Multi Commodity Research Articles

HEDGING IN AGRICULTURAL COMMODITIES

The Indian Agriculture Sector is on the edge of a rebellion that will revolutionize the complete food chain by means of the total food production in India is expected to twofold in the following ten years. Outstanding export projections, competitive pricing of agricultural products that are internationally comparable has created trade prospects in the agro industry. Agricultural Output is expected to grow by 11% in 2018-2019 after recording a 8-9 % increase in the previous years. It will create Indian Agriculture Industry Gateway by which exporter and importer can fulfill their requirement and reap the benefits of agro related opportunities. MCX (Multi Commodity Exchange) and NCDEX (National Commodity Derivatives Exchange) has developed opportunities for trading in spot and forward trade. It will help to develop India as Agricultural Based Economy. Trading of agricultural commodities help the traders to take the advantage of Price Fluctuations but also faces Investment Risk and Price Risk. Movement in future prices create the possibility for short

An approximation to max min fairness in multi commodity networks

The two objectives of max min fairness (MMF) in multi commodity networks are maximizing the overall throughput so the network operator is satisfied when network is utilized, and minimizing the overall difference in throughput between commodities satisfying the users with fair bandwidth allocation. These two objectives are conflicting, so are translated into a bi-objective model where throughput is maximized in one objective, and the difference in flow between commodities is minimized in the other objective. The proposed approach in this paper is meant to handle large scale networks since the common approaches are feasible only on small to medium scale networks. Although the solution is an approximation to MMF, but it can be exact to the MMF solution when ɛ is properly selected. An illustrative example is discussed in addition to experimentations on real and random networks. The experimentations show the effectiveness of the proposed model.

Conceptual design and performance analysis of a parabolic trough collector supported multi-commodity cold storage

In this paper, a conceptual design of a parabolic trough collector supported multi–commodity cold storage based on LiBr–water absorption system has been proposed to reduce wastage of food grains. The cold storage has been designed to store three high value perishable commodities namely: potato, olive and grapefruit for different months of a calendar year. A thermal model has been developed to predict the performance of the proposed cold storage on an hourly basis. A parabolic trough collector based heating system has also been designed to meet the heat load of the generator during the sunshine hours. To make the system operational in rural areas where grid electricity may not be available, an outline for the power system based on a combination of solar PV and thermal system has been proposed. To provide power backup, an integrated solar hydrogen system has been introduced in the scheme. Finally, the performance of the proposed cold storage has been analysed for representative days of various months of a climatic cycle of Kolkata, India (22.57°N, 88.36°E). The study reinforces the need and viability of utilization of single commodity cold storages for the storage of multi-commodities round the year, powered through solar energy.

VOLATILITY SPILLOVER BETWEEN SPOT AND FUTURES MARKET OF HIGHLY TRADED COMMODITIES IN INDIA: The DCC-GARCH Approach

This study intends to examine the volatility spillover effects and measure the time-varying correlations between futures and spot prices of thirteen highly traded commodities traded on Multi Commodity Exchange (MCX) of India. The research uses Exponential GARCH proposed by Nelson (1991) to explore the direction and magnitude of spillover effects between futures and spot commodity market and employs Dynamic Conditional Correlation (DCC) GARCH proposed by Engle (2002) to demonstrate the time varying conditional correlation between heteroscedastic coefficients of the futures and spot markets. Empirical results show that significant and asymmetric bi-directional volatility spillover effects exist in case of most of the selected commodities, even though, the magnitude of volatility spillover is found larger in the direction from futures market to spot market. The dynamic correlation between the conditional variance of the spot and future markets is found to be significant in case of all the commodities except Silver and Copper. It proves that significant volatility spillover effect is present between spot and futures markets of selected commodities. Understanding of volatility transmission and interrelationship between spot and futures commodity market will help investors make right investment decisions, portfolio optimization and financial risk management. Policy makers and regulators can use this knowledge in planning and implementing appropriate regulatory framework. Much of the earlier research focuses on inter market volatility spillover taking into consideration two or more different financial markets. This study focuses on intra market volatility spillover by studying the interactions of spot-futures prices of commodities. Also, considering the time-varying nature of conditional correlations, this study employs EGARCH and multivariate GARCH (DCC) to capture the volatility spillover effects instead of univariate GARCH or standard linear VAR models.

