicles, and bird-transport crates.

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We investigate the influence of articles, authors, journals and institutions in the field of environmental and ecological economics. We depart from studies that investigated the literature until 2001 and include a time period that has witnessed an enormous increase of importance in the field. We adjust for the age effect given the huge impact of the year of an article's publication on its influence and we show that this adjustment does make a substantial difference — especially for disaggregated units of analysis with diverse age characteristics such as articles or authors. We analyse 6597 studies on environmental and ecological economics published between 2000 and 2009. We provide rankings of the influential articles, authors, journals and institutions and find that Ecological Economics, Energy Economics and the Journal of Environmental Economics and Management have the most influential articles, they publish very influential authors and their articles are cited most. The University of Maryland, Resources for the Future, the University of East Anglia and the World Bank appear to be the most influential institutions in the field of environmental and ecological economics.

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A process-based fire regime model (SPITFIRE) has been developed, coupled with ecosystem dynamics in the LPJ Dynamic Global Vegetation Model, and used to explore fire regimes and the current impact of fire on the terrestrial carbon cycle and associated emissions of trace atmospheric constituents. The model estimates an average release of 2.24 Pg C yr−1 as CO2 from biomass burning during the 1980s and 1990s. Comparison with observed active fire counts shows that the model reproduces where fire occurs and can mimic broad geographic patterns in the peak fire season, although the predicted peak is 1–2 months late in some regions. Modelled fire season length is generally overestimated by about one month, but shows a realistic pattern of differences among biomes. Comparisons with remotely sensed burnt-area products indicate that the model reproduces broad geographic patterns of annual fractional burnt area over most regions, including the boreal forest, although interannual variability in the boreal zone is underestimated.

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Brachyspira pilosicoli is a potentially zoonotic anaerobic intestinal spirochaete that is one of several species causing avian intestinal spirochaetosis. The aim of this study was to develop a reproducible model of infection in point-of-lay chickens and compare the virulence of two strains of B. pilosicoli in a model using experimentally challenged laying chickens. Seventeen-week-old commercial laying chickens were experimentally challenged by oral gavage with either B. pilosicoli strain B2904 or CPSp1, following an oral dose of 10 % sodium bicarbonate to neutralize acidity in the crop. Approximately 80 % of the chickens became colonized and exhibited increased faecal moisture content, reduced weight gain and delayed onset of lay. Tissues sampled at post-mortem examination were analysed to produce a quantitative output on the number of spirochaetes present and hence, the extent of colonization. The liver and spleen were colonized, and novel histopathology was observed in these tissues. The infection model we report here has potential use in studies to improve our understanding of the mechanisms by which Brachyspira elicit disease in poultry and in testing novel intervention strategies.

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With movement toward kilometer-scale ensembles, new techniques are needed for their characterization. A new methodology is presented for detailed spatial ensemble characterization using the fractions skill score (FSS). To evaluate spatial forecast differences, the average and standard deviation are taken of the FSS calculated over all ensemble member–member pairs at different scales and lead times. These methods were found to give important information about the ensemble behavior allowing the identification of useful spatial scales, spinup times for the model, and upscale growth of errors and forecast differences. The ensemble spread was found to be highly dependent on the spatial scales considered and the threshold applied to the field. High thresholds picked out localized and intense values that gave large temporal variability in ensemble spread: local processes and undersampling dominate for these thresholds. For lower thresholds the ensemble spread increases with time as differences between the ensemble members upscale. Two convective cases were investigated based on the Met Office United Model run at 2.2-km resolution. Different ensemble types were considered: ensembles produced using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and an ensemble produced using different model physics configurations. Comparison of the MOGREPS and multiphysics ensembles demonstrated the utility of spatial ensemble evaluation techniques for assessing the impact of different perturbation strategies and the need for assessing spread at different, believable, spatial scales.