Showing papers on "Commodity market published in 2020"

Global Economic Prospects : June 2020

Abstract: The COVID-19 pandemic has, with alarming speed, dealt a heavy blow to an already-weak global economy, which is expected to slide into its deepest recession since the second world war, despite unprecedented policy support. The global recession would be deeper if countries take longer to bring the pandemic under control, if financial stress triggers defaults, or if there are protracted effects on households and firms. Economic disruptions are likely to be more severe and protracted in emerging market and developing economies with larger domestic outbreaks and weaker medical care systems; greater exposure to international spillovers through trade, tourism, and commodity and financial markets; weaker macroeconomic frameworks; and more pervasive informality and poverty. Beyond the current steep economic contraction, the pandemic is likely to leave lasting scars on the global economy by undermining consumer and investor confidence, human capital, and global value chains. Being mostly a reflection of the recent plunge in global energy demand, low oil prices are unlikely to provide much of a boost to global growth in the near term. While policymakers’ immediate priorities are to address the health crisis and moderate the short-term economic losses, the likely long-term consequences of the pandemic highlight the need to forcefully undertake comprehensive reform programs to improve the fundamental drivers of economic growth, once the crisis abates.

Does economic policy uncertainty matter for commodity market in China? Evidence from quantile regression

Abstract: This paper investigates the effect of economic policy uncertainty (EPU) on China’s agricultural and metal commodity futures returns across quantiles. We address this issue using the panel quantile ...

Modeling and Forecasting Commodity Market Volatility with Long-Term Economic and Financial Variables

Abstract: This paper investigates the time-varying volatility patterns of some major commodities as well as the potential factors that drive their long-term volatility component. For this purpose, we make use of a recently proposed GARCH-MIDAS approach which typically allows us to examine the role of economic and financial variables of different frequencies. Using commodity futures for crude oil (WTI and Brent), gold, silver and platinum, our results show the necessity of disentangling the short- and long-term components in modeling and forecasting commodity volatility. They also indicate that the long-term volatility of most commodity futures is significantly driven by the level of the general real economic activity as well as the changes in consumer sentiment, industrial production, and economic policy uncertainty. However, the forecasting results are not alike across commodity futures as no single model fits all commodities.

Information-rich wheat markets in the early days of COVID-19

Abstract: This paper uses the information implicit in commodity futures and options prices to infer market beliefs about the impact of early-stages COVID-19 on commodity market fundamentals. The particular commodity examined is soft red winter (SRW) wheat, and the timeframe is early February to late March 2020. The analysis highlights various adjustments in the cash and futures price of SRW wheat in light of surging short-run demand from consumer hoarding of staple food products, and a weakening long-run market from growing wheat stocks and an emerging global recession. This split is causing the forward curve to flatten and basis levels to invert. The change over time in the price of options on wheat futures reveals increased price volatility in response to growing uncertainty about the COVID-19 impacts. Similarly, changes in the skewness of the option's volatility smile illustrate a shift in traders’ perception about risk in the right versus left tail of the price distribution.

Merchants against the bankers: the financialization of a commodity market

Abstract: Global commodity and capital markets have undergone dramatic structural changes associated with financialization. But, in spite of this, the literature on financialization neglects questions about ...

Impact of News on the Commodity Market: Dataset and Results

Abstract: Over the last few years, machine learning based methods have been applied to extract information from news flow in the financial domain. However, this information has mostly been in the form of the financial sentiments contained in the news headlines, primarily for the stock prices. In our current work, we propose that various other dimensions of information can be extracted from news headlines, which will be of interest to investors, policy-makers and other practitioners. We propose a framework that extracts information such as past movements and expected directionality in prices, asset comparison and other general information that the news is referring to. We apply this framework to the commodity "Gold" and train the machine learning models using a dataset of 11,412 human-annotated news headlines (released with this study), collected from the period 2000-2019. We experiment to validate the causal effect of news flow on gold prices and observe that the information produced from our framework significantly impacts the future gold price.

Financialization and Commodity Market Serial Dependence

Abstract: Recent financialization in commodity markets makes it easier for institutional investors to trade a portfolio of commodities via various commodity-indexed products. We present novel causal evidence that exposure to such index trading results in negative daily return autocorrelations among commodities in that index. This is because index trading propagates nonfundamental noises to indexed commodities, giving rise to price overshoots and subsequent reversals, consistent with the prediction of a stylized model. We present direct evidence for such noise propagation using commodity news sentiment data.

