Due to the liberalization of countless electricity markets, load forecasting has become crucial to all public utilities for which electricity is a strategic variable. With the goal of contributing to the forecasting process inside public utilities, this paper addresses the issue of applying the Holt-Winters exponential smoothing technique and the time series analysis for forecasting the hourly ...

We address the problem of forecasting spatial activities on a daily basis that are subject to the types of multiple, complex calendar e€ects that arise in many applications. Our problem is motivated by applications where we generally need to produce thousands, and frequently tens of thousands, of models, as arises in the prediction of daily origin±destination freight ̄ows. Exponential smoothing...

ETFs are baskets of securities designed to track the performance of an index. They are designed to provide exposure to broad-based indexes at a lower cost. We first analyzed why ETF should be the choice for an investment. We provide a brief history of this segment, key attributes of ETFs, and investments strategies and implementations with ETFs. The article then presents data analysis and a ser...

Rate measurements are required for many purposes, e.g. for system analysis and modelling or for live systems that react to measurements. For off-line measurement all data is available in advance. Here, time delay between data collection and data analysis is not an issue. On-line measurement, however, measures rates on the fly. Thus, measurement algorithms that provide their output as timely as ...

This paper describes a simulation environment, called Prosim, which permits a user to define components, subsystems, and their interconnections to analyse a statistical process control (SPC) system. The components and systems are defined and analysed interactively. A library of standard SPC objects containing models for the Xbar, range, exponential weighted moving average, pchart and other SPC ...

We address the problem of forecasting spatial activities on a daily basis that are subject to the types of multiple, complex calendar e ects that arise in many applications. Our problem is motivated by applications where we generally need to produce thousands, and frequently tens of thousands, of models, as arises in the prediction of daily origin-destination freight ows. Exponential smoothingb...

We introduce a novel covariance estimator that exploits the heteroskedastic nature of financial time series by employing exponential weighted moving averages and shrinking in-sample eigenvalues through cross-validation. Our is model-agnostic in we make no assumptions on distribution random entries matrix or structure matrix. Additionally, show how Random Matrix Theory can provide guidance for a...