Results 41 to 50 of about 73,403 (234)

Markov-Switching MIDAS Models [PDF]

Journal of Business & Economic Statistics, 2013
This article introduces a new regression model—Markov-switching mixed data sampling (MS-MIDAS)—that incorporates regime changes in the parameters of the mixed data sampling (MIDAS) models and allows for the use of mixed-frequency data in Markov-switching models.
MARCELLINO, MASSIMILIANO, P. Guerin
openaire   +5 more sources

Regime‐Dependent Nowcasting of the Austrian Economy

Journal of Forecasting, EarlyView.
ABSTRACT We nowcast and forecast economic activity in Austria, namely, real gross domestic product (GDP), consumption, and investment, which are available at a quarterly frequency, using a preselected number of monthly indicators based on a combination of statistical procedures.
Jaroslava Hlouskova, Ines Fortin
wiley   +1 more source

A Compact Solid State Detector for Small Angle Particle Tracking [PDF]

, 1999
MIDAS (MIcrostrip Detector Array System) is a compact silicon tracking telescope for charged particles emitted at small angles in intermediate energy photonuclear reactions.
A Braghieri, A Lanza, A Panzeri, Audit, Barichello, Braghieri, F Sadiq, I Preobrazhensky, J.R.M Annand, Lippi, M Cambiaghi, M Lang, O Barnaba, P Jennewein, P Pedroni, S Altieri, Sauer, T Locatelli, T Pinelli   +18 more
core   +2 more sources

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares

Journal of Forecasting, EarlyView.
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley   +1 more source

Variable Weights Combination MIDAS Model Based on ELM for Natural Gas Price Forecasting

IEEE Access, 2022
Accurate and stable natural gas price forecasts are essential for effective management of energy systems. However, due to the mixed frequency of data and the inherent nonlinear fluctuation characteristics of natural gas price changes, it is difficult to ...
Lue Li, Caihong Han, Shengwei Yao, Liangshuo Ning   +3 more
doaj   +1 more source

Point and Risk estImation Using an enSemble of Models for Nowcasting: PRISM‐Now

Journal of Forecasting, EarlyView.
ABSTRACT We propose PRISM‐Now, a novel ensemble forecasting system for near‐term GDP projection. Recognizing that relevant economic information evolves over time, we treat forecasts from multiple base models as draws from a mixture distribution of “good” and “bad” estimates, whose composition changes continuously and cannot be identified ex ante.
Beomseok Seo, Hyungbae Cho, Dongjae Lee
wiley   +1 more source

Estimating the Impact of Fundamental Macroeconomic Factors on the Capital Market: A MIDAS Approach [PDF]

تحقیقات مالی
ObjectiveAs one of the pillars of financing countries, the stock market plays a key role in the prosperity of economic activities. The key position of the stock market has caused much research to be conducted to identify the factors affecting it.
Reza Tehrani, Mahmoud Moktarband, Menal Aboodeh   +2 more
doaj   +1 more source

Crater lake cichlids individually specialize along the benthic-limnetic axis [PDF]

, 2014
A common pattern of adaptive diversification in freshwater fishes is the repeated evolution of elongated open water (limnetic) species and high-bodied shore (benthic) species from generalist ancestors.
Barlow G. W., Dryden I. L., Fryer G., Hammer Ø., Hudson A. G., Keenleyside M. H. A., McCrary J. K., McKaye K. R., McPhail J. D., Mousseau T. A., Pritchard J. K., Recknagel H., Robinson B. W., Schluter D., Stauffer J. R.   +14 more
core   +2 more sources

Nowcasting World Trade With Machine Learning: A Three‐Step Approach

Journal of Forecasting, EarlyView.
ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn, Baptiste Meunier, Sebastian Stumpner   +2 more
wiley   +1 more source

Forecasting Natural Gas Futures Price Volatility of the United States: National Versus State‐Level Climate Concern Indexes

Journal of Futures Markets, EarlyView.
ABSTRACT This paper uses GARCH‐MIDAS to predict US natural gas futures volatility using national and state‐level Climate Concern Indexes (CCIs). We find that both national and state‐level CCIs positively affect price volatility. Notably, models using state‐level data—specifically those utilizing least‐squares (LS) weighting combinations—surpass the ...
Afees A. Salisu, Ahamuefula E. Ogbonna, Rangan Gupta, Onur Polat   +3 more
wiley   +1 more source