Assessing the functional efficiency of agricultural futures markets in China

2019 ◽  
Vol 11 (2) ◽  
pp. 431-442
Author(s):  
Ju Ronghua ◽  
Yang Zhiling
Keyword(s):  
Futures Markets ◽  
Futures Market ◽  
Market Liquidity ◽  
Content Type ◽  
Data Services ◽  
Futures Contract ◽  
Functional Efficiency ◽  
The Social ◽  
Agricultural Futures ◽  
Loss Index

Purpose The purpose of this paper is to quantitatively analyse the changes in the functional efficiency of the six Chinese agricultural futures markets and compare the relative behaviour of different futures markets. In addition, this paper analyses the causes of differences in the functional efficiency of agricultural futures markets and advances policy suggestions. Design/methodology/approach The method used in this paper is the social loss index proposed by Stein (1981, 1986). This method can quantitatively measure the functional efficiency of agricultural futures markets from the perspective of social welfare. The indicator is calculated for the 2009–2017 period and for several sub-periods. The data are from the CSMAR research data services in China. Findings Preliminary results suggest that the longer it takes for an agricultural futures contract to reach maturity, the lower the functional efficiency of its market. Second, the functional efficiency of the agricultural futures markets in China is improved except for that of the wheat futures market. Finally, the corn futures market is most efficient probably due to the progress of marketization, while the strong wheat futures market is most inefficient probably due to the decrease in futures market liquidity. Originality/value This paper uses a more reasonable method to study the functional efficiency of Chinese agricultural futures markets and then analyses the causes of differences in the functional efficiency of agricultural futures markets.

Liquidity of China’s agricultural futures market: measurement and cross-market dependence

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yuanyuan Xu ◽  
Jian Li ◽  
Linjie Wang ◽  
Chongguang Li
Keyword(s):  
Futures Markets ◽  
Low Frequency ◽  
Futures Market ◽  
Market Liquidity ◽  
Contagion Effect ◽  
Short Term ◽  
Seminal Paper ◽  
Content Type ◽  
Agricultural Futures

PurposeThis paper aims to present the first empirical liquidity measurement of China’s agricultural futures markets and study time-varying liquidity dependence across markets.Design/methodology/approachBased on both high- and low-frequency trading data of soybean and corn, this paper evaluates short-term liquidity adjustment in Chinese agricultural futures market measured by liquidity benchmark and long-term liquidity development measured by liquidity proxies.FindingsBy constructing comparisons, the authors identify the seminal paper of Fong, Holden and Trzcinka (2017) as the best low-frequency liquidity proxy in China’s agricultural futures market and capture similar historical patterns of the liquidity in soybean and corn markets. The authors further employ Copula-generalized autoregressive conditional heteroskedasticity models to investigate liquidity dependence between soybean and corn futures markets. Results show that cross-market liquidity dependence tends to be dynamic and asymmetric (in upper versus lower tails). The liquidity dependence becomes stronger when these markets experience negative shocks than positive shocks, indicating a concern on the contagion effect of liquidity risk under negative financial situations.Originality/valueThe findings of this study provide useful information on the dynamic evolution of liquidity pattern and cross-market dependence of fastest-growing agricultural futures in the largest emerging economy.

scholarly journals Study of efficiency and information transmission for agricultural futures markets: a comparative analysis between Buenos Aires and Chicago using monthly and daily data

2017 ◽  
Vol 34 (69) ◽  
pp. 3-23
Author(s):  
Jeremías Lachman ◽  
Pablo Jack
Keyword(s):  
Comparative Analysis ◽  
Information Transmission ◽  
Market Efficiency ◽  
Futures Markets ◽  
Buenos Aires ◽  
Relevant Information ◽  
Futures Market ◽  
Daily Data ◽  
Agricultural Futures ◽  
The One

This paper aims to study and compare the efficiency in futures markets for soybean crop between Buenos Aires (MATBA) and Chicago (CME–CBOT) for the years 1994 through 2015. There are numerous studies that analyze this phenomenon independently, but few of them have done a comparative analysis between marke- ts. Therefore, the main objective of this research — in addition to individually analyzing the efficiency in futures market in each country — is to be able to detect the existence of a relationship between the two markets. In this article we show that, in addition for market efficiency in all cases, market efficiency in MatBa was derived from the efficiency in CME–CBOT. This means that relevant information is transmitted from the Chicago market to the one in Buenos Aires. By using a cointegration approach based on Johansen (1995) we estimated the models with monthly and daily data.

