Transmission of risks between energy and agricultural commodities: Frequency time-varying VAR, asymmetry and portfolio management

This paper examines energy and agricultural commodities' short-run and long-run connectedness by using the Time-varying parameter vector autoregressions (TVP-VAR). It applies the frequency version of the TVP-VAR model, which is a modified version of the dynamic TVP-VAR model. The frequency decomposition definition also decomposes into short-run and long-run connectedness. We further the analysis by investigating the effect of asymmetry in returns on connectedness. It also examines how portfolio management strategies would lead to a maximization of profits with minimal risks. Empirical evidence indicates that only 32.52% and 31.38% of connectedness in oil and gas, respectively, are transmitted to agricultural commodities, which suggests their weak tendencies in influencing agricultural commodities;the total connectedness index hovers around 40–60% in the 2018–2019 period;however, it dropped below 40% in 2020–2021 when the COVID-19 pandemic contributed to disintegrate the connectedness between energy and agricultural commodities but increased further during the 2022 Russia-Ukraine saga. The findings also indicate that corn, wheat, and flour are net transmitters of risks to oil and natural gas in the long and short-run, and wheat-flour pairwise connectedness is the strongest in the connectedness. Asymmetry is also pronounced in the network of connectedness. Portfolio analyses indicate that investors require a low proportion of energy in a portfolio of energy-agricultural commodities to achieve an optimum profit. The findings will offer exciting insights into the connectedness of agricultural and energy commodities, particularly during periods of high price uncertainty.

The Impact of COVID-19 on Global Indica and Japonica Rice Markets: Examining by an Endogenous Agricultural Investment Model

Indica and japonica rice are commonly subjected to different market structures, and the international prices for both subspecies display different trends. The global indica and japonica rice markets in the mid and long term under climate change conditions were projected by the Rice Economy Climate Change (RECC) model. Additionally, endogenous agricultural investments were incorporated into the projections. A COVID-19 pandemic scenario was stimulated to observe its impact on the global indica and japonica rice markets. The results indicated that agricultural investments are expected to decrease in many indica rice-producing countries, whereas the investments will increase in many japonica riceproducing countries in the long term. Therefore, the global indica rice production will decrease due to its investment reduction;however, global japonica rice production will increase in the mid and long term. Due to the COVID-19 scenario, the international indica and japonica rice prices would decrease in 2020 due to the unprecedented shrinking economies worldwide, but the prices would increase from 2021 to 2040 compared with the baseline average of the price projections with the RECC model. The scenario simulation results reveal that the japonica rice markets are projected to have less impact than the indica rice markets from the COVID-19 pandemic © 2022, Japan Agricultural Research Quarterly.All Rights Reserved.

The Impact of COVID-19 on Global Indica and Japonica Rice Markets: Examining by an Endogenous Agricultural Investment Model

Indica and japonica rice are commonly subjected to different market structures, and the international prices for both subspecies display different trends. The global indica and japonica rice markets in the mid and long term under climate change conditions were projected by the Rice Economy Climate Change (RECC) model. Additionally, endogenous agricultural investments were incorporated into the projections. A COVID-19 pandemic scenario was stimulated to observe its impact on the global indica and japonica rice markets. The results indicated that agricultural investments are expected to decrease in many indica rice-producing countries, whereas the investments will increase in many japonica rice -producing countries in the long term. Therefore, the global indica rice production will decrease due to its investment reduction;however, global japonica rice production will increase in the mid and long term. Due to the COVID-19 scenario, the international indica and japonica rice prices would decrease in 2020 due to the unprecedented shrinking economies worldwide, but the prices would increase from 2021 to 2040 compared with the baseline average of the price projections with the RECC model. The scenario simulation results reveal that the japonica rice markets are projected to have less impact than the indica rice markets from the COVID-19 pandemic.

Dynamic spillover transmission in agricultural commodity markets: What has changed after the COVID-19 threat?

This paper applies the dynamic Diebold-Yilmaz and Baruník-Křehlík spillover indices to document a closer integration between agricultural commodity markets in the period when markets rebounded after the COVID-19 threat to the Russia-Ukraine war. We also identified the record return spillover transmission among agricultural commodities during a time of conflict and the strongest transmitters are wheat, maize and barley. The findings emphasise an increasing uncertainty to the global food market.

