Results 71 to 80 of about 143 (132)

On subset least squares estimation and prediction in vector autoregressive models with exogenous variables

Canadian Journal of Statistics, EarlyView.
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne, Thanh‐Liem Huynh, Mylène Oscar   +2 more
wiley   +1 more source

Asymptotic properties of cross‐classified sampling designs

Canadian Journal of Statistics, EarlyView.
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley   +1 more source

Forecasting New Employment Using Nonrepresentative Online Job Advertisements With an Application to the Italian and EU Labor Market

Journal of Forecasting, EarlyView.
ABSTRACT Using online job advertisement data improves the timeliness and granularity depth of analysis in the labor market in domains not covered by official data. Specifically, its variation over time may be used as an anticipator of official employment variations.
Pietro Giorgio Lovaglio, Mario Mezzanzanica   +1 more
wiley   +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

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

Intraday Functional PCA Forecasting of Cryptocurrency Returns

Journal of Forecasting, EarlyView.
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley   +1 more source

The Impact of Uncertainty on Forecasting the US Economy

Journal of Forecasting, EarlyView.
ABSTRACT This paper examines the predictive value of uncertainty measures for key macroeconomic indicators across multiple forecast horizons. We evaluate how different uncertainty proxies—economic policy uncertainty (EPU), VIX, geopolitical risk, and measures of macroeconomic and financial uncertainty—enhance forecast accuracy for industrial production,
Angelica Ghiselli
wiley   +1 more source

Multifactorial Screening for Fine‐Scale Selection of CCS Industrial Clusters and Hubs in Brazil

Greenhouse Gases: Science and Technology, EarlyView.
ABSTRACT As Brazil moves toward implementing its decarbonization commitments, carbon capture and storage (CCS) hubs are emerging as a key pathway for large‐scale CO2 abatement in hard‐to‐abate sectors. This paper presents a multifactorial, data‐driven framework to screen and prioritize potential CCS industrial clusters and hubs across Brazilian regions,
Gustavo P. Oliveira, Beatriz R. Almeida, Thiago R. C. Justino, Carlos A. S. Santos, Alex A. Santos, Fabiana Philipi   +5 more
wiley   +1 more source

Creation of a Landslide Susceptibility Map Using Short‐Term Data From the July 2018 Heavy Rainfall in Southern Hiroshima Prefecture

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, Ting Liu, Toshiro Hata, Rebecca Muenich   +3 more
wiley   +1 more source

Alternative Price Dynamics and Valuation of Flexible Strategies

International Journal of Finance &Economics, EarlyView.
ABSTRACT In this article, we study the optimal operational strategy of production projects. We investigate different underlying price models and determine the optimal barriers of transition to suspension, recovery, or irreversible abandonment of productive activity.
Cristina Bertolosi, Gianluca Fusai, Ioannis Kyriakou   +2 more
wiley   +1 more source