We analyze a fixed-point algorithm for reinforcement learning (RL) of optimal portfolio mean-variance preferences in the setting multivariate generalized autoregressive conditional-heteroskedasticity (MGARCH) with small penalty on trading. A numerical solution is obtained using neural network (NN) architecture within recursive RL loop. theorem proves that NN approximation error has big-oh bound...

Seasonal adjustment procedures attempt to estimate the sample realizations of an unobservable conomic time series in the presence of both seasonal and irregular factors. In this article, we consider a factor that has not been considered explicitly in previous treatments ofseasonal adjustment: measurement error. Because of the sample design used in the Current Population Survey, measurement erro...

In single-step analyses, missing genotypes are explicitly or implicitly imputed, and this requires centering the observed genotypes using the means of the unselected founders. If genotypes are only available for selected individuals, centering on the unselected founder mean is not straightforward. Here, computer simulation is used to study an alternative analysis that does not require centering...