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Firms can choose from an array of approaches for reducing the detrimental financial effects caused by unfavorable fluctuations in commodity prices. The purpose of this paper is to provide guidance for effectively estimating the financial effects of mitigating commodity price risk volatility (CPV) in supply chain management decisions.

This paper adopts two prominent and complementary methodologies, namely, total cost of ownership (TCO and real options valuation (ROV), to illustrate how commodity price risk mitigation strategies can be analyzed with respect to their effect on costs and performance. The paper provides insights through a case study to demonstrate the application of these methods together and establish the benefits and challenges associated with their implementation.

The paper illustrates advantages and disadvantages of TCO and ROV and how these approaches can be adopted together to contribute to effective purchasing decisions. Supply chain flexibility is a key capability but requires investments. Holistically measuring the financial effects of flexibility investments is imperative for gaining executive management support in mitigating commodity price volatility.

This study can provide supply chain professionals with useful guidance for measuring the costs and benefits related to developing strategies for mitigating commodity price volatility. TCO provides a focus on the costs associated with the commodity purchasing process, and ROV enables the aggregation of all the costs and benefits associated with the use of the strategy and synthesizes them into the net value estimate.

The paper provides a comparison of different but complementary approaches, specifically TCO and ROV, for analyzing the effectiveness of CPV risk mitigation decisions. In addition, these two methods allow supply chain professionals to evaluate and control the financial effects of CPV risk, particularly the impact of mitigation on firm’s cash flows.

The authors explore the hypothesis that some movements in commodity prices are anticipated (news shocks) and can trigger aggregate fluctuations in small open emerging economies. This paper aims to discuss the aforementioned objective.

The authors build a multi-sector dynamic stochastic general equilibrium model with endogenous commodity production. There are five exogenous processes: a country-specific interest rate shock that responds to commodity price fluctuations, a productivity (TFP) shock for each sector and a commodity price shock. Both TFP and commodity price shocks are composed of unanticipated and anticipated components.

The authors show that news shocks to commodity prices lead to higher output, investment and consumption, and a countercyclical movement in the trade-balance-to-output ratio. The authors also show that commodity price news shocks explain about 24% of output aggregate fluctuations in the small open economy.

Given the importance of both anticipated and unanticipated commodity price shocks, policymakers should pay attention to developments in commodity markets when designing policies to attenuate the business cycles. Future research should investigate the design of optimal fiscal and monetary policies in SOE subject to news shocks in commodity prices.

This paper contributes to the knowledge of the sources of fluctuations in emerging economies highlighting the importance of a new source: news shocks in commodity prices.

Transparent and fair price discovery is essential to commodity market participants in the trade value chain for competitive benefit. The purpose of this paper is to investigate the price discovery of Indian cardamom at e-auction, spot and futures markets in addition to the existence of the day of the week effect at e-auction apart from exploring a novel price risk management framework.

This study used Johansen co-integration, vector error correction model, Granger causality and regression with dummy variables to understand a day of the week effect in high-value agri-commodity of cardamom e-auction prices. These price data were based on authenticated sources of Spices Board India and Multi Commodity Exchange of India Ltd.

The statistical results indicate price discovery exists in the e-auction market and it leads to spot and futures prices. cardamom e-auction prices are negatively related to cardamom futures and positively related to spot prices. It also finds the non-existence of the day of the week effect in the high-value cardamom e-auction system in India. The study revealed that a cardamom e-auction is more active in price discovery than a cardamom futures contract.

These results shall facilitate policymakers to explore intervention of online forward market mechanism at the national level to ensure price discovery and market efficiency. However, the study did not explore reasons for the non-equilibrium of a cardamom futures contract with spot and e-auction market.

The results of this study are useful in understanding the price discovery of cardamom e-auction and its role in the spot and futures market. Cardamom price discovery depends upon the e-auction system; any change of auction policy shall be binding on Indian cardamom prices. The introduction of an online forward market mechanism as described in the paper shall facilitate price risk management apart from improving the efficiency of price discovery.

This is the first study considering cardamom e-auction, spot and futures prices in the price discovery process in India. Statistical results of a day of the week effect clearly show no significant volatility of cardamom prices during the week. Besides, this study did not find the role of cardamom futures contracts intended to serve the economic function of price discovery and price risk management. Hence, suggests policy intervention for implementing an online Forward Market mechanism for Indian cardamom to ensure market efficiency and manage price risk.

This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

Professionals from the dairy sector commonly believe that the results of Global Dairy Trade (GDT) auctions are a good leading indicator for prices of dairy commodities. The purpose of this paper is to test that hypothesis for prices of key dairy commodities (skimmed milk powder (SMP), whole milk powder (WMP), butter and cheddar) in the main dairy markets (the US, EU and Oceania).

The leading properties of the GDT auctions are investigated using vector error correction models (VECM).

