90 resultados para Conditional Heteroskedasticity


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This paper studies the signalling effect of the consumption−wealth ratio (cay) on German stock returns via vector error correction models (VECMs). The effect of cay on U.S. stock returns has been recently confirmed by Lettau and Ludvigson with a two−stage method. In this paper, performance of the VECMs and the two−stage method are compared in both German and U.S. data. It is found that the VECMs are more suitable to study the effect of cay on stock returns than the two−stage method. Using the Conditional−Subset VECM, cay signals real stock returns and excess returns in both data sets significantly. The estimated coefficient on cay for stock returns turns out to be two times greater in U.S. data than in German data. When the two−stage method is used, cay has no significant effect on German stock returns. Besides, it is also found that cay signals German wealth growth and U.S. income growth significantly.

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Ensembles of extended Atmospheric Model Intercomparison Project (AMIP) runs from the general circulation models of the National Centers for Environmental Prediction (formerly the National Meteorological Center) and the Max-Planck Institute (Hamburg, Germany) are used to estimate the potential predictability (PP) of an index of the Pacific–North America (PNA) mode of climate change. The PP of this pattern in “perfect” prediction experiments is 20%–25% of the index’s variance. The models, particularly that from MPI, capture virtually all of this variance in their hindcasts of the winter PNA for the period 1970–93. The high levels of internally generated model noise in the PNA simulations reconfirm the need for an ensemble averaging approach to climate prediction. This means that the forecasts ought to be expressed in a probabilistic manner. It is shown that the models’ skills are higher by about 50% during strong SST events in the tropical Pacific, so the probabilistic forecasts need to be conditional on the tropical SST. Taken together with earlier studies, the present results suggest that the original set of AMIP integrations (single 10-yr runs) is not adequate to reliably test the participating models’ simulations of interannual climate variability in the midlatitudes.

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We study a two-way relay network (TWRN), where distributed space-time codes are constructed across multiple relay terminals in an amplify-and-forward mode. Each relay transmits a scaled linear combination of its received symbols and their conjugates,with the scaling factor chosen based on automatic gain control. We consider equal power allocation (EPA) across the relays, as well as the optimal power allocation (OPA) strategy given access to instantaneous channel state information (CSI). For EPA, we derive an upper bound on the pairwise-error-probability (PEP), from which we prove that full diversity is achieved in TWRNs. This result is in contrast to one-way relay networks, in which case a maximum diversity order of only unity can be obtained. When instantaneous CSI is available at the relays, we show that the OPA which minimizes the conditional PEP of the worse link can be cast as a generalized linear fractional program, which can be solved efficiently using the Dinkelback-type procedure.We also prove that, if the sum-power of the relay terminals is constrained, then the OPA will activate at most two relays.

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Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

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A novel diagnostic tool is presented, based on polar-cap temperature anomalies, for visualizing daily variability of the Arctic stratospheric polar vortex over multiple decades. This visualization illustrates the ubiquity of extended-time-scale recoveries from stratospheric sudden warmings, termed here polar-night jet oscillation (PJO) events. These are characterized by an anomalously warm polar lower stratosphere that persists for several months. Following the initial warming, a cold anomaly forms in the middle stratosphere, as does an anomalously high stratopause, both of which descend while the lower-stratospheric anomaly persists. These events are characterized in four datasets: Microwave Limb Sounder (MLS) temperature observations; the 40-yr ECMWF Re-Analysis (ERA-40) and Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalyses; and an ensemble of three 150-yr simulations from the Canadian Middle Atmosphere Model. The statistics of PJO events in the model are found to agree very closely with those of the observations and reanalyses. The time scale for the recovery of the polar vortex following sudden warmings correlates strongly with the depth to which the warming initially descends. PJO events occur following roughly half of all major sudden warmings and are associated with an extended period of suppressed wave-activity fluxes entering the polar vortex. They follow vortex splits more frequently than they do vortex displacements. They are also related to weak vortex events as identified by the northern annular mode; in particular, those weak vortex events followed by a PJO event show a stronger tropospheric response. The long time scales, predominantly radiative dynamics, and tropospheric influence of PJO events suggest that they represent an important source of conditional skill in seasonal forecasting.

