infonet-economy

Modeling natural gas futures prices is essential for valuation purposes as well as for hedging strategies in energy risk management. We present a general multi-factor affine diffusion model which incorporates the joint stylized features of both spot and futures prices. The model is brought into state space form on which Kalman filter techniques are applied to evaluate the maximum...

The problem of non-random sample selectivity often occurs in practice in many different fields. In presence of sample selection, the data appears in the sample according to some selection rule. In these cases, the standard tools designed for complete samples, e.g. ordinary least squares, produce biased results, and hence, methods correcting this bias are needed. In his seminal work,...

The sophisticated and automated means of data collection used by an increasing number of institutions and companies leads to extremely large datasets. Subset selection in regression is essential when a huge number of covariates can potentially explain a response variable of interest. The recent statistical literature has seen an emergence of new selection methods that provide some...

This article first demonstrates the inconsistency of the estimator based on the standard Allan Variance (AV) for composite stochastic processes. This result motivates the use of a recently developed estimator, called the Generalized Method of Wavelet Moments (GMWM) estimator. This estimator was previously shown to be consistent and asymptotically normally distributed under the...

We present an algorithm for determining the nature of stochastic processes together with its parameters based on the analysis of time series of inertial errors. The algorithm is suitable mainly (but not only) for situations when several stochastic processes are superposed. In such cases, classical approaches based on the analysis of Allan variance or PSD are likely to fail due to the...

Copula functions are very convenient for modelling multivariate observations. Popular estimation methods are the two-stage MLE and an alternative semi-parametric with empirical cdf for the margins. Unfortunately, they are hastily biased whenever relatively small model deviations occur at the marginal (empirical or parametric) and/or copula levels. In this master thesis we propose...

This article presents a new estimationmethod for the parameters of a times series model.We consider here composite Gaussian processes that are the sum of independent Gaussian processes which, in turn, explain an important aspect of the time series, as is the case in engineering and natural sciences. The proposed estimation method offers an alternative to classical estimation based on...