Domestic and International Information Linkages between Gold Spot and Futures Markets: An Empirical Study for India

This article examines information linkages between gold spot market in India and gold futures at India’s Multi Commodity Exchange (MCX) and five international platforms [i.e., Commodity Exchange (COMEX), Dubai Gold and Commodity Exchange (DGCX), Tokyo Commodity Exchange (TOCOM), Hong Kong Exchange (HKE) and Singapore Mercantile Exchange (SMX)] from August 2008 to March 2015. Cointegration procedure and vector error correction model (VECM), supported by Granger causality, are employed to study price discovery process, and bivariate EGARCH-BEKK model is used to examine volatility spillover process. At domestic level, spot market dominates the futures in information transmission process. Internationally, DGCX leads all other exchanges in price discovery process, while COMEX leads in volatility spillovers. In price discovery, MCX leads only TOCOM till August 2013, while price discovery is absent thereafter. In volatility spillovers, MCX dominates TOCOM and HKE till this period and only HKE afterwards. Thus, information linkages between MCX and international exchanges appear to have been impacted severely since August 2013. The study highlights the need to re-establish price and volatility linkages between Indian and international exchanges, and also provides significant suggestions for policymakers. The study is relevant for investors, researchers and the academia. It contributes to market efficiency and information transmission literature for commodity markets.

Testing Multi Bubbles for Commodity Derivative Markets: A Study on MCX

Due to their volatility differences, yield differences and low correlations with equity markets, metal futures are held for diversification in the international investors’ portfolios. Beginning with dot.com bubble and following global crisis, the mutual movement of equity markets caused investors to canalize alternative investment vehicles. The study aims to investigate if there are bubbles in metal futures in The Multi Commodity Exchange of India Limited (MCX) related the period beginning from January 2010 to August 2017 for copper, lead, nickel and zinc; and March 2010 to August 2017 for aluminum in a weekly data range. Using Sup Augmented Dickey Fuller (SADF) and Generalized Sup Augmented Dickey Fuller (GSADF) tests, no evidence on bubble could be found in any metal market in the used MCX sample. The precious metal markets are out of the sample because of their relatively high volatility.

Do global oil price shocks affect Indian metal market?

The main objective of this paper is to investigate the spillover effect of global crude oil prices on Indian metal market using dynamic conditional correlation generalized autoregressive conditional heteroskedasticity models. The study considers Indian metal market, Multi Commodity Exchange of India Limited METAL index and two precious metals gold and silver, and three industrial metals aluminium, copper and zinc over the period from 1 June 2006 to 31 March 2017. The results of the study show moderate co-movement between West Texas Intermediate (WTI) crude oil and Indian metal market. Precious metals gold and silver do not show either upward nor downward trend even in global financial crisis 2008–2009 while industrial metals aluminium, copper and zinc are weakly correlated to crude oil prices. In addition, it is found that global crude oil prices have short-term as well as long-term memory effect on Indian metal market and metal prices. The study presents the case for diverse stakeholders to improve strategic oil reserves for stabilizing oil prices during global turmoil. Also, policy makers and practitioners may draw meaningful conclusions from findings of the present study to improve future market for stabilizing spot prices of metals while operating in Indian metal markets.

A Forest-to-Product Biomass Supply Chain in the Pacific Northwest, USA: A Multi-Product Approach

Abstract. A comprehensive biomass supply chain landscape model is presented to provide an analysis of transportable biomass conversion facility design and evaluate its potential economic viability. This study focuses on the generation of a tactical-based landscape model to optimize biomass extraction, transportation, conversion and product production within a market system. The model considers various pathways including supply options at landings (burn, grind, chip, bale), centralized landings (grind/chip), biomass conversion facilities (biochar, briquettes, torrefied wood) and delivery to final market. The model solves a multi-period, multi commodity, multi-echelon combinatorial problem to maximize net present value using a genetic algorithm. The landscape is evaluated over a one year planning horizon with monthly time steps simulating a transportable conversion facility mobilization cycle. A hypothetical biochar facility located in Lakeview, Oregon was used as a case study. A sequence of scenarios are used to vary system inputs (logistics, product pricing and moisture management strategies) to put bounds around system viability. The results provide an economic framework to view the Pacific Northwest forest harvest residues processing, conversion and transportation supply chain options. System viability is largely dependent on market pricing, plant assumptions and conversion estimates while processing and transportation logistics are smaller, but important contributors for small scale biomass conversion faculty design configurations. Keywords: Biomass supply, Biomass products, Facility location, Tactical planning, Transportable plants.

