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Journal ArticleDOI

Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment

TLDR
In this article, the extent of co-movement (measured by correlation coefficients) among the nominal price returns of 11 major energy, agricultural, and food commodities was analyzed using monthly data between 1970 and 2013.
About
This article is published in Energy Economics.The article was published on 2016-06-01. It has received 137 citations till now. The article focuses on the topics: Commodity.

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Forecasting: theory and practice

Fotios Petropoulos, +84 more
- 04 Dec 2020 - 
TL;DR: A non-systematic review of the theory and the practice of forecasting, offering a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts.
Journal ArticleDOI

High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets

TL;DR: In this paper, the authors investigated the realised volatility connectedness of US crude oil futures and five China's agricultural commodity futures using connectedness measures and high-frequency data, and showed that market interdependence has increased for negative volatility relative to positive volatility, implying that volatility transmission has a leverage effect across markets.
Journal ArticleDOI

Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis

TL;DR: In this paper, the authors evaluated the association between crude oil prices and world food price indices, first within general space and time, and then within the combined time-frequency sphere.
Journal ArticleDOI

Forecasting: theory and practice

TL;DR: In this paper , the authors provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organize, and evaluate forecasts.
Journal ArticleDOI

Volatility transmissions across international oil market, commodity futures and stock markets: Empirical evidence from China

TL;DR: In this paper, a trivariate VAR-BEKK-GARCH model was used to investigate the dynamic relationship among the Chinese stock market, commodity markets and global oil price.
References
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Investment Under Uncertainty

TL;DR: In this article, Dixit and Pindyck provide the first detailed exposition of a new theoretical approach to the capital investment decisions of firms, stressing the irreversibility of most investment decisions, and the ongoing uncertainty of the economic environment in which these decisions are made.
Journal ArticleDOI

The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics

TL;DR: The Lagrange multiplier (LM) statistic as mentioned in this paper is based on the maximum likelihood ratio (LR) procedure and is used to test the effect on the first order conditions for a maximum of the likelihood of imposing the hypothesis.
Journal ArticleDOI

Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models

TL;DR: In this article, a new class of multivariate models called dynamic conditional correlation models is proposed, which have the flexibility of univariate generalized autoregressive conditional heteroskedasticity (GARCH) models coupled with parsimonious parametric models for the correlations.
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Multivariate Simultaneous Generalized ARCH

TL;DR: In this paper, a new parameterization of the multivariate ARCH process is proposed and equivalence relations are discussed for the various ARCH parameterizations, and conditions suffcient to guarantee the positive deffniteness of the covariance matrices are developed.
Journal ArticleDOI

Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model.

TL;DR: In this article, a multivariate time series model with time varying conditional variances and covariances but with constant conditional correlations is proposed, which is readily interpreted as an extension of the seemingly unrelated regression (SUR) model allowing for heteroskedasticity.
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