Results 241 to 250 of about 334,825 (304)

A dynamic micro-macro-economic model to assess water charging policies.

J Clean Prod
Sapino F, Parrado R, Pérez-Blanco CD.
europepmc   +1 more source

Stock Forecasting Based on Informational Complexity Representation: A Framework of Wavelet Entropy, Multiscale Entropy, and Dual-Branch Network. [PDF]

Entropy (Basel)
Tian G, Xu C, Yang Y.
europepmc   +1 more source

Daily Residential Natural Gas Demand Forecasting Using Machine Learning Regression: Comparative Evaluation With a Case Study in Qazvin Province, Iran

Energy Science &Engineering, EarlyView.
This graphical abstract summarizes the proposed framework for improving short‐term residential natural gas consumption forecasting by integrating a novel socioeconomic indicator, the subscription growth ratio (SGR), with conventional meteorological variables.
Ali Pirzad, Mostafa Khanzadi
wiley   +1 more source

Macroeconomic-aware forecasting of construction costs in developing countries: Using gated recurrent unit and long short-term memory deep learning framework. [PDF]

PLoS One
Alzara M, Gihad N, Abdou H, Soltan A, Hilal A, Ehab A, Ehab A.   +6 more
europepmc   +1 more source

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches

Journal of Forecasting, EarlyView.
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann, Mawuli Segnon, Timo Wiedemann   +2 more
wiley   +1 more source

Influence of equity structure in China's high-tech manufacturing industry on enterprise value under epidemic shocks. [PDF]

Sci Rep
Yao J, Jiang Q.
europepmc   +1 more source

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

The effect of macroeconomic shocks on non-performing loans and credit risk in the iranian banking system using time-varying parameter vector autoregressions. [PDF]

PLoS One
Peykani P, Sargolzaei M, Oprean-Stan C, Kamyabfar H, Reghabi A.   +4 more
europepmc   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Forecasting House Prices: The Role of Market Interconnectedness

Journal of Forecasting, EarlyView.
ABSTRACT While the existing research uncovers interconnections between various housing markets, it largely ignores the question of whether such linkages can improve house price predictions. To address this issue, we proceed in two steps. First, we forecast disaggregated house price growth rates from Australia and China to determine whether ...
Zac Chen, George Milunovich, Shuping Shi, Ben Wang   +3 more
wiley   +1 more source