Results 91 to 100 of about 97,715 (338)

MODELING FACTORS AFFECTING NET ASSETS OF INVESTMENT FUNDS USING AUTOREGRESSIVE DISTRIBUTED LAG (ARDL) MODEL

, 2020
The article focuses on econometric modelling of the factors affecting the net assets of investment funds as an example of “Kamalak’ and “Daromad-plus” investment funds in the form of open joint stock company using autoregressive distributed lag (ARDL ...
Abdullaev Ilyоs Sultanovich, Khamraev Kuvvat Iskandarovich   +1 more
semanticscholar   +1 more source

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

On Distributed Lags in Dynamic Panel Data Models: Evidence from Market Shares [PDF]

The objective of this paper is twofold: First, the applicability of a widely used dynamic model, the autoregressive distributed lag model (ARDL), is scrutinized in a panel data setting. Second, Chile’s development of market shares in the EU market in the
Dierk Herzer, Felicitas Nowak-Lehmann, Inmaculada Martínez-Zarzoso, Sebastian Vollmer   +3 more
core  

Waves of Uncertainty: Crude Oil Under Geopolitical, Economic, and ESG Turbulence

Energy Science &Engineering, EarlyView.
Dynamic copula and wavelet coherence reveal that geopolitical, economic, and sustainability uncertainties significantly shape crude oil price co‐movements. Long‐term coherence, especially post‐2015, highlights the growing role of ESG risks alongside geopolitical shocks and economic crises in global energy risk transmission.
Sana Braiek, Naif Alsagr, Aamir Aijaz Syed, Ahmed Jeribi   +3 more
wiley   +1 more source

Problems in Applying Dynamic Panel Data Models: Theoretical and Empirical Findings [PDF]

The objective of this paper is twofold: First, the applicability of a widely used dynamic model, the autoregressive distributed lag model (ARDL), is scrutinized in a panel data setting. Second, Chile’s development of market shares in the EU market in the
Dierk Herzer, Felicitas Nowak-Lehmann D., Inmaculada Martínez-Zarzoso, Sebastian Vollmer   +3 more
core  

Emissions Reductions and Economic Feasibility of China's Solar Thermal Power Industry After the Introduction of Chinese Certified Emission Reduction Policy

Energy Science &Engineering, EarlyView.
ABSTRACT To promote the development of renewable energy, China re‐implemented the Chinese Certified Emission Reduction (CCER) policy in 2023. This study explores certificated CO2 and air pollutants (i.e., NOx, SO2 and particulate matter (PM)) emissions reductions from China's solar thermal power (STP) industry at national scale and conducts the ...
Yun Li, Xintong Liu, Yaxuan Han, Xiaoda Xue   +3 more
wiley   +1 more source

A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets

Journal of Forecasting, EarlyView.
ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c$$ c $$ latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley   +1 more source

Long Run and Short Effects in Static Panel Models [PDF]

For short and fat panels the Mundlak model can be viewed as an approximation of a general dynamic autoregressive distributed lag model. We give an exact interpretation of short run and long effects and provide simulations to assess the quality of the ...
Michael Pfaffermayr, Peter Egger
core  

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

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