Results 101 to 110 of about 3,197 (255)

A multivariate realized GARCH model

Journal of Econometrics
We propose a novel class of multivariate GARCH models that incorporate realized measures of volatility and correlations. The key innovation is an unconstrained vector parametrization of the conditional correlation matrix, which enables the use of factor models for correlations.
Archakov, Ilya, Hansen, Peter Reinhard, Lunde, Asger   +2 more
openaire   +2 more sources

Improved Conservative Scheme for Lenard‐Bernstein Collisions in Gyrokinetic Turbulence Simulations

Contributions to Plasma Physics, EarlyView.
ABSTRACT Turbulence in the edge and scrape‐off layer regions plays a critical role for the performance of future magnetic confinement fusion power plants. Gyrokinetic simulations allow studying this regime with high fidelity. A key aspect in these regions is the high concentration of impurities, which can radiate energy, leading to significant losses ...
Andrew Ivan Sulimro, Philipp Ulbl, Jordy Trilaksono, Frank Jenko   +3 more
wiley   +1 more source

How Multiple Streams Influence Agenda‐Setting for Water Reuse in Swiss Substates

Environmental Policy and Governance, EarlyView.
ABSTRACT As climate change creates significant challenges for both the environment and society, potential mitigation and adaptation solutions are widely discussed. Yet, neither challenges nor their potential solutions automatically reach the political agenda or lead to a policy decision.
Magdalena A. Knabl, Katrin Pakizer, Manuel Fischer, Eberhard Morgenroth, Christian Binz   +4 more
wiley   +1 more source

MODELING ROMANIAN EXCHANGE RATE EVOLUTION WITH GARCH, TGARCH, GARCH- IN MEAN MODELS [PDF]

Annals of the University of Oradea: Economic Science, 2011
In this paper we analyze the return of exchange rate in order to test and analyze the best models which are capable of forecasting accurately there evolution. We apply the GARCH family models on the exchange rate return in order to obtain the best models
Cociuba Mihail Ioan, Trenca Ioan
doaj  

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
wiley   +1 more source

Comparison of Symmetrical; Asymmetrical; and Logarithmic Models Using GARCH; GJR-GARCH; and EGARCH Method in Forecasting Indonesia–USA Currency Volatility

Ekonometria
Aim: The main object of this study was to present a comparison between GARCH models, i.e. the standard GARCH model, asymmetric GJR-GARCH, and logarithmic EGARCH on exchange rate (IDR/USD) volatility.
Juwita Suwondo, Rern-Jay Hung, Eko Yuni Prihantono, Renaldi   +3 more
doaj   +1 more source

A Novel Text‐Based Framework for Forecasting Carbon Prices

Journal of Forecasting, EarlyView.
ABSTRACT This study proposes a text‐based framework for predicting EU carbon prices. Using weekly data from 2020 to 2024, we construct a multivariate dataset combining financial indicators, commodity prices, Google Trends measures, and news‐based sentiment extracted using FinBERT.
Christian Oliver Ewald, Yaoyu Li
wiley   +1 more source

Beta Forecasting With Realized Beta Estimators and Machine Learning Algorithms

Journal of Forecasting, EarlyView.
ABSTRACT This paper applies machine learning algorithms to the modeling of realized betas for the purposes of forecasting stock systematic risk. Higher levels of beta forecast accuracy are demonstrated, relative to other studies in the literature. These improvements are also highly significant, both statistically and economically.
Bao Doan, Dulani Jayasuriya, John B. Lee, Jonathan J. Reeves   +3 more
wiley   +1 more source

Predicting volatility of cryptocurrencies: Deep learning and GARCH family models

Modern Finance
This paper examines the application of econometric models, deep learning architectures, and hybrid combinations of both methods for volatility forecasting in cryptocurrency markets. Using daily data on 10 major cryptocurrencies from 2020–2025, this work
Abdul Moiz, Hassan Raza
doaj   +1 more source

MARS‐Diff: Guarded Residual Diffusion for Leakage‐Disciplined Probabilistic Portfolio‐Loss Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT This paper develops Masked Asset–Regime Scenario Diffusion (MARS‐Diff), a leakage‐disciplined framework for probabilistic forecasting of multiday portfolio losses. The framework combines a regularized heterogeneous autoregressive model with exogenous predictors (HAR‐X) as its anchor, a train‐only masked representation of a high‐dimensional ...
Çağlar Sözen, Mervenur Sözen
wiley   +1 more source