Results 71 to 80 of about 291,653 (252)
International Studies of Economics, EarlyView.ABSTRACT Communication with the market to guide public expectations has become a pivotal monetary policy instrument for central banks worldwide. Therefore, assessing the efficacy of communication in influencing personal expectations is essential for central banks.
Yuying Jin, Sunyao Xia
wiley +1 more source
Portfolio optimization with mixture vector autoregressive models [PDF]
arXiv, 2020 Obtaining reliable estimates of conditional covariance matrices is an important task of heteroskedastic multivariate time series. In portfolio optimization and financial risk management, it is crucial to provide measures of uncertainty and risk as accurately as possible.
arxiv
A Spatially Correlated Model with Generalized Autoregressive Conditionally Heteroskedastic Structure for Counts of Crimes [PDF]
, 2022 Isabel Escudero +2 more
openalex +1 more source
IEEE Access, 2018 In this paper, a novel time series heteroskedastic model is proposed for sea clutter modeling application. In the light of characteristics of the practical clutter at low grazing angle, the original generalized autoregressive conditional ...
Yunjian Zhang +3 more
doaj +1 more source
Energy Market Uncertainties and Gold Return Volatility: A GARCH–MIDAS Approach
Australian Economic Papers, EarlyView.ABSTRACT In this study, the GARCH–MIDAS model is utilized to evaluate how predictable oil and energy market uncertainties are in relation to gold return volatility. We examine daily gold returns and monthly energy uncertainty measurements such as oil market uncertainty (OMU) and oil price uncertainty (OPU), as well as measurements of energy market ...
Afees A. Salisu +3 more
wiley +1 more source
Dynamic Portfolio Selection on Croatian Financial Markets: MGARCH Approach
Business Systems Research, 2016 Background: Investors on financial markets are interested in finding trading strategies which could enable them to beat the market. They always look for best possibilities to achieve above-average returns and manage risks successfully. MGARCH methodology
Škrinjarić Tihana, Šego Boško
doaj +1 more source
MODEL MATEMATIK UNTUK MENENTUKAN NILAI TUKAR MATA UANG RUPIAH TERHADAP DOLLAR AMERIKA
Jurnal Teknik Industri, 1999 The main objective of this paper is to estimate parameters in the heteroskedasticity models, particularly in Auto Regressive Conditional Heteroskedasticity - ARCH(1) and Generalized Autoregressive Conditional Heteroskedasticity- GARCH(1,1).
Jani Rahardjo +2 more
doaj
A mixture autoregressive model based on Student's $t$-distribution [PDF]
arXiv, 2018 A new mixture autoregressive model based on Student's $t$-distribution is proposed. A key feature of our model is that the conditional $t$-distributions of the component models are based on autoregressions that have multivariate $t$-distributions as their (low-dimensional) stationary distributions.
arxiv
PREDICTIVE DENSITY COMBINATION USING BAYESIAN MACHINE LEARNING
International Economic Review, EarlyView.Abstract Based on agent opinion analysis theory, Bayesian predictive synthesis (BPS) is a framework for combining predictive distributions in the face of model uncertainty. In this article, we generalize existing parametric implementations of BPS by showing how to combine competing probabilistic forecasts using interpretable Bayesian tree‐based machine
Tony Chernis +4 more
wiley +1 more source
The impact of the COVID-19 pandemic and the Russian invasion of Ukraine on Gold markets
Business, Management and Economics EngineeringPurpose – The study examines global Gold market performance and correlations between COVID-19, the Russian invasion, inflation, investors’ fear, asymmetric shocks, and the VIX (volatility index) impact on volatility.
Fisnik Morina +3 more
doaj +1 more source