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
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A data-parsimonious model for long-term risk assessments of West Nile virus spillover. [PDF]
Sci RepHosseini S +3 more
europepmc +1 more source
A New Implementation of Network GARCH Model for Stock Volatility and Co‐Volatility Forecasting
Journal of Forecasting, EarlyView.ABSTRACT Volatility clustering and spillovers are key features of financial time series with many cross‐sectional assets. While network analysis links similar or correlated stocks and helps trace volatility spillovers, contemporary multivariate ARCH‐GARCH formulations struggle to represent structured network dependence and remain parsimonious.
Peiyi Zhou
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Connected Components on Lie Groups and Applications to Multi-Orientation Image Analysis. [PDF]
J Math Imaging Visvan den Berg NJ, Mula O, Vis L, Duits R.
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Extraction of Antimicrobial Peptides From Fava Bean Protein Hydrolyzate by Phosphorylated Biochar
Food Safety and Health, EarlyView.Antimicrobial peptides were extracted by functional biochar in one step. The enriched peptides demonstrated significantly enhanced antibacterial activity. ABSTRACT The extraction of antimicrobial peptides (AMPs) from plant proteins remains challenging due to their low abundance, structural diversity, and the need for mild, efficient, and selective ...
Xiang‐Yu Huang +8 more
wiley +1 more source
Geological Journal, EarlyView.This work advances landslide susceptibility mapping by incorporating short‐term trigger data with landscape susceptibility mapping. We also examine the importance of downsampling, watershed delineation and geospatial correlations in evaluating outcomes.
Kanta Kotsugi +3 more
wiley +1 more source
Machine Learning-Based Prediction of Textural Properties and Nonlinear Regulatory Pattern Analysis of 3D-Printed Dough Containing Konjac Glucomannan. [PDF]
FoodsLeng W, Sun Y, Xie J, Pang J.
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Alternative Data for Realised Volatility Forecasting: Limit Order Book and News Stories
International Journal of Finance &Economics, EarlyView.ABSTRACT We examine whether two major alternative data sources, limit order book information and firm‐specific news, provide incremental predictive information for daily realised volatility forecasting within the HAR‐family, using a parsimonious framework to ensure practical implementation and comparability. The framework is designed for practical real‐
Eghbal Rahimikia, Ser‐Huang Poon
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Reliability, bias, and computational cost of estimating the Bayes factor using bridge sampling and the Savage-Dickey density ratio. [PDF]
Behav Res MethodsOberauer K, Musfeld P, Aust F.
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How Does AI Empower Corporate ESG Practices? Mechanisms Based on Information Processing Theory
International Journal of Finance &Economics, EarlyView.ABSTRACT In the context of the latest technological revolution and industrial transformation, Artificial Intelligence (AI) provides new impetus for the development of corporate ESG practices. This study, based on data from 2630 A‐share listed companies in China from 2010 to 2022, examines the impact of AI on corporate ESG performance and its mechanisms
Qin Zhu, Shanshan Jiang, Anna Min Du
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