Assessing the relationship between closing prices and trading volume in the US livestock futures markets

2020 ◽  
Vol 37 (3) ◽  
pp. 413-428
Author(s):  
Dimitrios Panagiotou ◽  
Alkistis Tseriki
Keyword(s):  
Trading Volume ◽  
Futures Markets ◽  
Quantile Regressions ◽  
Content Type ◽  
Feeder Cattle ◽  
Daily Data ◽  
The Us ◽  
Volume Relationship ◽  
Agricultural Futures ◽  
The Relationship

Purpose The purpose of this paper is to examine the relationship between closing prices and trading volume in the livestock futures markets of lean hogs, live cattle and feeder cattle. Design/methodology/approach The parametric quantile regressions methodology is used. Daily data between January 1, 2010 and July 31, 2019 were used. Findings Findings suggest that the relationship between the two variables is non-linear. Price-volume relationship is positive (negative) under positive (negative) returns. Furthermore, co-movement is weaker at the lower quantiles and stronger at the higher quantiles. Results are in line with the empirical findings of the price-volume relationship in six agricultural futures markets from the study by Fousekis and Tzaferi (2019). Originality/value This is the first study that uses the parametric quantile regressions method in the livestock futures market, to examine the returns-volume dependence.

Volatility persistence and trading volume in an emerging futures market

2010 ◽  
Vol 11 (3) ◽  
pp. 296-309 ◽  
Author(s):  
Pratap Chandra Pati ◽  
Prabina Rajib
Keyword(s):  
Capital Market ◽  
Trading Volume ◽  
Price Volatility ◽  
Futures Market ◽  
Market Volatility ◽  
Leverage Effect ◽  
Time Varying ◽  
Conditional Volatility ◽  
Content Type ◽  
Futures Contract

PurposeThe purpose of this paper is to estimate time‐varying conditional volatility, and examine the extent to which trading volume, as a proxy for information arrival, explain the persistence of futures market volatility using National Stock Exchange S&P CRISIL NSE Index Nifty index futures.Design/methodology/approachTo estimate the volatility and capture the stylized facts of fat‐tail distribution, volatility clustering, leverage effect, and mean‐reversion in futures returns, appropriate ARMA‐generalized autoregressive conditional heteroscedastic (GARCH) and ARMA‐EGARCH models with generalized error distribution have been used. The ARMA‐EGARCH model is augmented by including contemporaneous and lagged trading volume to determine their contribution to time‐varying conditional volatility.FindingsThe paper finds evidence of leverage effect, which indicates that negative shocks increase the futures market volatility more than positive shocks of the same magnitude. In addition, the results indicate that inclusion of both contemporaneous and lagged trading volume in the GARCH model reduces the persistence in volatility, but contemporaneous volume provides a greater reduction than lagged volume. Nevertheless, the GARCH effect does not completely vanish.Practical implicationsResearch findings have important implications for the traders, regulatory bodies, and practitioners. A positive volume‐price volatility relationship implies that a new futures contract will be successful only to the extent that there is enough price uncertainty associated with the underlying asset. Higher trading volume causes higher volatility; so, it suggests the need for greater regulatory restrictions.Originality/valueEquity derivatives are relatively new phenomena in Indian capital market. This paper extends and updates the existing empirical research on the relationship between futures price volatility and volume in the emerging Indian capital market using improved methodology and recent data set.