Time-Varying Conditional Profitability of Momentum Strategies in Commodity Futures Market: Evidence from India

Abstract: Manuscript type: Research paper Research aim: This study aims to provide fresh evidence on the presence of momentum profitability in the Indian commodity futures market. Design/Methodology/Approach: This study is based on a sample of highly traded commodity future contracts of the Indian commodity market over the period from 2006 to 2017. It applies the conditional multi-factor model to test the time-varying performance of momentum strategies. Research findings: This study confirms the existence of exceptionally high abnormal momentum profitability in the commodity futures market despite the presence of transaction costs. However, the application of conditional multi-factor model suggests that momentum profits are basically time-varying. The low and insignificant correlation of momentum portfolios with stocks and bonds confirm that relative strength momentum portfolios of commodity futures can be effectively used to create a well-diversified portfolio. Theoretical contribution/Originality: This study analyses the time-varying conditional profitability of momentum strategies for the commodity market of emerging economies such as India. It enriches the small group of studies conducted on commodity futures in the Indian context. The major contribution of the study is the use of conditional multi-factor model to assess the possible role of time-varying conditional alpha and beta to define the momentum payoffs in commodity futures market for the Indian context. Policy implications: Policymakers should design more lucrative policies so as to attract the institutional investors for investment in the Indian commodity market. This is because domestic and foreign institutional investors are central to the enhancement and stability of the financial market. Research implications/Limitations: The study uses the 13 highly traded commodity futures contract to design the momentum strategies. The robustness of the high abnormal returns given by these strategies can be investigated further by the use of extended study period and expanded cross section of commodity futures contract.

The Third Dimension of Financialization: Intraday Institutional Financial Traders and Commodity Market Quality

Abstract: We provide the first detailed empirical evidence on the financialization of intraday trading activity in the world’s largest commodity market and show that this development had a first-order positive impact on market liquidity and pricing efficiency. We use a rich regulatory dataset to show that the electronification of U.S. crude oil futures trading in 2006 brought about a massive growth in intraday activity by “non-commercial” institutional financial traders. We exploit differences in the post-electronification growth rates of institutional financial trading in crude oil futures contracts of different maturities to tease out the effect of financialization on key metrics of commodity market quality. We show that increased institutional financial trading reduces the variance of pricing errors, narrows bid-ask spreads, and improves market depth. Our inferences are robust to differences in the nature and volume of non-financial trading. Finally, we provide novel evidence of notable differences between the respective contributions of high-frequency traders (HFTs) vs. other (non-HFT) institutional financial traders to different market quality attributes.

Institutional Arrangement for Food Price Stabilization and Market Distribution System: Study of Chili Commodity in Banyuwangi Regency

Abstract: The fluctuating development of chili prices implies that the maintained supply of chili is very important to maintaining the stability of food prices. The value chain integration of the chili commodity from upstream to downstream supported by the availability of adequate infrastructure and institutions is the main prerequisite in increasing the productivity of chili commodities. The purpose of this study is (1) to give a description of the chili commodity marketing chain in Banyuwangi Regency; (2) analyze the determinants of structure, conduct, and performance of the chili commodity market in Banyuwangi Regency. The analytical method used consists of the Autoregressive Integrative Moving Average (ARIMA) and Structure Conduct Performance (SCP) models.The results of the study show that price determination was based on market mechanisms and collective agreements for farmers who partner with collectors and food processing industries. However, the lack of price and knowledge information in market analysis and projections of price movements and the absence of special institutions that deal with chili governance and limited use of technology have led to the emergence of asymmetrical information from chili businesses and the growth of new players in the trade system that dominates the chili trade. The chili market structure tends to oligopsony, which has the power to influence market prices and is concentrated, causing little competition between chili traders in Banyuwangi Regency.

Designing call auction institutions to eliminate price bubbles: Is English Dutch the best?

Abstract: The bubble-and-burst pattern in asset markets is among the most replicable results in experimental economics. Using controlled laboratory experiments, we compare mispricing in markets organized by standard double auction rules with mispricing in markets organized by two alternative sets of clock auctions. The double Dutch auction, shown to be more efficient than the double auction in past commodity market experiments, does not eliminate bubbles. However, the English Dutch auction yields prices reflective of underlying fundamentals and succeeds in taming bubbles even with inexperienced traders in a declining fundamental value environment with an increasing cash-to-asset ratio.

