Results 111 to 120 of about 30,945,589 (274)
A Multivariate Generalized Orthogonal Factor GARCH Model [PDF]
The paper studies a factor GARCH model and develops test procedures which can be used to test the number of factors needed to model the conditional heteroskedasticity in the considered time series vector.
Saikkonen, Pentti, Lanne, Markku
core
Threshold Asymmetric Conditional Autoregressive Range (TACARR) Model
Journal of Forecasting, EarlyView.ABSTRACT This paper introduces a Threshold Asymmetric Conditional Autoregressive Range (TACARR) model for analyzing the daily price ranges of financial assets. The proposed formulation assumes that the conditional expected range switches between two regimes, representing upward and downward market states, with the disturbance distribution also allowed ...
Isuru Ratnayake, V. A. Samaranayake
wiley +1 more source
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
Garch Parameter Estimation Using High-Frequency Data [PDF]
Estimation of the parameters of Garch models for financial data is typically based on daily close-to-close returns. This paper shows that the efficiency of the parameter estimators may be greatly improved by using volatility proxies based on intraday ...
Visser, Marcel P.
core
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
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
The Role of Variance Risk Premium in Derivative Pricing: Modeling, Estimation and Impact
Journal of Futures Markets, EarlyView.ABSTRACT This paper estimates a model where variance risk premiums (VRP) is not fully explained by equity risk premiums (ERP). This separation can be detected thanks to a new breed of GARCH models with enough innovations to disconnect returns from variances. This type of risk‐neutralization is compatible with continuous‐time settings.
Marcos Escobar‐Anel +2 more
wiley +1 more source
Brexit and Its Impact on EU Financial Markets
International Journal of Finance &Economics, EarlyView.ABSTRACT We investigate the impact of Brexit on volatility spillovers across the EU countries. We introduce a Brexit intensity measure that assigns an intensity score reflective of the financial markets' reaction to the events that occurred as Brexit negotiations began to unfold.
Marwan Izzeldin +3 more
wiley +1 more source
International Journal of Finance &Economics, EarlyView.ABSTRACT This study examines risk transmission and co‐movements between financial markets (G7 countries and China) and commodity markets (gold and oil) during the COVID‐19 crisis. Daily closing prices for major equity indices (CAC40, CSI300, DAX30, FTSE100, MIB, NIKKEI, TSX and S&P500) and futures prices for gold, brent and WTI were analysed using DCC ...
V. Moutinho +3 more
wiley +1 more source