The impact of embedded location options on price discovery of agricultural futures contracts – the evidence from the Chana contract

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanjay Mansabdar ◽  
Hussain C. Yaganti ◽  
Sankarshan Basu
Keyword(s):  
Price Discovery ◽  
Time Series Data ◽  
Futures Contracts ◽  
Series Data ◽  
Futures Prices ◽  
Content Type ◽  
Futures Contract ◽  
Agricultural Futures ◽  
Embedded Options ◽  
The Impact

Purpose Embedded options can create asymmetries in information impounded by cash and futures markets, causing errors in price discovery estimation. This paper aims to investigate the impact of embedded location options on measures of price discovery. Design/methodology/approach Various price discovery metrics are computed using observed futures prices that contain embedded location options and cash prices for Chana. Prices of a futures contract that contains no options using observed futures prices and estimates of location option value are synthesized. The price discovery measures are recomputed using synthetic option-adjusted futures contract prices and cash prices, and changes in these measures are attributed to the impact of the embedded location option. Findings If the presence of the location option is ignored, futures appear to dominate price discovery. Once the location option is adjusted for, cash markets are found to dominate price discovery. Research limitations/implications The lack of complete time-series data from the exchange for multiple commodities allows only limited empirical evidence for generalizing conclusions. Practical implications This paper highlights that regulators, exchanges and policymakers in India need to revisit delivery specifications of agricultural commodity futures contracts to enhance their utility from a price discovery perspective. Originality/value This work shows that ignoring the presence of embedded options can cause significant errors in price discovery assessment of agricultural futures contracts, particularly in heterogenous cash markets.

Short-term contrarian and sentiment by traders’ types on futures markets

2018 ◽  
Vol 10 (4) ◽  
pp. 298-319 ◽  
Author(s):  
Walid Bahloul
Keyword(s):  
Behavioral Finance ◽  
Futures Markets ◽  
Futures Market ◽  
Policy Implications ◽  
Short Term ◽  
Content Type ◽  
Directional Relation ◽  
Capm Model ◽  
Abnormal Profits ◽  
Irrational Traders

Purpose The purpose of this paper is to investigate whether the interaction between sentiments and past prices can lead to higher abnormal profit in futures markets. Such examinations allow the authors to relate the paper to the debate that focuses on examining the behavior of different types of traders in futures market, and who among these traders destabilize the markets. Design/methodology/approach First, the authors develop new dynamic strategies in US futures market that combine sentiment by type of traders based on trader position provided by the Disaggregated Commitments of Traders with short-term contrarian signals. Next, the authors adjust the abnormal profits to the CAPM model and Miffre and Rallis’s (2007) model. Finally, the authors use the Du (2012) decomposition methodology. Findings The main findings are that the abnormal profit is more pronounced when the authors combine past returns with lagged high producer/merchant/processor/user or low managed money sentiment. The results from swap dealer or other reportable groups show that there is no pervasive directional relation between their sentiment and contrarian profit. A further investigation of the sources of abnormal profits demonstrates that these profits survive even after the adjustment of obtained return to risk. Instead, these profits are mainly due to the overreaction to the news by irrational traders. Originality/value Based on behavioral finance theories, the authors conclude that producer, merchant, processor and user behave like irrational traders, while managed money traders behave like rational ones. Given that current regulatory proposes the limitation of speculation, the policy implications of these results are important. Therefore, these findings suggest that policy distinctions on trading motives may be more challenging to construct than ever.

Price discovery and volatility spillover: an empirical evidence from spot and futures agricultural commodity markets in India

2020 ◽  
Vol 10 (4) ◽  
pp. 447-473 ◽  
Author(s):  
Manogna R L ◽  
Aswini Kumar Mishra
Keyword(s):  
Granger Causality ◽  
Futures Markets ◽  
Price Discovery ◽  
Spillover Effects ◽  
Futures Market ◽  
Commodity Markets ◽  
Volatility Spillover ◽  
Agricultural Commodity ◽  
Content Type ◽  
Spot Prices

