We consider the discretized version of a (continuous-time) two-factor model introduced by Benth and coauthors for the electricity markets. For this model, the underlying is the exponent of a sum of independent random variables. We provide and test an algorithm, which is based on the celebrated Föllmer-Schweizer decomposition for solving the mean-variance hedging problem. In particular, we estab...

In classical analysis of variance, dispersion is measured by considering squared distances of sample elements from the sample mean. We consider a measure of dispersion for univariate or multivariate response based on all pairwise distances between-sample elements, and derive an analogous distance components (DISCO) decomposition for powers of distance in (0,2]. The ANOVA F statistic is obtained...

In this paper, we study the statistical performance of robust tensor decomposition with gross corruption. The observations are noisy realization of the superposition of a low-rank tensorW∗ and an entrywise sparse corruption tensor V∗. Unlike conventional noise with bounded variance in previous convex tensor decomposition analysis, the magnitude of the gross corruption can be arbitrary large. We...

Assuming a product space model for biometric and financial events, there exists a rather natural principle for the decomposition of gains of life insurance contracts into a financial and a biometric part using orthogonal projections. In a discrete time framework, the paper shows the connection between this decomposition, locally variance-optimal hedging and the so-called pooling of biometric ri...

A recent analysis of the charge (Z) correlations in the ∆Z− < Z > plane for Xe+Sn central collisions at 32 MeV/u has shown an enhancement in the production of equally sized fragments (low ∆Z) which was interpreted as evidence for spinodal decomposition. However the signal was weak. After a critical analysis of its robustness, we propose in this paper a new technique to build the uncorrelated yi...

unlike other studies in which the autours have focused on testing the existence of an environmental kuznets curve, in this study, causality relationship between the energy consumption (oil equivalent), carbon emissions, gross domestic production, total labor force and fixed capital formation is investigated during 1960 to 2007 in iran. following an examination of stationary tests for all the va...

For a large class of vanilla contingent claims, we establish an explicit Föllmer-Schweizer decomposition when the underlying is a process with independent increments (PII) and an exponential of a PII process. This allows to provide an efficient algorithm for solving the mean variance hedging problem. Applications to models derived from the electricity market are performed.

32.1 Smoothed ANOVA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 586 32.1.1 Zhang et al.’s SANOVA proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 586 32.1.2 Maŕi-Dell’Olmo et al.’s SANOVA proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . 588 32.2 Some Specific Application...

Regression methods aim at inducing models of numeric data. While most state-of-the-art machine learning methods for regression focus on inducing piecewise regression models (regression and model trees), we investigate the predictive performance of regression models based on polynomial equations. We present Ciper, an efficient method for inducing polynomial equations and empirically evaluate its...