The relative efficiency of the crude oil futures market: evidence from India

The purpose of this study is to identify the extent of relative efficiency of the futures contracts of crude oil, traded in the multi commodity exchange of India limited. This study examines the price discovery process in the short-run and long-run by using daily data from 1 April 2006 to 30 June 2015. Stationarity and cointegration tests reveal that spot and futures prices are I(1) and cointegrated. Granger causality test has been employed to examine the short-run price discovery, which shows a bi-directional causality with a dominance of the futures market. Three different information share techniques-component share method of Gonzalo and Granger (1995), information share method of Hasbrouck (1995) and modified information share of Lien and Shrestha (2009) – have been used to measure the relative efficiency of the spot and futures market in the long-run. These results (short-run and long-run) indicate that the price discovery takes place in the futures market. Relative efficiency and the price discovery have crucial implications for optimal portfolio allocation and forecasting of future spot prices. These findings might be useful for the regulators, government, exchange and policy makers to form market structure policies and guidelines for the commodity markets in emerging economies.

Changing Senario of Carbon Finance in India

Decarbonizing the global economy is a strategic imperative as has been suggested by Intergovernmental Panel on Climate Change (IPCC) by striving for a transformation in energy production. This calls for low carbon transformation by the middle of this century and adoption of new pathways which shall help in achieving this objective. Runway climate disruptions and warnings by leading climatologists, ecologists, agronomists and economists have led to a process of shifting of world to a low carbon economy. In this backdrop, it becomes essential to analyze the basic factors, perspectives and drivers of carbon market in India. To analyze the theoretical framework and to present anecdote of carbon credit market in India, the paper understand the price discovery mechanism/information spillover/market efficiency and volatility dynamics in Indian carbon credit market and examines the reasons for the carbon credit market failure in India. For the purpose of study, data of Spot and Future prices of Carbon Credits has been collected from official Statistical database of Multi Commodity Exchange of India. The time period has been taken from June’08 to Nov’11 on a daily basis and various reports have been gathered from virtual databases. The paper concludes by suggesting strategies for the revival of aforementioned market in India.

The relative efficiency of the crude oil futures market: evidence from India

The purpose of this study is to identify the extent of relative efficiency of the futures contracts of crude oil, traded in the multi commodity exchange of India limited. This study examines the price discovery process in the short-run and long-run by using daily data from 1 April 2006 to 30 June 2015. Stationarity and cointegration tests reveal that spot and futures prices are I(1) and cointegrated. Granger causality test has been employed to examine the short-run price discovery, which shows a bi-directional causality with a dominance of the futures market. Three different information share techniques-component share method of Gonzalo and Granger (1995), information share method of Hasbrouck (1995) and modified information share of Lien and Shrestha (2009) – have been used to measure the relative efficiency of the spot and futures market in the long-run. These results (short-run and long-run) indicate that the price discovery takes place in the futures market. Relative efficiency and the price discovery have crucial implications for optimal portfolio allocation and forecasting of future spot prices. These findings might be useful for the regulators, government, exchange and policy makers to form market structure policies and guidelines for the commodity markets in emerging economies.

A multi-omics based ecological analysis of coastal marine sediments from Gladstone, in Australia's Central Queensland, and Heron Island, a nearby fringing platform reef

The impact of anthropogenic factors arising from point and non-point pollution sources at a multi commodity marine port and its surrounding ecosystems were studied using sediment samples collected from a number of onshore (Gladstone Harbour and Facing Island) and offshore (Heron Island and Fitzroy Reefs) sites in Australia's Central Queensland. Sediment samples were analyzed for trace metals, organic carbon, polycyclic aromatic hydrocarbons (PAH), emerging chemicals of concern (ECC) and sterols. Similarly, the biological and biochemical interaction between the reef and its environment was analyzed by the multi-omic tools of next-generation sequencing characterization of the bacterial community and microbial community metabolic profiling. Overall, the trace elements were observed at the lower end of the Australian environmental guideline values at the offshore sites, while higher values were observed for the onshore locations Nickel and copper were observed above the high trigger value threshold at the onshore sites. The levels of PAH were below limits of detection across all sites. However, some of the ECC and sterols were observed at higher concentrations at both onshore and offshore locations, notably, the cholesterol family sterols and 17α-ethynylestradiol. Multi-omic analyses also indicated possible thermal and photo irradiation stressors on the bacterial communities at all the tested sites. The observed populations of γ-proteobacteria were found in combination with an increased pool of fatty acids that indicate fatty acid synthesis and utilisation of the intermediates of the shikimate pathways. This study demonstrates the value of applying a multi-omics approach for ecological assessments, in which a more detailed assessment of physical and chemical contaminants and their impact on the community bacterial biome is obtained.

