Results 121 to 130 of about 236,683 (240)

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Renewable Energy Use, Agricultural Productivity, and Economic Expansion Impact on Environmental Sustainability in India

Energy Science &Engineering, EarlyView.
ABSTRACT This research aims to explore the effects of agricultural productivity and the use of renewable energy sources on India's CO2 emissions while taking economic expansion into concern based on data during 1985–2022. This study applies the autoregressive distributed lag (ARDL) technique, dynamic‐ordinary least square (DOLS), fully‐modified ...
Palanisamy Manigandan, Radulescu Magdalena, Duraisamy Pachiyappan, Nadia Sha, Marian Cristescu   +4 more
wiley   +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

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

Causal K-Means Clustering. [PDF]

J R Stat Soc Series B Stat Methodol
Kim K, Kim J, Kennedy EH.
europepmc   +1 more source

Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach

Journal of Forecasting, EarlyView.
ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch, Candace Berrett, Mason Ferlic, Kimberly F. Sellers   +3 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

Forecasting Volatility of Commodity, Currency, and Stock Markets: Evidence From Markov‐Switching Multifractal Models

Journal of Forecasting, EarlyView.
ABSTRACT This paper adopts a bivariate Markov‐switching multifractal (BMSM) model to reexamine comovement in SV between commodity, foreign exchange (FX), and stock markets. After the 2007–2008 global financial crisis understanding volatility linkages and the correlation structure between these markets becomes very important for risk analysts, portfolio
Ruipeng Liu, Mawuli Segnon, Oguzhan Cepni, Rangan Gupta   +3 more
wiley   +1 more source

Evaluating Forecasts at Multiple Horizons: An Extension of the Diebold–Mariano Approach

Journal of Forecasting, EarlyView.
ABSTRACT Forecast accuracy tests are fundamental tools for comparing competing predictive models. The widely used Diebold–Mariano (DM) test assesses whether differences in forecast errors are statistically significant. However, its standard form is limited to pairwise comparisons at a single forecast horizon.
Andrew Grant, Matus Mrazik, Steve Satchell   +2 more
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