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This paper models the determinants of integration in the context of global real estate security markets. Using both local and U.S. Dollar denominated returns, we model conditional correlations across listed real estate sectors and also with the global stock market. The empirical results find that financial factors, such as the relationship with the respective equity market, volatility, the relative size of the real estate sector and trading turnover all play an important role in the degree of integration present. Furthermore, the results highlight the importance of macro-economic variables in the degree of integration present. All four of the macro-economic variables modeled provide at least one significant result across the specifications estimated. Factors such as financial and trade openness, monetary independence and the stability of a country’s currency all contribute to the degree of integration reported.

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REDD (reduced emissions from deforestation and degradation) aims to slow carbon releases caused by forest disturbance by making payments conditional on forest quality over time. Like earlier policies to slow deforestation, REDD must change the behaviour of forest degrading actors. Broadly, it can be implemented with payments to forest users in exchange for improved forest management, thus creating incentives; through payments for enforcement, thus creating disincentives; or through addressing external drivers such as urban charcoal demand. In Tanzania, community-based forest management (CBFM), a form of participatory forest management, was chosen by the Tanzania Forest Conservation Group, a local NGO, as a model for implementing REDD pilot programmes. Payments are made to villages that have the rights to forest carbon. In exchange, the villages must demonstrably reduce deforestation at the village level. In this paper, using this pilot programme as a case study, combined with a review of the literature, we provide insights for REDD implementation in sub-Saharan Africa. We pay particular attention to leakage, monitoring and enforcement. We suggest that implementing REDD through CBFM-type structures can create appropriate incentives and behaviour change when the recipients of the REDD funds are also the key drivers of forest change. When external forces drive forest change, however, REDD through CBFM-type structures becomes an enforcement programme with local communities rather than government agencies being responsible for the enforcement. That structure imposes costs on local communities, whose local authority limits the ability to address leakage outside the particular REDD village.

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An idealised modelling study of sting-jet cyclones is presented. Sting jets are descending mesoscale jets that occur in some extratropical cyclones and produce localised regions of strong low-level winds in the frontal fracture region. Moist baroclinic lifecycle (LC1) simulations are performed with modifications to produce cyclones resembling observed sting-jet cyclones. A sting jet exists in the idealised control cyclone with similar characteristics to the sting jet in a simulation of windstorm Gudrun (a confirmed sting-jet case). Unlike in windstorm Gudrun, a low-level layer of strong moist static stability prohibits the descent of the strong winds from above the boundary layer to the surface in the idealised case. Conditional symmetric instability (CSI) exists in the cloud head and dissipates as the sting jet leaves the cloud head and descends. The descending, initially moist, sting-jet trajectories consistently have negative or near-zero saturated moist potential vorticity but moist static stability and inertial stability, consistent with CSI release; the moist static stability becomes negative during the period of most rapid descent, by which time the air is relatively dry implying conditional instability release is unlikely. Sensitivity experiments show that the existence of the sting jet is robust to changes in the initial state, and that the initial tropospheric static stability significantly impacts the descent rate of the sting jet. Inertial and conditional instability are probably being released in the experiment with the weakest initial static stability. This suggests that sting jets can arise through the release of all three instabilities associated with negative saturated moist potential vorticity. While evaporative cooling occurs along the sting-jet trajectories, a sensitivity experiment with evaporation effects turned off shows no significant change to the wind strength or descent rate of the sting jet implying that instability release is the dominant sting-jet driving mechanism.

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Lying to participants offers an experimenter the enticing prospect of making “others' behaviour” a controlled variable, but is eschewed by experimental economists because it may pollute the pool of subjects. This paper proposes and implements a new experimental design, the Conditional Information Lottery, which offers all the benefits of deception without actually deceiving anyone. The design should be suitable for most economics experiments, and works by a modification of an already standard device, the Random Lottery incentive system. The deceptive scenarios of designs which use deceit are replaced with fictitious scenarios, each of which, from a subject's viewpoint, has a chance of being true. The design is implemented in a sequential play public good experiment prompted by Weimann's (1994) result, from a deceptive design, that subjects are more sensitive to freeriding than cooperation on the part of others. The experiment provides similar results to Weimann's, in that subjects are at least as cooperative when uninformed about others' behaviour as they are if reacting to high contributions. No deception is used and the data cohere well both internally and with other public goods experiments. In addition, simultaneous play is found to be more efficient than sequential play, and subjects contribute less at the end of a sequence than at the start. The results suggest pronounced elements of overconfidence, egoism and (biased) reciprocity in behaviour, which may explain decay in contributions in repeated play designs. The experiment shows there is a workable alternative to deception.

