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Since 2013, China's futures exchanges have implemented night trading for agricultural futures to reduce the overnight risk and price jump of futures products by extending trading hours. This study uses difference‐in‐differences (DID) to examine the impacts of night trading on daytime price volatility in corn and corn starch futures markets. On the basis of tick‐by‐tick data for these futures, we find that night trading has significantly reduced daytime volatility and contributed to price volatility stability in the corresponding futures market. Moreover, we make DID estimations for separate daytime sessions and find that the reduction of the daytime volatility takes place mainly during the first trading session. Robustness and placebo tests further support our main conclusions. Our results provide valuable guidance for futures exchanges and regulators seeking to formulate night trading policies for futures and options. [ABSTRACT FROM AUTHOR]

Using positions data for 18 commodity futures during 2001–2020, we examine systematic and idiosyncratic determinants of Amihud price impact and microstructure noise proxying for permanent and transitory components of commodity futures liquidity. Idiosyncratic factors have the largest economic impact: while excess hedging demand increases PI and noise, active position‐taking (by market‐makers) in excess of the hedging demand reduces noise. Systematic factors, including the lack of competition among liquidity providers, adversely impact liquidity, but this effect is mitigated if liquidity providers are well‐capitalized. Supplementary leverage ratio (SLR) makes holding inventory costlier and is associated with lower liquidity. [ABSTRACT FROM AUTHOR]

• Rice futures trading ceased at Japan's Osaka Dojima Exchange in 2021. • The Japanese rice market failed to meet the multiple conditions necessary for successful futures trade. • With fragmented spot rice markets, futures trading could not foster price discovery and encourage hedging. • Rice futures trading in Japan provides a cautionary case for policy makers interested in promoting commodity futures trading. Futures markets promise improved price transparency and risk mitigation for staple commodities important to many developing countries, but they can fail even in developed economies with modern financial institutions. We investigate rice futures trading in Japan at the Osaka Dojima Exchange to identify the reasons underlying its failure in 2021. Our analysis reviews the multiple necessary conditions for a successful commodity futures market. We find the Japanese rice market did not meet many of these conditions. The spot market was fragmented with heterogeneous goods and a single dominant firm. Futures trading was unable to facilitate price discovery or effective hedging activity. To the extent it was traded, the Dojima rice futures contract was instead used as a forward contract for making and taking physical delivery. In addition, there was political opposition and regulatory uncertainty around futures trading. Using detailed data on trader positions in the futures market, we show how these factors contributed to diminished interest in futures trading from firms who handle physical commodities. The lessons from the Japanese case are useful for traders, exchanges, and policy makers, especially those in countries where futures markets may face similarly unfavorable economic and political conditions. [ABSTRACT FROM AUTHOR]

Global commodity markets, due to major health crises, political tension, sanctions, growing demand, and other global supply and demand factors, are currently particularly unstable. In addition to the macro-environmental factors that drive the prices, agricultural and other commodity markets are becoming more susceptible to the continuously-growing speculation on major commodity exchanges. Therefore, the purpose of this study is to analyze the influence of financial speculation on agricultural and other commodity prices and return volatility. In our study, we use daily returns on wheat, soybean, corn, and oats futures from the Chicago Mercantile Exchange as well as two additional commodities (crude oil and gold) to compare the extent of this effect. To measure this impact, we, besides traditional tools for time-series analysis, apply the threshold autoregressive conditional heteroskedasticity (TGARCH) technique. We also provide a model using dummy variables for the season to determine whether or not financial speculation's impact on return volatility differs among seasons, as seasonality plays an important role in return dynamics for agriculture. Our study's findings show that financial speculation, except for the oats market, either has no impact or makes the underlying futures returns less volatile. Therefore, we draw the conclusion that either there is no relationship between the rise in short-run speculation and the volatility of agricultural commodity prices, or the link is at best questionable. Research results provide important implications for the sustainable development of commodity markets, as passive legislation measurers can be seen as more effective ones compared to more strict active ones in order to maintain these markets liquid and capable of distributing price risks for agricultural producers and manufacturers in a challenging economic and geopolitical environment. [ABSTRACT FROM AUTHOR]

In this paper, we examine whether the repeated rejection of Masters's price pressure hypothesis is robust with respect to measurement errors in index trader positions data. We allow for autocorrelated errors and a potential impact of index trader positions on both the level and volatility of commodity returns. The resulting state‐space model is estimated via particle Markov chain Monte Carlo (PMCMC). The empirical investigation relies on weekly data for 12 commodities listed in the SCoT and DCoT reports from 2006 to 2020. Our empirical findings show that the rejection of the price pressure hypothesis is robust concerning the inclusion of measurement errors in index trader positions data. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In recent years, commodity markets have become increasingly popular among financial investors. While previous studies document a factor structure, not much is known about how prominent anomalies are priced in commodity futures markets. We examine a large set of such anomaly variables. We identify sizable premia for jump risk, momentum, skewness, and volatility-of-volatility. Other prominent variables, such as downside beta, idiosyncratic volatility, and MAX, are not priced in commodity futures markets. Commodity investors should rebalance their portfolios regularly. Returns for annual holding periods are substantially weaker than for monthly rebalancing. [ABSTRACT FROM AUTHOR]

