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Markov switching GARCH models for Bayesian hedging on energy futures markets

Billio, Monica; Casarin, Roberto; Osuntuyi, Anthony - In: Energy economics 70 (2018), pp. 545-562

Persistent link: https://www.econbiz.de/10011942887

Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks

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Out-of-sample prediction of the oil futures market volatility : a comparison of new and traditional combination approaches

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Forecasting the oil futures price volatility : large jumps and small jumps

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Forecasting oil futures price volatility : new evidence from realized range-based volatility

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Realized higher-order moments spillovers between commodity and stock markets : evidence from China

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The role of higher moments in predicting China's oil futures volatility : evidence from machine learning models

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Intraday return predictability in China's crude oil futures market : new evidence from a unique trading mechanism

Wen, Danyan; Wang, Yudong; Zhang, Yaojie - In: Economic modelling 96 (2021), pp. 209-219

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Markov Switching GARCH Models for Bayesian Hedging on Energy Futures Markets

Billio, Monica - 2015

A new Bayesian multi-chain Markov Switching GARCH model for dynamic hedging in energy futures markets is developed by constructing a system of simultaneous equations for the return dynamics on the hedged portfolio and futures. More specifically, both the mean and variance of the hedged portfolio...

Persistent link: https://www.econbiz.de/10013033418

Markov switching GARCH models for Bayesian hedging on energy futures markets

Billio, Monica; Casarin, Roberto; Osuntuyi, Anthony - 2014

Persistent link: https://www.econbiz.de/10011629426