Showing 1 - 10 of 8,325
In this paper I propose a novel optimal linear filter for smoothing, trend and signal extraction for time series with a unit root. The filter is based on the Singular Spectrum Analysis (SSA) methodology, takes the form of a particular moving average and is different from other linear filters...
Persistent link: https://www.econbiz.de/10014219324
This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic relationships within a longitudinal data setting. The discussion surveys approaches for characterizing the micro dynamics of continuous dependent variables both over time and across...
Persistent link: https://www.econbiz.de/10014024953
The measurement error problem in linear time series regression, with focus on the impact of error memory, modeled as nite-order MA processes, is considered. Three prototype models, two bivariate and one univariate ARMA, and ways of handling the problem by using instrumental variables (IVs) are...
Persistent link: https://www.econbiz.de/10010459136
We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are … implementation of our forecasting procedure relies on the multivariate linear Gaussian state space framework and is applied to … national French hourly electricity load. The analysis focuses on two hours, 9 AM and 12 AM, but forecasting results are …
Persistent link: https://www.econbiz.de/10011373810
In this note I show that the method proposed in Thomakos (2008) for optimal linear filtering, smoothing and trend extraction for a unit root process can be applied with no changes when a drift parameter is added to the process. The method in the aforementioned paper is based on Singular Spectrum...
Persistent link: https://www.econbiz.de/10012724772
in applications that involve forecasts of latent target variables. Such applications include the forecasting of … application to correlation forecasting is presented …
Persistent link: https://www.econbiz.de/10013079416
There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such … as private consumption or unemployment. However, applications on forecasting GDP are rather rare. In this paper we … incorporate Google search data into a Bridge Equation Model, a version of which usually belongs to the suite of forecasting models …
Persistent link: https://www.econbiz.de/10011667109
The procedure for estimating probabilities of future investment returns using time-shifted indexes is based on the simple principle that a multi-dimensional conditional probability distribution can be envisioned involving investment total returns (for a single investment or a fixed portfolio of...
Persistent link: https://www.econbiz.de/10014198891
This chapter summarizes recent literature on asymptotic inference about forecasts. Both analytical and simulation based methods are discussed. The emphasis is on techniques applicable when the number of competing models is small. Techniques applicable when a large number of models is compared to...
Persistent link: https://www.econbiz.de/10014023703
The procedure for estimating probabilities of future investment returns using time-shifted indexes is based on the simple principle that a multi-dimensional conditional probability distribution can be envisioned involving investment total returns (for a single investment or a fixed portfolio of...
Persistent link: https://www.econbiz.de/10014072195