We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on...

This work brings together two distinct pieces of evidence concerning, at the macro level, international distributions of incomes and their dynamics, and, at the micro level, the size distributions of firms and the properties of their growth rates. First, our empirical analysis provides a new...

Families of minimax estimators are found for the location parameter of a p-variate (pgt; or = 3) spherically symmetric unimodal(s.s.u.)distribution with respect to general quadratic loss. The estimators of James and Stein, Baranchik, Bock and Strawderman are all considered for this general...

It is 15:00 on Friday in Nairobi. Do you know where your enumerators are?? Good quality data is paramount for applied economic research. If the data are distorted, corresponding conclusions may be incorrect. We demonstrate how Benford's law, the distribution that first digits of numbers in...

Many financial portfolios are optimized without taking the higher moments into account. We recommend tilting these portfolios in a direction that increases their estimated mean and third central moment and decreases their variance and fourth central moment. The advantages of tilting come at the...

We propose a nonparametric estimator of the empirical distribution function (EDF) of the latent spot variance of the log-price of a financial asset. We show that over a fixed time span our realized EDF (or REDF)-inferred from noisy high-frequency data-is consistent as the mesh of the observation...

Increasingly, professional forecasters and academic researchers present model-based and subjective or judgment-based forecasts in economics which are accompanied by some measure of uncertainty. In its most complete form this measure is a probability density function for future values of the...

Continuous statistical distributions can be broken down into symmetric and asymmetric distributions. Asymmetric distributions deviate from symmetric ones by having different shapes on the left and right side of a suitable point of symmetry. They can be classified into “left”- and...