In this paper, impacts of day-ahead market pricing on behavior of producers and consumers in option and day-ahead markets and on option pricing are studied. To this end, two comprehensive equilibrium models for joint put option and day-ahead markets under pay-as-bid and uniform pricing in day-ahead market are presented, respectively. Interaction between put option and day-ahead markets, uncerta...

Recently, Diebold and Kilian [Unit root tests are useful for selecting forecasting models, Journal of Business and Economic Statistics 18, 265-273, 2007] and Niwitpong [Effect of Preliminary unit roots on predictors for an unknown mean AR(1) process, Thailand Statistician 7, 71-79, 2009] indicated that the preciseness of a predictor for an AR(1) process can be increased by using the preliminary...

A dependable long-term hydrologic prediction is essential to planning, designing and 12 management activities of water resources. A three-stage indirect multi-step-ahead prediction model, 13 which combines dynamic spline interpolation into multilayer adaptive time-delay neural network 14 (ATNN), is proposed in this study for the long term hydrologic prediction. In the first two stages, a 15 gro...

Forecasting data from a time series is to make predictions for the future from available data. Thus, such a problem can be viewed as a traditional data mining problem because it is to extract rules for prediction from available data. There are two kinds of forecasting approaches. Most traditional forecasting approaches are based on all available data including the nearest data and far away data...

The prediction of corporate bankruptcies is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. This work presents two contributions. First we review the topic of bankruptcy prediction, with emphasis on neural-network (NN) models. Second, we develop an NN bankruptcy prediction model. Inspired by one of the traditional credit ri...

NLARX (NonLinear AutoRegresive with eXogenous inputs) models are frequently used in black-box nonlinear system identi cation. Though it is easy to make one step ahead prediction with such models, multiple steps prediction ids far from trivial. The main di culty is that in general there is no easy way to compute the mathemaical expectation of an output conditioned by past measurements. An optima...

Recently, the authors introduced a novel algorithm for long range prediction of flat fading channels that can reliably predict future fading coefficients far beyond the coherence time. This prediction capability provides enabling technology for power and bandwidth efficient adaptive modulation and coding methods. In this paper, we extend our results to the Direct Sequence Code Division Multiple...