The results show that prices at GDT auctions may be treated as a benchmark for global prices of WMP and SMP as they affect prices in all considered markets. However, in case of EU market the relationship with the GDT is bidirectional. GDT prices reveal some leading properties also in cheddar market, however price relationships in this market are much more complex. In case of butter market, GDT can be regarded as a benchmark only for Oceania.

The results of this paper improve knowledge on price transmission in dairy markets, show the role of the GDT auctions in the price setting process, and thus may help professionals from the dairy sector to formulate their price expectations more precisely.

Despite the fact that many professionals from the dairy sector treat GDT auctions as a benchmark, so far their leading properties have not been scientifically proven.

Marx’s monetary theory is an important part of Marxist economics and an irreplaceable milestone in the intellectual history of the monetary theory. The purpose of this paper is to summarize the main content of Marx’s monetary theory from three aspects: the source and nature of money, the function of money and the historical significance of money.

Moreover, this paper also gives an extended understanding of Marx’s monetary theory from four perspectives: the endogenous credit mechanism of money, the functions of money and demands for money, the financial function of money and the economic and social functions of money.

Lastly, the present paper discusses the practical significance of Marx’s monetary theory from three perspectives, namely, the inspection of “Bitcoin” from the nature and function of money, the definition of demands and the division of supplies at the monetary level, and the prevention of systemic financial risks and the focus of financial supervision.

Marx’s monetary theory is an important part of Marxist economics and an irreplaceable milestone in the intellectual history of the monetary theory. However, for a long time, the contribution of Marx has rarely been mentioned in the intellectual history of monetary theory. Even the book, Political Economy (On Capitalism), has been only summarily concerned with the source and function of money in Marx’s monetary theory, rather than revealing Marx’s outstanding contribution in the monetary theory and the financial connotation of Marx’s monetary theory, and expounding its practical significance.

This paper aims to estimate the impact of the 2000s commodity boom in the major Latin American economies.

The author used a structural vector autorregresive analysis where the selection of variables is conditional on a New Keynesian Model for a small open economy.

The evidence indicates that the Argentinean nominal exchange rate appreciated less while its output and inflation grew more than those of the other nations when subjected to commodity shocks. These results are interpreted as a more aggressive leaning-against-the-wind intervention by Argentina, probably to avoid the Dutch disease. Although the effects with regard to output were indeed stronger in Argentina, this was only at the expense of higher inflation and volatility suffered during the boom.

At the time of the writing of this paper, no work had evaluated Argentinean underperformace to the manner in which its exchange rate policy was handled in comparison with the rest of the region during the boom. This paper intends to fill this gap.

The purpose of this paper is to examine the pricing efficiency of the Malaysian crude palm oil (CPO) market before and after the structural break. This study uses the daily closing price of CPO and CPO futures (CPO-F) for the period ranging from June 2009 to August 2016 while taking structural breaks into account.

In this study, symmetric and asymmetric long-run relationship model are employed, such as the Johansen cointegration, VECM, TAR and M-TAR models, to examine the impact of structural breaks on the pricing efficiency of the Malaysian CPO market.

This finding establish that Malaysian CPO price is efficient before and after the structural break. The consistent efficiency of the Malaysian CPO market supports the trading of the CPO-F in Globex and the use of Malaysian CPO pricing as the reference price. This study establishes that a structural break in the Malaysian CPO price series does not affect the pricing efficiency of the market.

This study shows that using Malaysian CPO price as a reference price is sustainable even in the event of a structural break. Therefore, market participants in the Malaysian CPO market have less to worry about the CPO price as it supports the weak form of efficiency. Price deviation in the short run may not lead to arbitrage profit as transaction cost may not be covered.

This study implies that if there is distortion in the price due to shocks, both manufacturers and producers need to hedge their positions in the futures market (subject to their positions in the underlying market). By entering into the futures market, pricing is locked in advance; hence, price risk is eliminated. Such a distortion could also affect the efficiency of the CPO price, therefore this study also addresses the issue of efficiency of the local CPO market.

Previous studies on Malaysian CPO pricing efficiency did not take the effect of structural break into consideration, making it difficult for these studies to show consistency in the efficiency of the Malaysian CPO market.

The division of labor of e-commerce transaction system is an important research topic. However, there is a certain disparity between the current mainstream research model and the reality, which leads to a biased result. This paper aims to find the effects of transaction efficiency on the evolution of e-commerce transaction system’s division of labor and the relationships between the results and other parameters.

This paper puts forward a definition of transaction efficiency based on transaction services and establishes a model of middleman’s specialized production decision of transaction services on this basis.

The research results show that the transaction efficiency plays an important role on the change of middlemen’s division of labor level. The degree of economic specialization, price of commodities and transaction services and other associated factors also affect middlemen’s division of labor.

This paper is of great significance for evaluating the development level and forecast the development direction of e-commerce.

Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.