In this paper we 'update' the option implied probability of default (option iPoD) approach recently suggested in the literature. First, a numerically more stable objective function for the estimation of the risk neutral density is derived whose integrals can be solved analytically. Second, it is...

This study models high and low frequency variation in global equity correlations using a comprehensive sample of 43 countries that includes developed and emerging markets, during the period 1995-2008. These two types of variations are modeled following the semi-parametric Factor-Spline-GARCH...

In this paper modelling time series by single hidden layer feedforward neural network models is considered. A coherent modelling strategy based on statistical inference is discussed. The problems of selecting the variables and the number of hidden units are solved by using statistical model...

We develop tests for deciding whether a large cross-section of asset prices obey an exact factor structure at the times of factor jumps. Such jump dependence is implied by standard linear factor models. Our inference is based on a panel of asset returns with asymptotically increasing...

We study the temporal behavior of the cross-sectional distribution of assets' market exposure, or betas, using a large panel of high-frequency returns. The asymptotic setup has the sampling frequency of returns increasing to infinity, while the time span of the data remains fixed, and the...

In this paper, we discuss estimation procedure and various inferential methods for varying coefficient panel data models that include spatially correlated error components. Our estimation procedure is an extension of the quasi-maximum likelihood method for spatial panel data regression to the...

In this paper we 'update' the option implied probability of default (option iPoD) approach recently suggested in the literature. First, a numerically more stable objective function for the estimation of the risk neutral density is derived whose integrals can be solved analytically. Second, it is...

This paper is concerned with modelling time series by single hidden layer feedforward neural network models. A coherent modelling strategy based on statistical inference is presented. Variable selection is carried out using existing techniques. The problem of selecting the number of hidden units...

We develop an econometric methodology to infer the path of risk premia from large unbalancedpanel of individual stock returns. We estimate the time-varying risk premia implied by conditional linearasset pricing models where the conditioning includes instruments common to all assets and asset...