Hedging Efficiency of Indian Commodity Futures

This article examines the hedge ratio and hedging effectiveness in agricultural (castor seed, guar seed) and non-agricultural (copper, nickel, gold, silver, natural gas and crude oil) commodities traded in National Commodity and Derivative Exchange (NCDEX) and Multi Commodity Exchange (MCX), respectively. Constant and dynamic hedge ratios are estimated by using ordinary least square (OLS), vector autoregression (VAR), vector error correction model (VECM) and vector autoregressive-multivariate generalized autoregressive conditional heteroskedasticity model (VAR-MGARCH). The results of constant as well as dynamic hedge ratios reveal that the Indian futures market provides higher hedging effectiveness in case of precious metal (65–75 per cent) compared to industrial metal and energy commodities (less than 50 per cent). Hedging effectiveness for castor seed and natural gas is even lower than 10 per cent. This study concluded that VECM and VAR-MGARCH both are providing higher hedging although VECM is providing the highest hedge ratio. It has been found that the next to near month futures provide better hedging effectiveness as compared to near month futures for crude oil and silver. It is recommended that the policy makers should pay attention towards the number of delivery centres, standard of quality of underlying assets and transaction costs in spot market.

Intraday Periodicity and Volatility Forecasting: Evidence from Indian Crude Oil Futures Market

We estimate intraday periodicities in return volatility by implementing two time series procedures—flexible Fourier form and cubic spline. We use intraday data for more than five years for crude oil futures contracts traded at the Multi Commodity Exchange India Limited. Filtration of the intraday periodicities from the raw returns reveals long-run dependence in volatility. We observe the presence of recurring and consistent intraday patterns in return volatility. Further, we find that adjustment for the intraday periodicity in return volatility improves forecasting performance. Our results are robust after controlling for the scheduled macroeconomic announcements. JEL Classification: C14, C22, G10

Market efficiency and information content of Indian commodity futures markets

This article examines the efficiency of pricing of eight commodity futures traded at Multi Commodity Exchange (MCX) and National Commodity & Derivative Exchange (NCDEX) of India. We find that the current futures prices and the expiration-day spot prices are generally cointegrated, and exhibit market efficiency. We also find evidence of predictive content in the futures prices for the future spot prices. This content varies among different commodities, and is more significant for the natural gas and agricultural commodities, which have higher storage and transportation costs. The risk premium is absent in the futures prices of most of our commodities, excepting two agricultural commodities and nickel.

Portfolio co-integration dynamics of metal and energy commodities: evidence from India

The present paper has bifocal objectives. First, the paper explores the time series dynamics of the industrial and precious metals commodities futures contract traded on the India's largest commodity exchange, Multi Commodity Exchange of India. Second, the paper focuses on the causality dynamics of industrial and precious metals. No such study has been undertaken on the Indian commodity bourses. In addition, it focuses on the existence of the long-term co-integration relationship - if any - between these specific categories of commodities. Amid sharp rises in both commodity prices and commodity investing, many commentators have wondered whether commodities nowadays move in sync with traditional asset classes like equity, gold, crude oil and Forex. The rationale behind diversification contends that a portfolio of different kinds of investments will, on average, yield higher returns and pose a lower risk than any individual investment found within the portfolio. The paper tries to identify the long run relation-ship of industrial and precious metals with its traditional investment counterparts like Crude Oil prices, USDINR exchange rates, and Nifty 50 index. For same, the paper has utilised advance Granger causality and Johansen co-integration tests. Our results imply that industrial and precious metals may not able to provide the benefits of diversification all the time.

