Damped trend exponential smoothing has previously been established as an important forecasting method. Here, it is shown to have close links to simple exponential smoothing with a smoothed error tracking signal. A special case of damped trend exponential smoothing emerges from our analysis, one that is more parsimonious because it effectively relies on one less parameter. This special case is c...

STUDY OBJECTIVE The aim was to evaluate the current approach to forecasting hospital bed requirements. DESIGN The study was a time series and regression analysis. The time series for mean duration of stay for general surgery in the age group 15-44 years (1969-1982) was used in the evaluation of different methods of forecasting future values of mean duration of stay and its subsequent use in t...

Accurate short-term electrical load forecasting plays a pivotal role in the national economy and people’s livelihood through providing effective future plans and ensuring a reliable supply of sustainable electricity. Although considerable work has been done to select suitable models and optimize the model parameters to forecast the short-term electrical load, few models are built based on the c...

Forecasting as a scientific discipline has progressed a lot in the last forty years, with Nobel prizes being awarded for seminar work in the field, most notably to Engle, Granger and Kahneman. Despite these advances, even today we are unable to answer a very simple question, the one that is always the first tabled during discussions with practitioners: “what is the best method for my data?”. In...

We examine whether the U.S. rate of price inflation has become harder to forecast and, to the extent that it has, what changes in the inflation process have made it so. The main finding is that the univariate inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an integrated moving average process with time-varying paramet...

Global warming has induced an increasing number of deadly tropical cyclones with a continuing trend. Developing high-functional climate risk management tools in forecasting, catastrophe modeling, pricing and hedging is crucial to curtail destruction. We develop a hurricane futures and futures-option pricing model in a doubly-binomial framework with stochastic news arrival intensity, and a corre...

This paper employ the discrete hidden Markov model (HMM) in order to capture information about the Markov switching model’s inner states that is not directly observable, and to pre-detect the real estate business cycle’s volatility trend. The empirical results show that this HMM can capture the asymmetry in the duration of states. Compared with the real estate leading indicator announced by the...

Before 1960, little empirical research was done on forecasting methods. Since then, the literature has grown rapidly, especially in the area of judgmental forecasting. This research supports and adds to the forecasting guidelines proposed before 1960, such as the value of combining forecasts. New findings have led to significant gains in our ability to forecast and to help people to use forecas...

Driven by a trend towards renewable forms of generation, in particular wind, the nature of power system operation is changing. With respect to wind power, the uncertainty of the wind becomes an issue which must be considered. Through the use of wind forecasting, this uncertainty may be managed. The error inherent in forecasting will impact system reliability and cost as will inaccuracies in ass...

There are many various methods to forecast time series. However, there is no single forecasting method that generally outperforms any other. Consequently, there always exists a danger of choosing a method that is inappropriate for a given time series. To overcome such a problem, distinct ensemble techniques are being proposed. These techniques combine more individual forecasting methods. In thi...