Global commodity markets, due to major health crises, political tension, sanctions, growing demand, and other global supply and demand factors, are currently particularly unstable. In addition to the macro-environmental factors that drive the prices, agricultural and other commodity markets are becoming more susceptible to the continuously-growing speculation on major commodity exchanges. Therefore, the purpose of this study is to analyze the influence of financial speculation on agricultural and other commodity prices and return volatility. In our study, we use daily returns on wheat, soybean, corn, and oats futures from the Chicago Mercantile Exchange as well as two additional commodities (crude oil and gold) to compare the extent of this effect. To measure this impact, we, besides traditional tools for time-series analysis, apply the threshold autoregressive conditional heteroskedasticity (TGARCH) technique. We also provide a model using dummy variables for the season to determine whether or not financial speculation’s impact on return volatility differs among seasons, as seasonality plays an important role in return dynamics for agriculture. Our study’s findings show that financial speculation, except for the oats market, either has no impact or makes the underlying futures returns less volatile. Therefore, we draw the conclusion that either there is no relationship between the rise in short-run speculation and the volatility of agricultural commodity prices, or the link is at best questionable. Research results provide important implications for the sustainable development of commodity markets, as passive legislation measurers can be seen as more effective ones compared to more strict active ones in order to maintain these markets liquid and capable of distributing price risks for agricultural producers and manufacturers in a challenging economic and geopolitical environment.

The herd behavior which can be defined as ignoring self-opinions and imitating the other investors in investment decision making process can be a fundamental characteristic of financial markets in crisis periods. The main purpose of the study is to examine the possible existence of the herd behavior in the commodity futures markets for the period of 06.01.1998-07.06.2018. In this study, the methodologies of Christie and Huang (1995) and Chang, Cheng, and Khorana (2000), which are based on the cross-sectional variability of commodity futures contracts, and the Hwang and salmon (2004) method which is based on the cross-sectional variability of beta coefficients were implemented. As a result, the evidence obtained from the method of Christie and Huang (1995), which assumed a linear relation between cross-sectional variability and market returns, does not show herd behavior. On the other hand, the evidence obtained from the method of Chang, Cheng and Khorana (2000), who argue a nonlinear relation supports the hypothesis that there is a herd behavior in the commodity futures market and shows that the relationship between cross sectional variability and high and low rates of return is nonlinear. In particular, it is seen that the effects of herd behavior are more pronounced in the bullish periods of in the market. Furthermore, the findings obtained from the methodology based on the variability of the betas also show the presence of the herd behavior in certain periods.

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.

In commodity futures markets, contracts with various delivery dates trade simultaneously. Applied researchers typically discard the majority of the data and form a single time series by choosing only one price observation per day. This strategy precludes a full understanding of these markets and can induce complicated nonlinear dynamics in the data. In this paper, I introduce the partially overlapping time series (POTS) model to model jointly all traded contracts. The POTS model incorporates time-to-delivery, storability, seasonality, and GARCH effects. I apply the POTS model to corn futures at the Chicago Board of Trade and the results uncover substantial inefficiency associated with delivery on corn futures. The results also support two theories of commodity pricing: the theory of storage and the Samuelson effect.

The value of USDA reports in commodity futures markets has been intensively researched, but statistical hypothesis tests have been limited by the sheer number of reports and the consequent need to limit parameters to be estimated. This has led most tests of USDA report announcement effects to be based on single coefficients for each report series. We relax the implicit assumption that a report series has a constant impact on futures price volatility or returns in two ways in order to introduce more flexible tests for announcement effects. First, we introduce a time trend into the impact of announcements on futures price volatility to determine if USDA reports are becoming more or less influential over time. Then we allow each report to have a different impact on futures price returns using Theil-Goldberger mixed estimation. The results show that many, but not all, USDA reports have significant effects on corn and soybean futures market returns or volatility. [ABSTRACT FROM AUTHOR]

We look at the dynamic conditional correlations (DCCs) between oil, natural gas and other non-energy commodity futures markets, obtained from a DCC-GARCH model over the period 1998-2014. They are positive and display a sharp increase around year 2008 and a subsequent decrease. The DCCs between energy and metals are larger than the energy-agriculture ones. To understand how macroeconomic and financial factors, as well as speculative activity, influence them, we estimate an ARDL(1,1) model, adopting a pooled mean group (PMG) estimator. We observe that macroeconomic and financial variables are significantly correlated with the energy-agriculture and energy-metals DCCs. Speculative activity contributes to explain the energy-agriculture DCCs but not those of the energy-metals. [ABSTRACT FROM AUTHOR]

