1,721,019 research outputs found
Bias-optimal vol-of-vol estimation: the role of window overlapping
No full textThe simplest and most natural vol-of-vol estimator, the pre-estimated spot variance-based realized variance, is typically plagued by a large finite-sample bias. In this paper, we analytically show that allowing for the overlap of consecutive local windows to pre-estimate the spot variance may correct for this bias. In particular, we provide a feasible rule for the bias-optimal selection of the length of local windows when the volatility is a CKLS process. The effectiveness of this rule for practical applications is supported by numerical and empirical analyses
High performance algorithms for time dependent wave scattering from a bounded obstacle
No full textProceeding
The use of the Pontryagin maximum principle in a furtivity problem in time dependent acoustic obstacle scattering
No full textA tail-revisited Markowitz mean-variance approach and a portfolio network centrality
Full text linkA measure for portfolio risk management is proposed by extending the Markowitz mean-variance approach to include the left-hand tail effects of asset returns. Two risk dimensions are captured: asset covariance risk along risk in left-hand tail similarity and volatility. The key ingredient is an informative set on the left-hand tail distributions of asset returns obtained by an adaptive clustering procedure. This set allows a left tail similarity and left tail volatility to be defined, thereby providing a definition for the left-tail-covariance-like matrix. The convex combination of the two covariance matrices generates a “two-dimensional” risk that, when applied to portfolio selection, provides a measure of its systemic vulnerability due to the asset centrality. This is done by simply associating a suitable node-weighted network with the portfolio. Higher values of this risk indicate an asset allocation suffering from too much exposure to volatile assets whose return dynamics behave too similarly in left-hand tail distributions and/or co-movements, as well as being too connected to each other. Minimizing these combined risks reduces losses and increases profits, with a low variability in the profit and loss distribution. The portfolio selection compares favorably with some competing approaches. An empirical analysis is made using exchange traded fund prices over the period January 2006–February 2018
The time harmonic electromagnetic field in a disturbed half space: an existence theorm and a computational method
No full textA new class of composite indicators: The penalized power mean
Full text linkIn this paper we propose a new aggregation method for constructing composite indicators based on a penalization of the power mean. The idea underlying this approach consists in multiplying the power mean by a factor that accounts for the horizontal heterogeneity among indicators while penalizing units with a larger heterogeneity. In line with the minimum loss of information principle, the penalization factor proposed
is proven to be linked to the loss of information generated when the indicators are substituted with their power means. As a consequence, the aggregation approach gives rise to the class of penalized power means and the penalized Benefit of the Doubt aggregative approach. Including heterogeneity makes the aggregation approach more suitable for refined rankings. Interestingly, the penalized power mean of order one coincides
with the Mazziotta Pareto Index. Some theoretical properties of the penalized power means are proven, thus supporting the Mazziotta Pareto index. An empirical analysis of the Human Development Index in 2019 is presented. Comparisons of the rankings induced by the penalized and non-penalized Benefit of the Doubt and power mean aggregation approaches are shown. There are three main findings: the penalized power means
satisfy the properties characterizing weakly monotone aggregation functions; the penalization reduces ranking variations while differentiating units with close means; and the geometric mean provides composite indicators whose ranking is closest to those obtained with power means of different order
A perturbative approach to acoustic scattering from a vibrating bounded obstacle
No full textIn this paper we study a mathematical model to describe a three dimensional acoustic scattering problem associated to a "vibrating" obstacle that is a bounded simply connected domain contained in the three dimensional real Euclidean space whose shape changes in time. In particular we propose a numerical method based on a perturbation series and the operator expansion method to solve the mathematical model considered. This method makes possible to obtain highly parallelizable algorithms able to compute the solution of the problem considered order by order in perturbation theory, and able to obtain the required solution of the scattering problem summing up the perturbation series. Really impressive speed up factors are observed and reported when the algorithm is executed on the Chiba Cluster, a parallel machine of the Argonne National Laboratory, USA. We validate the mathematical model and the numerical method proposed solving some test problems. The quantitative character of the numerical results obtained is established. The results obtained on the test problems are discussed both from the numerical and the physical point of view. In particular we show that the Doppler spectrum associated to the far field patterns of the scattered acoustic fields depends mainly from the incoming wave and from the excited vibrational modes (Figs. 9–13). The website: http://www.econ.unian.it/recchioni/w7 shows some Applets relative to the numerical examples
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