Transmission of futures prices to the Italian spot market: Are there opportunities to hedge corn price risk?

2018 ◽  
pp. 193-204
Author(s):  
Samuele Trestini ◽  
Carlotta Penone
Keyword(s):  
Spot Market ◽  
Price Risk ◽  
Futures Prices

scholarly journals HOW EFFECTIVE IS FUTURES AS AN INSTRUMENT OF HEDGING AGAINST PRICE RISK? -A STUDY BASED ON SPOT AND FUTURE PRICES OF GOLD

2016 ◽  
Vol 4 (9) ◽  
pp. 143-150
Author(s):  
Shafeeque Muhammad ◽  
Thomachan
Keyword(s):  
Spot Market ◽  
Futures Market ◽  
Price Risk ◽  
Time Varying ◽  
Risk Hedging ◽  
Hedging Effectiveness ◽  
Cash Market ◽  
Hedge Ratios ◽  
Opposite Position

This paper examines the role of commodity futures market as an instrument of hedging against price risk. Hedging is the practice of offsetting the price risk in a cash market by taking an opposite position in the futures market. By taking a position in the futures market, which is opposite to the position held in the spot market, the producer can offset the losses in the latter with the gains in the former. Both static and time varying hedge ratios have been calculated using VECM-MGARCH model. Variance of return from hedge portfolio has been found to be low. Further hedging effectiveness has been observed to be around 12%.

scholarly journals The Impact of Futures Price Volatility to Spot Market : Case of Coffee in Indonesia

2019 ◽  
Vol 15 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Anis Erma Wulandari ◽  
Harianto Harianto ◽  
Bustanul Arifin ◽  
Heny K Suwarsinah
Keyword(s):  
Exchange Rate ◽  
Price Volatility ◽  
Spot Market ◽  
Futures Market ◽  
Spot Price ◽  
Price Risk ◽  
Price Inflation ◽  
Spot Prices ◽  
Futures Price ◽  
The Impact

Indonesia is the world 4th largest coffee producer after Brazil, Vietnam and Colombia with export potential and higher national consumption concluded in 2017 while the coffee production was relatively stagnant. This was led the producer to not only the production risk but also the price risk which then emphasize the importance of futures markets existence as price risk management. This study is performed to examine the impact of futures price volatility to spot market using ARCH-GARCH toward primary data of coffee futures and spot prices of 1172 trading days starting from January 2014 to June 2018. The ARCH-GARCH analysis result indicates that futures price volatility and monetary variables are impacting the volatility of spot price. Arabica spot price volatility is impacted by volatility of Arabica futures price, inflation and exchange rate while Robusta spot price is impacted by Robusta futures price volatility and exchange rate. This is confirming that futures market plays dominant role in spot price discovery. Local futures and spot prices are also found to be significantly influenced by volatility of offshore futures prices which indicates that emerging country futures market is actually influenced by offshore futures market which the price itself used as price reference.

Market efficiency and price risk management of agricultural commodity prices in India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manogna R.L. ◽  
Aswini Kumar Mishra
Keyword(s):  
Risk Management ◽  
Market Efficiency ◽  
Price Discovery ◽  
The Other ◽  
Price Risk ◽  
Futures Prices ◽  
Agricultural Commodities ◽  
Content Type ◽  
Price Risk Management ◽  
Guar Seed

Purpose Market efficiency leads to transparent and fair price discovery of commodity markets, thus enhancing the value chain for competitive benefit. The purpose of this paper is to investigate the market efficiency of Indian agricultural commodities at spot, futures and mandi markets apart from exploring price risk management in these markets. Design/methodology/approach This study uses Johansen co-integration, vector error correction model and granger causality for analyzing market efficiency of the nine most liquid agricultural commodities across three markets, namely, spot, futures and mandi. All these nine commodities are traded on National Commodity and Derivatives Exchange. Findings The statistical results indicate price discovery exists in the mandi market and spot market leading to futures prices. Mandi price returns are seen to negatively influence futures returns in the case of cotton seed, guar seed and spot returns in the case of jeera, coriander and chana. For castor seed, the three markets are seen to have no long run relationship. The results of Granger causality reveal short run relationship between all the three markets in the case of soybean seed and coriander. In these commodities, prices in all three markets are capable of predicting the prices in the other markets. For the case of cottonseed, Rape Mustard seed, jeera, guar seed, the results indicate unidirectional causality between the mandi markets and the other two markets. Research limitations/implications These results shall facilitate policymakers to explore intervention through integrated agri-platform (IAP) in price discovery and market efficiency. Practical implications The results of this study are useful in understanding the price discovery of mandi markets and its role in the spot and futures market. Agricultural commodities price discovery depends upon the integration of all these three markets. Introduction of IAP as described in the paper shall facilitate price risk management apart from improving the efficiency of price discovery. Originality/value To the best of the knowledge, this is the first study considering mandi, spot and futures prices in the price discovery process in India. In addition, this study found the role of mandi markets in serving the economic function of price discovery and price risk management. Hence, suggests for policy intervention for Indian agricultural commodities to manage price risk.

