996 resultados para simultaneous volatility


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We analyze the puzzling behavior of the volatility of individual stock returns over the past few decades. The literature has provided many different explanations to the trend in volatility and this paper tests the viability of the different explanations. Virtually all current theoretical arguments that are provided for the trend in the average level of volatility over time lend themselves to explanations about the difference in volatility levels between firms in the cross-section. We therefore focus separately on the cross-sectional and time-series explanatory power of the different proxies. We fail to find a proxy that is able to explain both dimensions well. In particular, we find that Cao et al. [Cao, C., Simin, T.T., Zhao, J., 2008. Can growth options explain the trend in idiosyncratic risk? Review of Financial Studies 21, 2599–2633] market-to-book ratio tracks average volatility levels well, but has no cross-sectional explanatory power. On the other hand, the low-price proxy suggested by Brandt et al. [Brandt, M.W., Brav, A., Graham, J.R., Kumar, A., 2010. The idiosyncratic volatility puzzle: time trend or speculative episodes. Review of Financial Studies 23, 863–899] has much cross-sectional explanatory power, but has virtually no time-series explanatory power. We also find that the different proxies do not explain the trend in volatility in the period prior to 1995 (R-squared of virtually zero), but explain rather well the trend in volatility at the turn of the Millennium (1995–2005).

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We report on the use of the hydrogen bond accepting properties of neutral nitrone moieties to prepare benzylic-amide-macrocycle-containing [2]rotaxanes in yields as high as 70 %. X-Ray crystallography shows the presence of up to four intercomponent hydrogen bonds between the amide groups of the macrocycle and the two nitrone groups of the thread. Dynamic 1H NMR studies of the rates of macrocycle pirouetting in nonpolar solutions indicate that amide-nitrone hydrogen bonds are particularly strong, ~1.3 and ~0.2 kcal mol-1 stronger than similar amide-ester and amide-amide interactions, respectively. In addition to polarizing the N-O bond through hydrogen bonding, the rotaxane structure affects the chemistry of the nitrone groups in two significant ways: The intercomponent hydrogen bonding activates the nitrone groups to electrochemical reduction, a one electron reduction of the rotaxane being stablized by a remarkable 400 mV (8.1 kcal mol-1) with respect to the same process in the thread; encapsulation, however, protects the same functional groups from chemical reduction with an external reagent (and slows down electron transfer to and from the electroactive groups in cyclicvoltammetry experiments). Mechanical interlocking with a hydrogen bonding molecular sheath thus provides a route to an encapsulated polarized functional group and radical anions of significant kinetic and thermodynamic stability.

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Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions’ ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.

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Water uptake refers to the ability of atmospheric particles to take up water vapour from the surrounding atmosphere. This is an important property that affects particle size and phase and therefore influences many characteristics of aerosols relevant to air quality and climate. However, the water uptake properties of many important atmospheric aerosol systems, including those related to the oceans, are still not fully understood. Therefore, the primary aim of this PhD research program was to investigate the water uptake properties of marine aerosols. In particular, the effect of organics on marine aerosol water uptake was investigated. Field campaigns were conducted at remote coastal sites on the east coast of Australia (Agnes Water; March-April 2007) and west coast of Ireland (Mace Head; June 2007), and laboratory measurements were performed on bubble-generated sea spray aerosols. A combined Volatility-Hygroscopicity-Tandem Differential Mobility Analyser (VH-TDMA) was employed in all experiments. This system probes the changes in the hygroscopic properties of nanoparticles as volatile organic components are progressively evaporated. It also allows particle composition to be inferred from combined volatility-hygroscopicity measurements. Frequent new particle formation and growth events were observed during the Agnes Water campaign. The VH-TDMA was used to investigate freshly nucleated particles (17-22.5 nm) and it was found that the condensation of sulphate and/or organic vapours was responsible for driving particle growth during the events. Aitken mode particles (~40 nm) were also measured with the VH-TDMA. In 3 out of 18 VH-TDMA scans evaporation of a volatile, organic component caused a very large increase in hygroscopicity that could only be explained by an increase in the absolute water uptake of the particle residuals, and not merely an increase in their relative hygroscopicity. This indicated the presence of organic components that were suppressing the hygroscopic growth of mixed particles on the timescale of humidification in the VH-TDMA (6.5 secs). It was suggested that the suppression of water uptake was caused by either a reduced rate of hygroscopic growth due to the presence of organic films, or organic-inorganic interactions in solution droplets that had a negative effect on hygroscopicity. Mixed organic-inorganic particles were rarely observed by the VH-TDMA during the summer campaign conducted at Mace Head. The majority of particles below 100 nm in clean, marine air appeared to be sulphates neutralised to varying degrees by ammonia. On one unique day, 26 June 2007, particularly large concentrations of sulphate aerosol were observed and identified as volcanic emissions from Iceland. The degree of neutralisation of the sulphate aerosol by ammonia was calculated by the VH-TDMA and found to compare well with the same quantity measured by an aerosol mass spectrometer. This was an important verification of the VH-TMDA‘s ability to identify ammoniated sulphate aerosols based on the simultaneous measurement of aerosol volatility and hygroscopicity. A series of measurements were also conducted on sea spray aerosols generated from Moreton Bay seawater samples in a laboratory-based bubble chamber. Accumulation mode sea spray particles (38-173 nm) were found to contain only a minor organic fraction (< 10%) that had little effect on particle hygroscopicity. These results are important because previous studies have observed that accumulation mode sea spray particles are predominantly organic (~80% organic mass fraction). The work presented here suggests that this is not always the case, and that there may be currently unknown factors that are controlling the transfer of organics to the aerosol phase during the bubble bursting process. Taken together, the results of this research program have significantly improved our understanding of organic-containing marine aerosols and the way they interact with water vapour in the atmosphere.

