Results 71 to 80 of about 984,341 (254)

Evaluating the hedging performance of multivariate GARCH models

Asia Pacific Management Review, 2019
Mixed results have been documented for the hedging performance of multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. This paper investigates this issue by evaluating representative models (Baba−Engle−Kraft−Kroner [BEKK]
Yu‐Sheng Lai
semanticscholar   +1 more source

Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH [PDF]

SSRN Electronic Journal, 2010
The paper examines the performance of several multivariate volatility models, namely CCC, VARMA-GARCH, DCC, BEKK and diagonal BEKK, for the crude oil spot and futures returns of two major benchmark international crude oil markets, Brent and WTI, to calculate optimal portfolio weights and optimal hedge ratios, and to suggest a crude oil hedge strategy ...
Chang, Chia-Lin, McAleer, Michael, Tansuchat, Roengchai   +2 more
openaire   +5 more sources

From Reactive to Proactive Volatility Modeling With Hemisphere Neural Networks

Journal of Applied Econometrics, EarlyView.
ABSTRACT We revisit maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres. Our architecture features several key ingredients making MLE work in this context.
Philippe Goulet Coulombe, Mikael Frenette, Karin Klieber   +2 more
wiley   +1 more source

Asymmetric multivariate normal mixture GARCH [PDF]

, 2008
An asymmetric multivariate generalization of the recently proposed class of normal mixture GARCH models is developed. Issues of parametrization and estimation are discussed.
Haas, Markus, Mittnik, Stefan, Paolella, Marc S.   +2 more
core  

Functional generalized autoregressive conditional heteroskedasticity [PDF]

, 2015
Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the focus of research
Aue, Alexander, Horvath, Lajos, Pellatt, Daniel   +2 more
core   +2 more sources

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

Forecasting Related Time Series

Journal of Applied Econometrics, EarlyView.
ABSTRACT A collection of time series are “related” if they follow similar stochastic processes and/or they are statistically dependent. This paper proposes a related time series (RTS) forecasting model that exploits these relationships. The model's foundation is a set of univariate Gaussian autoregressions, one for each series, which are then augmented
Ulrich K. Müller, Mark W. Watson
wiley   +1 more source

Further evidence on the determinants of regional stock market integration in Latin America [PDF]

The European Journal of Comparative Economics, 2013
This paper employs a conditional version of the International Capital Asset Pricing Model (ICAPM) to investigate the determinants of regional integration of stock markets in the Latin America over the period 1996-2008. This model allows for three sources
Khaled Guesmi, Duc Khuong Nguyen, Frédéric Teulon   +2 more
doaj  

Revisiting EWMA in High‐Frequency‐Based Portfolio Optimization: A Comparative Assessment

Journal of Applied Econometrics, EarlyView.
ABSTRACT This paper compares the statistical and economic performance of state‐of‐the‐art high‐frequency (HF) based multivariate volatility models with a simpler, widely used alternative, the Exponentially Weighted Moving Average (EWMA) filter. Using over two decades of 100 U.S.
Laura Capera Romero, Anne Opschoor
wiley   +1 more source