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The low availability of zinc (Zn) in soils and crops affects dietary Zn intake worldwide. This study sought to determine if the natural genetic variation in shoot Zn concentrations (Zn(shoot)) is sufficient to pursue a crop improvement breeding strategy in a leafy vegetable crop. The gene-pool of Brassica oleracea L. was sampled using a large (n = 376) diversity foundation set (DFS), representing almost all species-wide common allelic variation, and 74 commercial varieties (mostly F(1)). The DFS genotypes were grown at low and high soil phosphorus (P) levels under glasshouse and field conditions, and also in a Zn-deficient soil, with or without Zn-fertilisation, in a glasshouse. Despite the large variation in Zn(shoot) among genotypes, environment had a profound effect on Zn(shoot) The heritability of Zn(shoot) was significant, but relatively low, among 90 doubled-haploid (DH) lines from a mapping population. While several quantitative trait loci (QTL) associated with Zn(shoot) occurred on chromosomes C2, C3, C5, C7, and C9, these were generally weak and conditional upon growth conditions. Breeding for Zn(shoot) in B. oleracea is therefore likely to be challenging. Shoot P concentrations increased substantially in all genotypes under low soil Zn conditions. Conversely, only some genotypes had increased Zn(shoot) at low soil P levels. Sufficient natural genetic variation may therefore exist to study some of the interactions between Zn and P nutrition.

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The objective of this paper is to apply the mis-specification (M-S) encompassing perspective to the problem of choosing between linear and log-linear unit-root models. A simple M-S encompassing test, based on an auxiliary regression stemming from the conditional second moment, is proposed and its empirical size and power are investigated using Monte Carlo simulations. It is shown that by focusing on the conditional process the sampling distributions of the relevant statistics are well behaved under both the null and alternative hypotheses. The proposed M-S encompassing test is illustrated using US total disposable income quarterly data.

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We pursue the first large-scale investigation of a strongly growing mutual fund type: Islamic funds. Based on an unexplored, survivorship bias-adjusted data set, we analyse the financial performance and investment style of 265 Islamic equity funds from 20 countries. As Islamic funds often have diverse investment regions, we develop a (conditional) three-level Carhart model to simultaneously control for exposure to different national, regional and global equity markets and investment styles. Consistent with recent evidence for conventional funds, we find Islamic funds to display superior learning in more developed Islamic financial markets. While Islamic funds from these markets are competitive to international equity benchmarks, funds from especially Western nations with less Islamic assets tend to significantly underperform. Islamic funds’ investment style is somewhat tilted towards growth stocks. Funds from predominantly Muslim economies also show a clear small cap preference. These results are consistent over time and robust to time varying market exposures and capital market restrictions.

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Methods of improving the coverage of Box–Jenkins prediction intervals for linear autoregressive models are explored. These methods use bootstrap techniques to allow for parameter estimation uncertainty and to reduce the small-sample bias in the estimator of the models’ parameters. In addition, we also consider a method of bias-correcting the non-linear functions of the parameter estimates that are used to generate conditional multi-step predictions.

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Techniques are proposed for evaluating forecast probabilities of events. The tools are especially useful when, as in the case of the Survey of Professional Forecasters (SPF) expected probability distributions of inflation, recourse cannot be made to the method of construction in the evaluation of the forecasts. The tests of efficiency and conditional efficiency are applied to the forecast probabilities of events of interest derived from the SPF distributions, and supplement a whole-density evaluation of the SPF distributions based on the probability integral transform approach.

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This paper contributes to the debate on the effects of the financialization of commodity futures markets by studying the conditional volatility of long–short commodity portfolios and their conditional correlations with traditional assets (stocks and bonds). Using several groups of trading strategies that hedge fund managers are known to implement, we show that long–short speculators do not cause changes in the volatilities of the portfolios they hold or changes in the conditional correlations between these portfolios and traditional assets. Thus calls for increased regulation of commodity money managers are, at this stage, premature. Additionally, long–short speculators can take comfort in knowing that their trades do not alter the risk and diversification properties of their portfolios.