Time-frequency dynamics of return spillover from crude oil to agricultural commodities

ABSTRACT

We explore return spillover from crude oil to ethanol, corn, soybean and wheat on daily data during 17 May 2005–27 June 2018. This study is unique in capturing the time-frequency dynamics of return spillover. We use the frequency-dependent spillover measure that jointly captures information from time and frequency domain. We also identify two endogenous break dates that segregate the study period in three sub-periods. Our results indicate that return spillover from crude oil to ethanol, major feed stocks (i.e. corn and soybean) and food crop (i.e. wheat) is pronounced only in lower frequency band or long-term (more than 1 month). We find that return spillover is stronger only during 2005–2010, i.e. the period of energy and food crisis.     

Financialization of agricultural commodities: Evidence from China

Speculation in the commodity futures market distorts commodity prices, driving them away from rational levels. This phenomenon, which is known as the financialization of commodities, has raised significant concerns in recent years. Particularly, in the agricultural market, ‘financialized’ commodities have been blamed for high world food prices. In this paper, we examine the financialization of agricultural commodities in China. To do so, a time-varying copula is employed to investigate the dependence structure between commodities and stock markets. Four insightful results are obtained. First, positive correlations between agricultural commodities and stock markets demonstrate the financialization of agricultural commodities. Second, the identified correlations are time-varying and idiosyncratic with respect to products. Third, the agricultural commodity market is more closely correlated with the domestic stock market than with the overseas market. Fourth, a growing dependence between commodities and the stock markets is detected and the co-movement became stronger after the global financial crisis.     

How index investment impacts commodities: A story about the financialization of agricultural commodities

This paper focuses on the impact of financial investors on agricultural prices, a phenomenon known as the financialization. In this aim, we check whether financial mechanisms drive extreme values and the mean of agricultural returns in the same way. Relying on the Threshold AutoRegressive Quantile (TQAR) methodology, we find evidence of reinforcement linkages between equity and agricultural markets since 2004, corresponding to the rise in inflows of institutional investors in commodity markets. These results show that agents impact more deeply commodity markets when the commodity index value is high. In addition, in extreme quantiles (0.75 and 0.90) of agricultural returns, the relationship between agricultural and stock returns is always significant when the commodity index return is in the higher regime. This finding suggests that, stock markets had a greater impact on agricultural price dynamics during the extreme movements which occurred during the 2007–2008 financial crisis, highlighting a potential influence of financial markets on the financialization of commodities.     

Revisiting global economic activity and crude oil prices: A wavelet analysis

Based on the wavelet analysis approach, this paper firstly examines the dynamic relationship between global economic activity (proxied by the Kilian economic index) and crude oil prices in both time- and frequency-domains. Our empirical results demonstrate significant correlation between crude oil prices and global economic activity at high frequencies (in the short run) during the entire sample period; however, the co-movement between the two at low frequencies (in the long run) is weaker and exists only during certain proportions of the sample period. We also document evidence that global economic activity and oil price are positively correlated, with dynamic lead-lag relationships across time. Our findings are robust to alternative choices of oil price indexes and controlling for other confounding factors such as geopolitical risk, armed conflicts, economic policy uncertainty and equity market uncertainty. The current study provides valuable implications for oil market investors based on the information of global economic situation and its dynamic relationships with oil prices.     

Oil price and automobile stock return co-movement: A wavelet coherence analysis

This paper explores possible co-movement between oil price and automobile stock return in a joint time-frequency domain. Daily price series from August 01, 1996 to June 20, 2017 is used in this analysis. The results indicate that the co-movement between oil price and automobile stock return is strong during November, 2000–December, 2002 and March, 2006–December, 2009. The co-movement is found to be more pronounced in the long-term and stock return is sensitive to the higher oil price emanating from the demand shock. This contravenes the conventional wisdom that crude oil is always counter-cyclical to the automobile stocks. For investor, this weakens the probable gain from including oil asset in a portfolio of automobile stocks as crude oil does not offer cushion against bearish automobile stock markets during the crisis period.     

China's liberalizing stock market,crude oil,and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach

China is the world's largest oil importer, and therefore the correlations between stock indices and highly volatile oil prices deserve close examination when investing in China's gradually liberalizing stock market. Another concern for international investors is whether safe-haven assets can reduce portfolio risks for investment in China. The paper makes two main contributions. First, we develop a novel method of examining a multivariate dependence structure by combining wavelet analysis with the vine copula model. Second, we apply the proposed methodology to study the correlations between China's liberalizing stock market, petroleum, and safe-haven assets at different frequencies. We find that the multidimensional dependence of these assets has been altered as a result of the 2008 global financial crisis. Moreover, the vine structures exhibit dependence patterns that vary over time horizons, indicating that the multidimensional dependence is sensitive to time scales.     

Crude oil and BRICS stock markets under extreme shocks: New evidence

In this paper, we propose an extreme Granger causality analysis model to uncover the causal links between crude oil and BRICS stock markets. Instead of analyzing the average causal relationship, as is usually done, we first decompose the data into three cumulative components and investigate the causality between different combinations of extreme positive, extreme negative and normal shocks. These types of combinations can describe all facets of the interactions between crude oil and BRICS stock markets, especially under extreme shocks. In contrast to the results obtained by the traditional Granger causality test, our empirical findings demonstrate that the effect of oil price changes on the stock markets is stronger under extreme circumstances than under normal circumstances. Furthermore, large upward or downward oil price changes have an asymmetric impact on extreme upward or downward stock price changes. Finally, robustness checks verify the rationality and validity of the extreme Granger causality analysis.     

A multivariate time series analysis of energy consumption,real output and pollutant emissions in a developing economy: New evidence from Nepal

Mountain economies will have to play a central role in attaining the global pursuit of green economic growth as crucial bearers of ecosystems goods and services. However, these economies are not adequately represented in the development policy debates in spite of their fundamental importance towards global sustainable development. This study examines the inter relationships between energy consumption, output and carbon emissions in a developing mountainous economy using an augmented Vector Autoregression model. Time-series data over the period 1975–2013 is studied applying a multivariate framework using population and gross fixed capital formation as additional variables for Nepal. Testing for Granger causality between integrated variables based on asymptotic theory reveals a long-run unidirectional Granger causality running from GDP to energy consumption, and a unidirectional Granger causality running from carbon emissions to GDP. We suggest that the government of Nepal can address energy poverty by accelerating the adoption energy conservation policies such as rationing energy consumption and energy efficiency improvements to narrow the energy supply-demand gap. The opportunity to promote the uptake of decentralised off-grid renewable technologies in remote areas and the large scale development of hydropower at the national level also needs to be prioritized. Our results remain robust across different estimators and contributes to an emerging literature on the nexus relationships between energy consumption, income and carbon emissions in mountainous developing economies.