952 resultados para Exposure scenarios
Resumo:
The objective of this paper is to suggest a method that accounts for the impact of the volatility smile dynamics when performing scenario analysis for a portfolio consisting of vanilla options. As the volatility smile is documented to change at least with the level of implied at-the-money volatility, a suitable model is here included in the calculation process of the simulated market scenarios. By constructing simple portfolios of index options and comparing the ex ante risk exposure measured using different pricing methods to realized market values, ex post, the improvements of the incorporation of the model are monitored. The analyzed examples in the study generate results that statistically support that the most accurate scenarios are those calculated using the model accounting for the dynamics of the smile. Thus, we show that the differences emanating from the volatility smile are apparent and should be accounted for and that the methodology presented herein is one suitable alternative for doing so.
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Aineisto on Keskustakampuksen kirjaston digitoimaa ja kirjasto vastaa aineiston käyttöluvista.
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Paraserianthes falcataria is a very fast growing, light wood tree species, that has recently gained wide interest in Indonesia for industrial wood processing. At the moment the P. falcataria plantations managed by smallholders are lacking predefined management programmes for commercial wood production. The general objective of this study was to model the growth and yield of Paraserianthes falcataria stands managed by smallholders in Ciamis, West Java, Indonesia and to develop management scenarios for different production objectives. In total 106 circular sample plots with over 2300 P. falcataria trees were assessed on smallholder plantation inventory. In addition, information on market prices of P. falcataria wood was collected through rapid appraisals among industries. A tree growth model based on Chapman-Richards function was developed on three different site qualities and the stand management scenarios were developed under three management objectives: (1) low initial stand density with low intensity stand management, (2) high initial stand density with medium intensity of intervention, (3) high initial stand density and strong intensity of silvicultural interventions, repeated more than once. In general, the 9 recommended scenarios have rotation ages varying from 4 to 12 years, planting densities from 4x4 meters (625 trees ha-1) to 3x2 meters (1666 trees ha-1) and thinnings at intensities of removing 30 to 60 % of the standing trees. The highest annual income would be generated on high-quality with a scenario with initial planting density 3x2 m (1666 trees ha-1) one thinning at intensity of removing 55 % of the standing trees at the age of 2 years and clear cut at the age of 4 years.
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Adsorption of dioxygen at clean Ni(110) and Ni(100) surfaces gives rise to two prominent features in the O(1s) spectra at 530 and 531 eV due to O2- and O- type species, respectively. Interaction of ammonia with a Ni(100)-O surface where theta(oxygen) < 0.1 ML favors the dissociation of NH3 giving NHn, (n = 1, 2) and N(a) species. This is accompanied by a decrease in the intensity of the 531 eV feature. On the other hand. a Ni(100)-O surface where the oxygen species are mainly of the O2- type is unreactive, Coadsorption studies of NH3-O-2 mixtures show that at Ni(110) surfaces the uptake of both oxygen and ammonia increase with the proportion of oxygen in the NH3-O-2 mixture. The surface concentrations of the O- species and the NHn species also increase with the increase in the O-2/NH3 ratio while the slope of the plot of sigma(N) versus sigma(O-) is around unity. The results demonstrate the high surface reactivity of the O- species and its role in the dissociation of ammonia. Based on these observations, the possibility of the formation of a surface complex between ammonia and oxygen (specifically O-) is suggested. Results from vibrational spectroscopic studies of the coadsorption of NH3-O-2 mixtures are consistent with those from core-level spectroscopic studies.
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We discuss rst a method of measuring polarisation at the ILC using the 1{prong hadronic decays of the . We then show in this contribution how a study of the ~sector and particularly use of decay polarisation can oer a very good handle for distinguishing between mSUGRA and a SUSY-GUTs scenario, both of which can give rise to appropriate Dark Matter.