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This paper discusses practical issues related to the use of the division model for lens distortion in multi-view geometry computation. A data normalisation strategy is presented, which has been absent from previous discussions on the topic. The convergence properties of the Rectangular Quadric Eigenvalue Problem solution for computing division model distortion are examined. It is shown that the existing method can require more than 1000 iterations when dealing with severe distortion. A method is presented for accelerating convergence to less than 10 iterations for any amount of distortion. The new method is shown to produce equivalent or better results than the existing method with up to two orders of magnitude reduction in iterations. Through detailed simulation it is found that the number of data points used to compute geometry and lens distortion has a strong influence on convergence speed and solution accuracy. It is recommended that more than the minimal number of data points be used when computing geometry using a robust estimator such as RANSAC. Adding two to four extra samples improves the convergence rate and accuracy sufficiently to compensate for the increased number of samples required by the RANSAC process.

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Differential pulse stripping voltammetry method(DPSV) was applied to the determination of three herbicides, ametryn, cyanatryn, and dimethametryn. It was found that their voltammograms overlapped strongly, and it is difficult to determine these compounds individually from their mixtures. With the aid of chemometrics, classical least squares(CLS), principal component regression(PCR) and partial least squares(PLS), voltammogram resolution and quantitative analysis of the synthetic mixtures of the three compounds were successfully performed. The proposed method was also applied to the analysis of some real samples with satisfactory results.

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In this paper an existing method for indoor Simultaneous Localisation and Mapping (SLAM) is extended to operate in large outdoor environments using an omnidirectional camera as its principal external sensor. The method, RatSLAM, is based upon computational models of the area in the rat brain that maintains the rodent’s idea of its position in the world. The system uses the visual appearance of different locations to build hybrid spatial-topological maps of places it has experienced that facilitate relocalisation and path planning. A large dataset was acquired from a dynamic campus environment and used to verify the system’s ability to construct representations of the world and simultaneously use these representations to maintain localisation.

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This study describes the design of a biphasic scaffold composed of a Fused Deposition Modeling scaffold (bone compartment) and an electrospun membrane (periodontal compartment) for periodontal regeneration. In order to achieve simultaneous alveolar bone and periodontal ligament regeneration a cell-based strategy was carried out by combining osteoblast culture in the bone compartment and placement of multiple periodontal ligament (PDL) cell sheets on the electrospun membrane. In vitro data showed that the osteoblasts formed mineralized matrix in the bone compartment after 21 days in culture and that the PDL cell sheet harvesting did not induce significant cell death. The cell-seeded biphasic scaffolds were placed onto a dentin block and implanted for 8 weeks in an athymic rat subcutaneous model. The scaffolds were analyzed by μCT, immunohistochemistry and histology. In the bone compartment, a more intense ALP staining was obtained following seeding with osteoblasts, confirming the μCT results which showed higher mineralization density for these scaffolds. A thin mineralized cementum-like tissue was deposited on the dentin surface for the scaffolds incorporating the multiple PDL cell sheets, as observed by H&E and Azan staining. These scaffolds also demonstrated better attachment onto the dentin surface compared to no attachment when no cell sheets were used. In addition, immunohistochemistry revealed the presence of CEMP1 protein at the interface with the dentine. These results demonstrated that the combination of multiple PDL cell sheets and a biphasic scaffold allows the simultaneous delivery of the cells necessary for in vivo regeneration of alveolar bone, periodontal ligament and cementum. © 2012 Elsevier Ltd.

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Forecasts generated by time series models traditionally place greater weight on more recent observations. This paper develops an alternative semi-parametric method for forecasting that does not rely on this convention and applies it to the problem of forecasting asset return volatility. In this approach, a forecast is a weighted average of historical volatility, with the greatest weight given to periods that exhibit similar market conditions to the time at which the forecast is being formed. Weighting is determined by comparing short-term trends in volatility across time (as a measure of market conditions) by means of a multivariate kernel scheme. It is found that the semi-parametric method produces forecasts that are significantly more accurate than a number of competing approaches at both short and long forecast horizons.