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oai:docta.ucm.es:20.500.14352/275052023-11-14T07:19:41Zcom_20.500.14352_14col_20.500.14352_17
Docta Complutense author Chang, Chia-Lin author Li, Yiying author McAleer, Michael 2023-06-18T10:25:20Z 2023-06-18T10:25:20Z 2015-06 2341-2356 https://hdl.handle.net/20.500.14352/27505 http://www.ucm.es/fundamentos-analisis-economico2/documentos-de-trabajo-del-icae Energy and agricultural commodities and markets have been examined extensively, albeit separately, for a number of years. In the energy literature, the returns, volatility and volatility spillovers (namely, the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset), among alternative energy commodities, such as oil, gasoline and ethanol across different markets, have been analysed using a variety of univariate and multivariate models, estimation techniques, data sets, and time frequencies. A similar comment applies to the separate theoretical and empirical analysis of a wide range of agricultural commodities and markets. Given the recent interest and emphasis in bio-fuels and green energy, especially bio-ethanol, which is derived from a range of agricultural products, it is not surprising that there is a topical and developing literature on the spillovers between energy and agricultural markets. Modelling and testing spillovers between the energy and agricultural markets has typically been based on estimating multivariate conditional volatility models, specifically the BEKK and DCC models. A serious technical deficiency is that the Quasi-Maximum Likelihood Estimates (QMLE) of a full BEKK matrix, which is typically estimated in examining volatility spillover effects, has no asymptotic properties, except by assumption, so that no statistical test of volatility spillovers is possible. Some papers in the literature have used the DCC model to test for volatility spillovers. However, it is well known in the financial econometrics literature that the DCC model has no regularity conditions, and that the QMLE of the parameters of DCC has no asymptotic properties, so that there is no valid statistical testing of volatility spillovers. The purpose of the paper is to evaluate the theory and practice in testing for volatility spillovers between energy and agricultural markets using the multivariate BEKK and DCC models, and to make recommendations as to how such spillovers might be tested using valid statistical techniques. Three new definitions of volatility and covolatility spillovers are given, and the different models used in empirical applications are evaluated in terms of the new definitions and statistical criteria. eng Volatility Spillovers Between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice technical report URL https://docta.ucm.es/bitstreams/f4225719-74b8-4ec1-87ed-07bac63d4476/download File MD5 ea718ef125b151cd98015f7ffce4b8df 497446 application/pdf 1508.pdf URL https://docta.ucm.es/bitstreams/83a811d4-33f8-4a0c-80aa-c2314b16a6b1/download File MD5 6801b77014051335e4211c1a53bb4dc1 67562 text/plain 1508.pdf.txt