Regressive Fractionally Integrated Moving Average model which is based on Fractional Integration Approach) in forecasting daily …-of-sample forecasting performance. Besides, fractal markets hypothesis was examined and according to the findings, fractal structure was … network model had the best performance in out-of-sample forecasting based on the criteria introduced for calculating …

We analyse the multihorizon forecasting performance of several strategies to estimate the stationary AR(1) model in a … driftless random walk (RW). In addition, we explore the forecasting performance of pairwise combinations between these …

forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and … AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for …

regression used in Bai and Ng (2008), called the elastic net (Zou and Hastie, 2005). We illustrate our approach by forecasting …

…ndings provide an easy-to-use method for conducting mixed data-sampling analysis as well as for forecasting world commodity price …

We propose a nouvel methodology for forecasting chaotic systems which uses information on local Lyapunov exponents … focal value of zero, which traditionally distinguishes order from chaos, plays no role whatsoever when forecasting …

account of them in estimating and forecasting IV. This paper investigates through Monte Carlo simulations the effects of RV … errors on estimating and forecasting IV with RV data. It is found that: (i) neglecting RV errors can lead to serious bias in …

– 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …