he accurate forecasting of carbon dioxide (CO₂) emissions from fossil fuel energy consumption is a key requirement for making energy policy and environmental strategy. In this paper, a novel quantum harmony search (QHS) algorithm-based discounted mean square forecast error (DMSFE) combination...

The state of charge (<i>SOC</i>) is important for the safety and reliability of battery operation since it indicates the remaining capacity of a battery. However, it is difficult to get an accurate value of <i>SOC</i>, because the <i>SOC</i> cannot be directly measured by a sensor. In this paper, an adaptive gain...

We study the problem of parameter estimation for discretely observed stochastic processes driven by additive small Lévy noises. We do not impose any moment condition on the driving Lévy process. Under certain regularity conditions on the drift function, we obtain consistency and rate of...

The prospect of paying for nursing home care represents a significant financial risk for older Americans. Despite this risk, few individuals buy long-term care insurance and, since many lack the resources to pay out of pocket, they often turn to the means-tested Medicaid program. Concerned about...

Accurate forecasting of fossil fuel energy consumption for power generation is important and fundamental for rational power energy planning in the electricity industry. The least squares support vector machine (LSSVM) is a powerful methodology for solving nonlinear forecasting issues with small...

This paper studies the customers’ equilibrium and socially optimal joining–balking behavior in single-server Markovian queues with multiple working vacations. Different from the classical vacation policies, the server does not completely stop service but maintains a low service rate in...

Analyzing comovements in equity markets is important for risk diversification in portfolio management. Copulas have several advantages compared to the linear correlation measure in modeling comovement. This paper introduces a copula ARMA-GARCH model for analyzing the comovement of indexes in...

"A new approach for using Lévy processes to compute value-at-risk (VaR) using high-frequency data is presented in this paper. The approach is a parametric model using an ARMA(1,1)-GARCH(1,1) model where the tail events are modelled using fractional Lévy stable noise and Lévy stable...