Short-Term Speculation Effects on Agricultural Commodity Returns and Volatility in the European Market Prior to and during the Pandemic

Motivated by increased agricultural commodity price volatility and surges during the past decade, we investigated whether financial speculation is to blame. The aim of this paper is to build on prior research about to what extent and in which ways financial speculation undermines agricultural commodity prices. In our analysis, we utilized the daily returns on milling wheat, corn, and soybean futures from the Euronext Commodities Paris market (MATIF) as well as the short-term speculation index. To quantify this impact, we apply Granger noncausality tests as well as the GARCH (generalized autoregressive conditional heteroskedasticity) technique. We also propose a model using seasonal dummy variables to examine whether financial speculation has a greater impact on price volatility during more volatile months. According to our results, financial speculation, as an external factor, in most cases has no effect or reduces the volatility of the underlying futures prices. The opposite is observed in the corn market, where volatility has risen in the post-2020 period and has been pushed up even more by speculation in April. However, since the influence on other commodities is limited or nonexistent, more emphasis should be focused on speculation in the European corn futures market or its interdependence with energy markets.

Price Volatility Dependence Structure Change Among Agricultural Commodity Futures Due to Extreme Event: An Analysis with the Vine Copula

Since the COVID-19 spreads, global food prices have continued to rise and become more volatile because of food security panic, global food supply chain disruption, and unfavorable weather conditions for cultivation. This paper aims to study and compare the dependence structure in price volatility among agricultural commodity futures before and during the COVID-19 pandemic, with different vine copulas, namely the R-vine, C-vine, and D-vine. The daily closing prices of the agricultural commodity futures are used in the investigation, including Corn, Wheat, Oat, Soybean, Rice, Sugar, Coffee, Cocoa, and Orange, traded in the Chicago Board of Trade (CBOT) from January 2016 to July 2021. The conditional volatilities were estimated using the best fit GARCH model with the student-t distribution. The empirical results highlight the dependence structures captured by the C-vine, D-vine, and R-vine copula-based models before and during the COVID-19 pandemic. Although the C-vine copula structures of the two different periods are unchanged, the details of the copula family in such a structure differ. In the case of D-vine and R-vine copulas, the details of the copula families and their vine structures of two different periods are significantly different, meaning that COVID-19 impacts the price volatility dependence structure among the agricultural commodity futures examined. Based on the AIC, the most appropriate dependence structure for pre-COVID-19 period is the C-vine copula, while the during-COVID-19 period is the D-vine copula. The dependence structure of agricultural commodity futures prices can be used in other risk analysis and management methods such as value at risk (VaR), portfolio optimization, and hedging. © 2022, Springer Nature Switzerland AG.

An Investigation of the Dynamic of Cocoa Commodity Competitiveness in Indonesia and Ivory Coast Before and During Covid-19 Pandemic

As a primary agricultural commodity, cocoa is the essential commodity and source of income for farmers, workers, and companies in terms of its supply chain. In Indonesia, cocoa is a commodity number three after coconut palm oil and rubber. Therefore, it plays a crucial role in creating job opportunities, which focusing on agribusiness and domestic agroindustry, environmental conservation, and regional development. In conjunction with the significant contribution of cocoa as an agricultural commodity, this study seeks to investigate the cocoa commodity competitiveness dynamics in Indonesia and Ivory Coast before and during the Covid-19 pandemic. This study calculates the data of export using a four-digit Harmonized System (HS) on the basis of the United Nations' Standard International Trade Classification (SITC) from 2016 to 2020. In determining the country's competitiveness, this study applies the Balassa Revealed Comparative Advantage (BRCA). This study indicates that the competitive dynamics of cocoa commodities occurred in Indonesia and Ivory Coast before and during the Covid-19 pandemic. Thus, the chocolate industry network should promote good governance for improving sustainable agricultural resources, including fair and inclusive labour policy and green supply chains incentives. Also, creating a better policy climate for effective agricultural management and developing a downstream chocolate industry should be crucial for both countries. © IEOM Society International.

Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak.

This paper represents an analysis of the spillover effects and time-frequency connectedness between crude oil prices and agricultural commodity markets using both the spillover index of Diebold and Yilmaz (2012) and the wavelet coherence model to evaluate whether the time-varying return spillover index exhibited the intensity and direction of transmission during the Covid-19 outbreak. Overall, the current results shed light on that in comparison with the pre-Covid-19 period, and the return spillover is more apparent during the Covid-19 crisis. However, levels of the intensity of this relationship vary through the period of research, with several intervals witnessing both negative and positive interactions. Further, our findings indicate significant heterogeneity among agriculture commodity markets in the degree of spillover to crude oil prices over time, amplifying our understanding of the economic channels through which the agriculture commodity markets are correlated. More importantly, there exist significant dependent patterns about the information spillovers across the crude oil and agriculture commodity markets might provide prominent implications for portfolio managers, investors, and government agencies.