Results 101 to 110 of about 42,233 (256)
Improving Portfolio Optimization by DCC And DECO GARCH: Evidence from Istanbul Stock Exchange [PDF]
In this paper, the performance of global minimum variance (GMV) portfolios constructed by DCC and DECO-GARCH are compared to that of GMV portfolios constructed by sample covariance and constant correlation methods in terms of reduced volatility.
Yilmaz, Tolgahan
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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 +4 more
wiley +1 more source
Seize the Moments: Approximating American Option Prices in the GARCH Framework [PDF]
This paper proposes an efficient approach to compute the prices of American style options in the GARCH framework. Rubinstein's (1998) Edgeworth tree idea is combined with the analytical formulas for moments of the cumulative return under GARCH developed ...
Caroline Sasseville +3 more
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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
Estimation of temporally aggregated multivariate GARCH models [PDF]
This paper investigates the performance of quasi maximum likelihood (QML) and nonlinear least squares (NLS) estimation applied to temporally aggregated GARCH models.Since these are known to be only weak GARCH, the conditional variance of the aggregated ...
Hafner, C.M., Rombouts, J.V.K.
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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 +3 more
wiley +1 more source
Accurate Value-at-Risk Forecast with the (good old) Normal-GARCH Model [PDF]
A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model.
Stefan Mittnik +2 more
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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
A multivariate generalized independent factor GARCH model with an application to financial stock returns [PDF]
We propose a new multivariate factor GARCH model, the GICA-GARCH model , where the data are assumed to be generated by a set of independent components (ICs).
Antonio García-Ferrer +2 more
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