Understanding the Dependence Structure Between the Futures and Spot Prices of Wheat in Egypt

2019 ◽  
Vol 4 (1) ◽  
pp. 20-37
Author(s):  
Osama Ahmed ◽  
Fadi Abdelradi
Keyword(s):  
Garch Model ◽  
Spot Market ◽  
Dependence Structure ◽  
Futures Prices ◽  
Spot Prices ◽  
Price Increases ◽  
Asymmetric Behavior ◽  
Wheat Market ◽  
Copula Estimation ◽  
Parametric Copula

The aim of this article is to check the dependence structure for the futures-spot prices link of Egyptian wheat. Co-movements between prices are assessed by a GJR-GARCH model and semi-parametric copula estimation. Results suggest a positive futures-spot prices link, which becomes stronger the closer the markets are. Evidence of asymmetric behavior of the prices at times of extreme market situations is found. As a result, increases in wheat futures prices are expected to be passed to the Egyptian spot market, while the prices decline is not passed. This implies that the Egyptian wheat market cannot protect consumers against extreme international wheat price increases.

Do Changes in Natural Gas Futures Prices Influence Changes in Natural Gas Spot Prices?

1993 ◽  
Vol 11 (5) ◽  
pp. 467-472 ◽  
Author(s):  
John H. Herbert
Keyword(s):  
Natural Gas ◽  
Futures Markets ◽  
Spot Market ◽  
Spot Markets ◽  
Futures Prices ◽  
Market Prices ◽  
Spot Prices ◽  
Futures Contract

Data on natural gas futures and spot markets are examined to determine if variability in price on futures markets influences variability in price on spot markets. Using econometric techniques, it is found that changes in futures contract prices do not precede changes in spot market prices.

scholarly journals An Artificial Neural Network For Hedging Crude Oil

2011 ◽  
Vol 3 (1) ◽  
Author(s):  
Hossein Najafi ◽  
Reza Rahgozar ◽  
Brian Champlin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Crude Oil ◽  
Network Model ◽  
Neural Network Model ◽  
Price Risk ◽  
Futures Prices ◽  
Font Size ◽  
Empirical Results ◽  
The Neural Network

<p class="MsoBodyText" style="text-align: justify; margin: 0in 34.9pt 0pt 35.5pt; mso-pagination: none;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">A neural network model for hedging crude oil is introduced.<span style="mso-spacerun: yes;">&nbsp; </span>The NYMEX futures prices is used to investigate the effectiveness of this model. Empirical results show that the neural network model reduces price risk more than other approaches. </span></span></p>

scholarly journals Optimal spot market inventory strategies in the presence of cost and price risk

2010 ◽  
Vol 73 (1) ◽  
pp. 109-137 ◽  
Author(s):  
X. Guo ◽  
P. Kaminsky ◽  
P. Tomecek ◽  
M. Yuen
Keyword(s):  
Spot Market ◽  
Price Risk

scholarly journals Relationship Between Spot Prices and Futures Prices: Evidence From Karachi Stock Exchange

2021 ◽  
Vol 5 (2) ◽  
pp. 109-123
Author(s):  
Muhammad Asif Ali ◽  
Muhammad Asif Ali ◽  
Dr. Naveed Hussain Shah
Keyword(s):  
Granger Causality ◽  
Stock Exchange ◽  
Granger Causality Test ◽  
Spot Market ◽  
Futures Market ◽  
Futures Prices ◽  
Causality Test ◽  
Spot Prices ◽  
Unit Root Testing ◽  
Integration Test

This study investigates the relationship between futures prices and their underlying spot prices of the stocks trading on Pakistan stock market. Data on the monthly closing prices of future contracts and their underlying stocks of 30 companies for the period January 2004 to June 2014 have been taken for analysis. Descriptive statistics, Augmented Dicky Fuller test for unit root testing, Johnson Co-integration test, Granger causality test and Vector Error Correction Model are used. The results confirms significant long term relationship between futures prices and the associated Spot prices in case of 26 companies. The report of Granger causality test indicates that a Bi-directional causality lack to exist in case of each security, VECM shows that Spot prices for current month are effected by previous month prices in case of 7 companies, while futures prices of current month are affected by previous month prices in case of 4 companies. VECM illustrates that the volatility shocks in spot market are less effected by futures market, however the volatility shocks in corresponding futures market were strongly and significantly affected by spot market volatility.

Measuring Price Risk in Commodity Markets

2010 ◽  
Vol 5 (2) ◽  
pp. 380-394 ◽  
Author(s):  
Szczepan Figiel ◽  
Mariusz Hamulczuk
Keyword(s):  
Commodity Markets ◽  
Price Risk
Sign in / Sign up

Export Citation Format

Share Document