Towards Trust Enabled Commodity Market for Farmers with Blockchain Smart Contracts

Abstract: This paper presents a conceptual model for an online agricultural commodity market that empowers farmers with a better price determination mechanism through collective marketing and Blockchain smart contracts. The model makes collective marketing possible by generating Many-one-Many relationships between farmers, farmers' groups, and buyers. While collective marketing improves farmers' bargaining position leading to higher rates, trust enabled by Blockchain smart contracts facilitates farmers to establish deals with buyers who offer the best rate transforming the commodity market into a sustainable market.

Beet production efficiency and ways to increase it in case of negative market conditions in the commodity market

Abstract: The relevance of the topic of the article is related to the need to develop agricultural markets at the regional level in order to increase the export potential of agricultural products. The purpose of the article is to find out the reasons for the decrease in the market price for sugar beet processed products, in particular white sugar, as well as to develop recommendations for optimizing the production and sale of sugar beet. The novelty of the study is to identify trends in the development of the market for raw materials for sugar production from sugar beets at the regional level and justification of the necessary priority measures to increase economic efficiency in the beet industry. The article presents the results of an analysis of the level of development of the commodity market for sugar producers. Priority directions for increasing production volumes and increasing the efficiency of sugar beet production as the main raw material for the production of white sugar and granulated sugar have been identified; recommendations have been given on ensuring sustainable growth in income from the sale of sugar beet root crops. The practical significance of the research results lies in the possibility of their use in the development of programs for the development of regional food markets, organizational, economic, technological measures to improve the efficiency of beet production in individual municipal areas to achieve high target indicators.

Did index trader and swap dealer activity produce a bubble in the agricultural commodity market

Abstract: This paper investigates the role of speculative activity in the agricultural commodity futures market in the period 2006-2017. Specifically, the study tests the causal relationship between the prices of fourteen agricultural commodities listed on the US commodity market Chicago Mercantile Exchange (CME) and Chicago Board of Trade (CBT) and the trading activity of commodity index traders (CITs) and swap dealers. The analysis uses the Granger Causality test based on a seemingly unrelated regression (SUR) system. The results show that CIT and swap dealer positions did not significantly influence prices of agricultural commodities, but might explain the increase in their price volatility. The findings disprove Masters’ hypothesis that speculators produced a bubble in the commodity market. In this context, any attempt (such as taxes) by lawmakers to limit speculation should be carefully evaluated. Key words: Commodity index traders, swap dealers, agricultural futures market, Masters’ hypothesis, Granger causality.

Revenue forecasting in the mining industries: A data-driven approach

Abstract: Robust forecasting of mining sector revenues is key to effective budgeting (and broader fiscal management) in many resource-rich countries. However, this is challenging in practice, given commodity market volatility, the extended lags (and often opaque processes) between resource discoveries and fiscal yields, and the heterogeneity of taxable entities within the sector. Such issues are exacerbated by capacity deficits: quantitative sector assessment frameworks are seldom employed or maintained by revenue authorities.

Assessing the Impact of COVID-19 on Interactions among Stock, Gold and Oil Prices in India

Abstract: In the last two decades the connection between the equity market and commodity markets has increased. Exploring the nature of this linkage in the context of emerging economies, however, is limited. This paper studies the relationship between the stock prices and the prices of two mostly traded commodities in the derivatives market, viz. crude oil and gold in the Indian context. Based on the data in the recent past, the paper employs ARDL model to estimate the long run relationship. It also finds out the impact of a disruption like COVID-19 pandemic on this relationship in the Indian financial markets. The findings point to the fact that the stock returns and the commodity prices are closely linked with each other. Interestingly, the pandemic has altered the relationship. In the pre-COVID period, there was no cointegration among the stock, gold and crude oil prices, but during the pandemic, there is evidence of cointegration and the short run relationship provides interesting insights. In the pre-pandemic period, evidence point to a mutual impact on the two markets, e.g. past values of oil price and gold price influence the stock returns while returns on the stock market influences oil price volatility. However, during the COVID period, apart from crude oil prices, it is the volatility of gold prices, that has emerged as the driver of the stock returns.