Results 211 to 220 of about 163,423 (274)

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source

Convex Versus Concave Emergence Profile of Implant-Supported Crowns in the Aesthetic Zone: 3-Year Results of a Randomized Controlled Trial. [PDF]

J Clin Periodontol
Endres J, Strauss FJ, Siegenthaler M, Naenni N, Jung RE, Thoma DS.   +5 more
europepmc   +1 more source

Coherent Forecasting of Realized Volatility

Journal of Forecasting, EarlyView.
ABSTRACT The QLIKE loss function is the stylized favorite of the literature on volatility forecasting when it comes to out‐of‐sample evaluation and the state of the art model for realized volatility (RV) forecasting is the HAR model, which minimizes the squared error loss for in‐sample estimation of the parameters.
Marius Puke, Karsten Schweikert
wiley   +1 more source

Sparse identification of nonlinear dynamics and Koopman operators with Shallow Recurrent Decoder Networks. [PDF]

Proc Natl Acad Sci U S A
Gao ML, Williams JP, Kutz JN.
europepmc   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das, Stephan Schlüter, Lorenz Schneider   +2 more
wiley   +1 more source

Robust learning for ridge-penalized quasi-GLMs under non-identical distributions. [PDF]

Sci Rep
Zhang H, Tian W, Yao Q, Wang P, Zhang B.
europepmc   +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

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

Performance analysis of mouldboard plough body with raised elements and frame based on numerical simulation. [PDF]

PLoS One
Ma X, Wang X, Wan C, Guo G, Zhao J, Zhang Q.   +5 more
europepmc   +1 more source

Evidence From Microscopy and U–Pb Geochronology as a Clue to the Influence of the Cretaceous Magmatism in the Diagenesis of Pre‐Salt Carbonate Reservoirs in the Santos Basin (Brazil)

Geological Journal, EarlyView.
Carbonates from Santos Basin revealed U–Pb ages correlated with basalt ages (A), suggesting that they were formed during magmatic events. These events placed hot CO2 in the reservoir, which, when mixed with carbonate‐rich cold water (B), led to thermal convection, enabling the formation of the U contained in the carbonates.
Marco António Ruivo de Castro e Brito, Cristiano Leite Sombra, Davy Raeder Brandão, Cleverson Guizan Silva, Sidney Luiz de Matos Mello, Eugênio Vaz dos Santos Neto, Rui Jorge Fernandes Baptista, Ramsés Capilla, Luiz Antônio Pierantoni Gambôa   +8 more
wiley   +1 more source