Commodity markets are a widely researched topic in the field of finance. In this paper, we investigate the co-movement of return and volatility measures in different commodity futures markets and how these measures are affected by liquidity risk. First, we find that commodity returns display co-movement and that liquidity risk plays a key role in shaping asset return patterns. Moreover, we show that the volatilities of commodity returns co-move, and we demonstrate the role of liquidity risk in this joint pattern. We also find that the commodity markets we investigated share a common volatility factor that determines their joint volatility co-movement. Because liquidity risk affects both commodity returns and volatility shocks, it might be interpreted as the common causal factor driving both measures simultaneously. Therefore, we affirm the view that liquidity shocks are firmly related to two residual risks originating from both market return and market volatility. Finally, we also show that liquidity spillovers can significantly drive cross-sectional correlation dynamics. [ABSTRACT FROM AUTHOR]

It is widely debated whether financial speculation was a significant force behind recent food price fluctuations. As a matter of fact, during the 2000s agricultural commodity derivatives markets were flooded by a ‘wall of money’ coming from financial investors. In agricultural exchanges, the greatest part of this huge financial inflow came from index traders, i.e. financial actors that follow a passive strategy of tracking a commodity index. In this article I present new empirical evidence that supports the hypothesis that financial investments have affected wheat price dynamics in recent years. In particular, I focus on Hard Red Winter (HRW) wheat. Since 2007 HRW wheat price fluctuations have been positively related to US stock market returns and oil price movements. These correlations appear to be determined by commodity index traders, since both these relationships proved to be spurious, with the most tracked commodity index as the confounding variable.

The convenience yield is a major notion in commodity markets but this variable is unobservable. Consequently, two methods are generally used to test stylized facts regarding commodity convenience yields: the first method relies on a convenience yield filtered from derivative prices while the second one directly uses an observable proxy, the interest-adjusted basis. We believe that our study is the first to theoretically prove that these two methods do not provide the same results. We confirm this finding by analyzing the copper and oil markets. [ABSTRACT FROM AUTHOR]

This paper revisits the “adequacy of speculation” debate in agricultural futures markets using the positions held by index funds in the Commitment of Traders reports. Index fund positions were a relatively stable percentage of total open interest from 2006–2008. Traditional speculative measures do not show any material shifts over the sample period. Even after adjusting speculative indices for commodity index fund positions, values are within the historical ranges reported in prior research. One implication is that long-only index funds may be beneficial in markets traditionally dominated by short hedging. [ABSTRACT FROM PUBLISHER]

Recent accusations against speculators in general and long-only commodity index funds in particular include: increasing market volatility, distorting historical price relationships, and fueling a rapid increase and decrease in the level of commodity prices. Some researchers have argued that these market participants—through their impact on market prices—may have inadvertently prevented the efficient distribution of food aid to deserving groups. Certainly, this result—if substantiated—would counter the classical argument that speculators make prices more efficient and thus improve the economic efficiency of the food marketing system. Given the very important policy implications, it is crucial to develop a more thorough understanding of long-only index funds and their potential market impact. Here, we review the criticisms (and rebuttals) levied against (and for) commodity index funds in recent U.S. Congressional testimonies. Then, additional empirical evidence is added regarding cross-sectional market returns and the relative levels of long-only index fund participation in 12 commodity futures markets. The empirical results provide scant evidence that long-only index funds impact returns across commodity futures markets. [ABSTRACT FROM AUTHOR]

We present the results of two efficiency measures that include intraday return predictability measure based on order imbalance and measures of several variance ratio tests on intraday subsamples of nine major Indian agricultural commodity futures (castor seed, cotton oil cake, rape mustard seed, soybean, refined soya oil, crude palm oil, jeera, chana, and turmeric) quoted in the National Commodity and Derivatives Exchange (NCDEX). We perform the efficiency measures on five subsamples with holding periods of 5, 10, 15, 30, and 60 min over two sample periods following the announcement of the merger between the Forward Market Commission (FMC) and Securities Exchange Board of India (SEBI). We compare results of tests of weak-form market efficiency of futures markets between two periods (pre-merger period and post-merger period). Our results confirm that Indian agricultural commodity futures markets continue to remain inefficient in the short-term during both pre-merger and post-merger periods. Based on these findings, it is likely that profitable trading strategies in the short intraday intervals will be available for traders and market participants during post-merger period. Thus, regulators must focus more on policy initiative so as to enhance market quality in order to address such inefficiencies in Indian commodity futures markets. [ABSTRACT FROM AUTHOR]