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Bayesian predictive distributions of oil returns using mixed data sampling volatility models
Virbickaite, Audrone; Nguyen, Hoang; Minh-Ngoc Tran - 2023
This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an … extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models … Stochastic Volatility (SV), along with Mixed Data Sampling (MIDAS) regressions, which enable us to incorporate the impacts of …
Persistent link: https://www.econbiz.de/10014252427
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Returns in commodities futures markets and financial speculation : a multivariate GARCH approach
Manera, Matteo; Nicolini, Marcella; Vignati, Ilaria - 2012
This paper analyses futures prices for four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) and five agricultural commodities (corn, oats, soybean oil, soybeans and wheat), over the period 1986-2010. Using CCC and DCC multivariate GARCH models, we find that...
Persistent link: https://www.econbiz.de/10009535531
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An empirical investigation of direct and iterated multistep conditional forecasts
McCracken, Michael W.; McGillicuddy, Joseph - 2017
When constructing unconditional point forecasts, both direct- and iterated-multistep (DMS and IMS) approaches are common. However, in the context of producing conditional forecasts, IMS approaches based on vector autoregressions (VAR) are far more common than simpler DMS models. This is despite...
Persistent link: https://www.econbiz.de/10011782870
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Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models
Nguyen, Hoang; Virbickaite, Audrone - 2022
Stock and oil relationship is usually time-varying and depends on the current economic conditions. In this study, we propose a new Dynamic Stochastic Mixed data frequency sampling (DSM) copula model, that decomposes the stock-oil relationship into a short-run dynamic stochastic component and a...
Persistent link: https://www.econbiz.de/10013258038
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STAR-GARCH models for stock market interactions in the Pacific Basin region, Japan and US
Busetti, Giorgio; Manera, Matteo - 2003
We investigate the financial interactions between countries in the Pacific Basin region (Korea, Singapore, Malaysia, Hong Kong and Taiwan), Japan and US. The originality of the paper is the use of STAR-GARCH models, instead of standard correlation-cointegration techniques. For each country in...
Persistent link: https://www.econbiz.de/10011591386
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Large vector autoregressions with asymmetric priors
Carriero, Andrea; Clark, Todd E.; Marcellino, Massimiliano - 2015 - This draft: November 2015
We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...
Persistent link: https://www.econbiz.de/10011389735
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Evaluating density forecasts with an application to stock market returns
Raaij, Gabriela de; Raunig, Burkhard - 2002
Persistent link: https://www.econbiz.de/10001650402
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A reality check on the GARCH-MIDAS volatility models
Virk, Nader Shahzad; Javed, Farrukh; Awartani, Basel - 2021
Persistent link: https://www.econbiz.de/10012604771
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Prediction accuracy of bivariate score-driven risk premium and volatility filters : an illustration for the Dow Jones
Blazsek, Szabolcs; Escribano, Álvaro; Licht, Adrian - 2020
Persistent link: https://www.econbiz.de/10012310604
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The contribution of frictions to expected returns
Hirakiy, Kazuhiro; Skiadopoulos, George - 2018
We derive a model-free option-based formula to estimate the contribution of market frictions to expected returns (CFER) within an asset pricing setting. We estimate CFER for the U.S. optionable stocks. We document that CFER is sizable, it predicts stock returns and it subsumes the effect of...
Persistent link: https://www.econbiz.de/10011932555