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Analysis of climate change impacts on streamflow by perturbing the climate inputs has been a concern for many authors in the past few years, but there are few analyses for the impacts on water quality. To examine the impact of change in climate variables on the water quality parameters, the water quality input variables have to be perturbed. The primary input variables that can be considered for such an analysis are streamflow and water temperature, which are affected by changes in precipitation and air temperature, respectively. Using hypothetical scenarios to represent both greenhouse warming and streamflow changes, the sensitivity of the water quality parameters has been evaluated under conditions of altered river flow and river temperature in this article. Historical data analysis of hydroclimatic variables is carried out, which includes flow duration exceedance percentage (e.g. Q90), single low- flow indices (e.g. 7Q10, 30Q10) and relationships between climatic variables and surface variables. For the study region of Tunga-Bhadra river in India, low flows are found to be decreasing and water temperatures are found to be increasing. As a result, there is a reduction in dissolved oxygen (DO) levels found in recent years. Water quality responses of six hypothetical climate change scenarios were simulated by the water quality model, QUAL2K. A simple linear regression relation between air and water temperature is used to generate the scenarios for river water temperature. The results suggest that all the hypothetical climate change scenarios would cause impairment in water quality. It was found that there is a significant decrease in DO levels due to the impact of climate change on temperature and flows, even when the discharges were at safe permissible levels set by pollution control agencies (PCAs). The necessity to improve the standards of PCA and develop adaptation policies for the dischargers to account for climate change is examined through a fuzzy waste load allocation model developed earlier. Copyright (C) 2011 John Wiley & Sons, Ltd.
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Concern over changes in global climate has increased in recent years with improvement in understanding of atmospheric dynamics and growth in evidence of climate link to long‐term variability in hydrologic records. Climate impact studies rely on climate change information at fine spatial resolution. Towards this, the past decade has witnessed significant progress in development of downscaling models to cascade the climate information provided by General Circulation Models (GCMs) at coarse spatial resolution to the scale relevant for hydrologic studies. While a plethora of downscaling models have been applied successfully to mid‐latitude regions, a few studies are available on tropical regions where the atmosphere is known to have more complex behavior. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling to interpret climate change signals provided by GCMs over tropical regions of India. Climate variables affecting spatio‐temporal variation of precipitation at each meteorological sub‐division of India are identified. Following this, cluster analysis is applied on climate data to identify the wet and dry seasons in each year. The data pertaining to climate variables and precipitation of each meteorological sub‐division is then used to develop SVM based downscaling model for each season. Subsequently, the SVM based downscaling model is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to assess the impact of climate change on hydrological inputs to the meteorological sub‐divisions. The results obtained from the SVM downscaling model are then analyzed to assess the impact of climate change on precipitation over India.
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ZrB2 with different amounts of B4C additive (0-5 wt.%) has been hot pressed at 2000 degrees C and 25 MPa for 1 h. By addition of B4C, density as well as micro-hardness increased. For lower B4C content (0.5 and 1 wt.%), hot pressed ZrB2 shows considerable improvement in flexural strength after exposure in air at 1000 C for 5 h, while higher B4C content (3 and 5 wt.%) leads to marginal or no improvement. For any content of B4C, flexural strength after exposure in air at 1500 degrees C for 5 h is lower than as-hot pressed ZrB2. (C) 2011 Elsevier B.V. All rights reserved.
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A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R (H) in a river basin at monthly scale. Uncertainty in the future projections of R (H) is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R (H) are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R (H) is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.
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This paper shows how multidisciplinary research can help policy makers develop policies for sustainable agricultural water management interventions by supporting a dialogue between government departments that are in charge of different aspects of agricultural development. In the Jaldhaka Basin in West Bengal, India, a stakeholder dialogue helped identify potential water resource impacts and livelihood implications of an agricultural water management rural electrification scenario. Hydrologic modelling demonstrated that the expansion of irrigation is possible with only a localized effect on groundwater levels, but cascading effects such as declining soil fertility and negative impacts from agrochemicals will need to be addressed.