PurposePrice discovery and spillover effect are prominent indicators in the commodity futures market to protect the interest of consumers, farmers and to hedge sharp price fluctuations. The purpose of this paper is to investigate empirically the price discovery and volatility spillover in Indian agriculture spot and futures commodity markets.Design/methodology/approachThis study uses Granger causality, vector error correction model (VECM) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) to examines the price discovery and spillover effects for nine most liquid agricultural commodities in spot and futures markets traded on National Commodity and Derivatives Exchange (NCDEX).FindingsThe VECM results show that price discovery exists in all the nine commodities with futures market leading the spot in case of six commodities, namely soybean seed, coriander, turmeric, castor seed, guar seed and chana. Whereas in case of three commodities (cotton seed, rape mustard seed and jeera), price discovery takes place in the spot market. The Granger causality tests indicate that futures markets have stronger ability to predict spot prices. Supporting these, the results from EGARCH volatility test reveal that there exist mutual spillover effects on futures and spot markets. Thus, it could be inferred that futures market is more efficient in price discovery of agricultural commodities in India.Research limitations/implicationsThese results can help the market participants to benefit by hedging out the uncertainty and the policymakers to design futures contracts to improve the efficiency of the agricultural commodity derivatives market.Practical implicationsThe findings provide fresh view on lead–lag relationship between future and spot prices using the latest data confirming that futures market indeed is dominant in price discovery.Originality/valueThere are very few studies that have explored the efficiency of the agricultural commodity spot and futures markets in India using both price discovery and volatility spillover in a detailed manner, especially at the individual agriculture commodity level.

Market efficiency in Indian soybean futures markets

2014 ◽  
Vol 9 (4) ◽  
pp. 520-534 ◽  
Author(s):  
Thiagu Ranganathan ◽  
Usha Ananthakumar
Keyword(s):  
Market Efficiency ◽  
Risk Premium ◽  
Futures Markets ◽  
Structural Breaks ◽  
Time Varying ◽  
Content Type ◽  
Futures Contract ◽  
Long Run ◽  
Short Run ◽  
Commodity Derivatives

Purpose – The National commodity exchanges were established in India in the year 2003-2004 to perform the functions of price discovery and price risk management in the economy. The derivatives market can perform these functions properly only if they are efficient and unbiased. So, there is a need to properly evaluate these aspects of the Indian commodity derivatives market. The purpose of this paper is to test the market efficiency and unbiasedness of the Indian soybean futures markets. Design/methodology/approach – The paper uses cointegration and a QARCH-M-ECM-based framework to test the market efficiency and unbiasedness in the soybean futures contract traded in the National Commodity Derivatives Exchange (NCDEX). The cointegration test is used to test the long-run unbiasedness and market efficiency of the contract, while the QARCH-M-ECM model is used to test the short-run market efficiency and unbiasedness of the contract by allowing for a time-varying risk premium. The price data is also tested for presence of structural breaks using a Zivot and Andrews unit root test. Findings – The soybean contract is unbiased in the long run, but there are short-run market inefficiencies and also a presence of a time-varying risk premium. Though the weak form of market efficiency is rejected in the short run, the semi-strong market efficiency is not rejected based on the forecasts. Originality/value – This is the first paper to consider time-varying risk premium while performing the tests of market efficiency and unbiasedness on Indian commodity markets.

Weak GDP may delay policymakers’ ‘Industry 4.0’ plans

2019 ◽  
Keyword(s):  
Industry 4.0 ◽  
Customer Value ◽  
Capital Investment ◽  
Potential Growth ◽  
Content Type ◽  
Data Services ◽  
Industrial Sectors ◽  
Property Data ◽  
The Social ◽  
Development Processes

Significance This spending is needed as manufacturers are under pressure to re-engineer their businesses by deploying technologies to enhance productivity and develop and scale new products and data-based services under the rubric of 'Industry 4.0'. Impacts Technologies will revolutionise every aspect of industry from materials, product development, processes, networks and client interactions. Customer solutions based on intellectual property, data, services, skills and other intangibles will be critical sources of value creation. Capital investment is falling amid rising cashflow pressures and competition and faltering demand; this could reduce potential growth. Slower growth will worsen differences between firms that successfully adopt technologies to enhance customer value and those that do not. Governments will face rising pressure to respond to the social impacts of changes affecting their industrial sectors and to protect jobs.

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