Portfolio co-integration dynamics of metal and energy commodities: evidence from India

The present paper has bifocal objectives. First, the paper explores the time series dynamics of the industrial and precious metals commodities futures contract traded on the India's largest commodity exchange, Multi Commodity Exchange of India. Second, the paper focuses on the causality dynamics of industrial and precious metals. No such study has been undertaken on the Indian commodity bourses. In addition, it focuses on the existence of the long-term co-integration relationship - if any - between these specific categories of commodities. Amid sharp rises in both commodity prices and commodity investing, many commentators have wondered whether commodities nowadays move in sync with traditional asset classes like equity, gold, crude oil and Forex. The rationale behind diversification contends that a portfolio of different kinds of investments will, on average, yield higher returns and pose a lower risk than any individual investment found within the portfolio. The paper tries to identify the long run relation-ship of industrial and precious metals with its traditional investment counterparts like Crude Oil prices, USDINR exchange rates, and Nifty 50 index. For same, the paper has utilised advance Granger causality and Johansen co-integration tests. Our results imply that industrial and precious metals may not able to provide the benefits of diversification all the time.

Crude oil market and global financial crisis - structural break and market volatility analysis

This research paper aims to analyse the impact of the recent global financial crisis on the volatility of crude spot market in India. The data has been collected for the period 2005 to 2014 from Multi Commodity Exchange, India. This paper first uses Ramsay RESET test to check the linearity of the relationship between spot and futures natural log returns. For structural break analysis, tests like Chow test, Chow forecast test, recursive estimates of CUSUM test and CUSUM of squares test have been performed on the monthly data of spot and futures price return series. No evidence of structural break was found in any test except CUSUM of squares test. Using EGARCH model with a dummy, we found that there was no effect of the global financial crisis on the volatility of crude spot market. The possible reason for the volatility of crude in 2008 could be financialisation of commodity exchanges and excessive speculation in crude oil futures.

Complex vehicle transport problems: taxonomy, new variants, challenges and solution methodology

Due to appeared of several and new alternatives of vehicle routing problems (VRPs) in the last years, the contributions focus on design of traffic flow and transportation systems, vehicle routing, and other important aspects of supply chain management such as dynamic routing, multi commodity problems, inventory management, lot sizing, and lot scheduling. In this paper, we are going to present an extensive review of the general vehicle routing problem then we are going to focus on the problematic approaches in this field. For each one of these problematic, a positioning compared to this state of the art will be developed. In the first part a synthesis of literature review devoted to the complex and logistic transport problems in general and a transport problem with limited fleet and common carrier in particular with stochastic and dynamic vehicle routing problem. In the second part, a description of the vehicle routing problem with mathematical formulations will be presented. The different variants of this problem will be approached.

Multi-Commodity Based Widest Congested Edge Disjoint Path Algorithm (MBWCEDP) using MPLS

Objectives: The paper deals with the Online Multipath Routing of the Traffic flows in MPLS networks. A good multipath routing algorithm fulfills all the online traffic demands at real time. Many conventional multipath routing algorithms were considered good in respect of many parameters but still suffered from their highly rejected online traffic demands rate. Methods/Statistical Analysis: The algorithm presented classifies the traffic demands into various profile classes (which are generated based on the SLAs signed by the Internet users). These profile classes work as a rough estimator of future traffic demands and are used to solve a multi commodity network flow problem. In the proposed algorithm Multicommodity network flow formulation groups the packet flows as per profile classes with the aim to minimize the cost, to prevent network hotspots i.e. bottleneck links and to ensure minimum rejected requests/ traffic demands. The algorithm works in two phases- In the preprocessing phase SLAs, Global and Local quasi static knowledge about the network are used to generate Multi-commodities based “Profile Classes” in the first phase and then these Multi-commodities based packet flows are distributed over widest residual bandwidth Disjoint Paths with respect to the bottleneck links in the second phase. The transmission of Multi-commodity based flows through disjoint paths w.r.t. bottleneck edges prevent the network from critical deadlock point which helps in minimizing the congestion, delays, rejected requests and maximizing the throughput, i.e. improving the overall performance of the network. Findings: To measure the performance of proposed algorithm to the Profile Based Algorithm a series of experiments were measured. Randomly generated request sequence is used for which a random sequence of individual flow request were generated and measured the performance both in terms of number of flows routed and total bandwidth request that was satisfied. Blocking probability for each edge is also considered random.In the findings is shown that out of total 1200 requests, performance of PBR is very poor as it rejects many requests due to overly strict admission control and minimum hop algorithm. The proposed algorithm cleverly controls traffic flow admission by considering congested edges in a disjoint way, so that one LSP does not interfere other LSPs. Application/Improvements: The network information is utilized to its extreme and most of the online path requests are accepted only a few requests are rejected.