Document Type : Research Article-en
Authors
1 Agricultural Economics, Faculty of Economics and Agricultural Development, Campus of Agriculture and Natural Resources
2 Agricultural Economics, Faculty of Economics and Agricultural Development, Campus of Agriculture and Natural Resources, Karaj, Iran. Also, Adjunct Professor, Johns Hopkins University, Institute for Applied Economics, Baltimore, Maryland, United State
Abstract
Introduction
The Iran Mercantile Exchange (IME) aims to become a regional reference for pricing essential commodities and raw materials, providing a primary option for producers seeking financing and risk management. The core function of the exchange is to hedge against price volatility. Financial market traders engage in hedging for risk management or speculation, which can introduce risks to exchange activities. If an investor fails to fulfill their obligations under certain conditions, the exchange assumes those obligations. Exchanges not only provide a platform for risk management but also implement various policies and methods to control risks arising from market participants' activities. Essentially, market participants seek to protect their interests against adverse future price changes. Hedging allows a production unit to control the costs of raw materials needed for production, enabling better product pricing management. The need for hedging arises when a producer has no control over the prices of raw materials or finished products. The ability to decide on the level of risk to accept or transfer through commodity exchanges is known as hedging capability.
Hedging operations differ from speculation, where the primary goal is to profit from risk management. In the Iran Commodity Exchange, hedging operations by agricultural product traders through a designed trading portfolio have not been widely promoted or considered. Hedging is an investment strategy aimed at reducing the risk of adverse price changes in an asset, typically involving taking a compensatory or opposite position relative to the guaranteed position. Conventional hedging techniques include taking a compensatory position in derivative contracts related to the current position. Another form of hedging can occur through diversification. Hedging is also an automatic insurance policy, where a risk-reward trade-off is achieved by reducing potential risk at the cost of potential benefits. In other words, hedging is costly, and a complete hedge eliminates all risks in a position or investment portfolio.
Generally, domestic studies indicate that price volatility of agricultural commodities in the Iran Commodity Exchange is higher than in the free market and the Chicago Commodity Exchange. Most domestic studies have used weekly and monthly time series and have often ignored the seasonal behavior of agricultural products in unit root tests. The time series models used in domestic studies include ARIMA, VAR, VECM, and ARCH/GARCH models. It is noteworthy that none of the domestic studies have attempted to design a comprehensive model for constructing an optimal agricultural product investment portfolio.
Foreign studies use more advanced methods and claim these methods are superior. Some foreign researchers suggest including agricultural products along with other products in the investment portfolio. According to foreign researchers, equation systems are superior for determining investment portfolios due to the calculation of moving covariances over single equations, although they are more complex in practice. Therefore, single equations are still prevalent.
This paper examines the hedging of hazelnut pistachios with two futures and deposit investment contracts using a daily model from October 19, 2018, to January 18, 2022. Pistachios are one of the two main agricultural products traded on the Iran Commodity Exchange, but the trading value of this product has decreased from approximately 865 billion rials to about 19 billion rials in recent years. This study aims to examine the risk changes of this product and answer how the optimal portfolio selection between the two contracts has changed over the study period.
Materials and Methods
This work outlines methods and strategies for determining an optimal portfolio to hedge the risk of hazelnut pistachios in the Iranian Commodity Exchange. It primarily uses Markowitz's Portfolio Theory, which balances risk and return. The goal is to minimize risk for a given level of expected return or maximize return for a given level of risk.
The hedging ratio is calculated as the ratio of futures contracts to cash positions, using methods like Minimum Variance (MV) and Mean-Variance. GARCH models, including bivariate GARCH and BEKK-GARCH, are employed to model and analyze the volatility and dynamic relationships between spot and futures prices. The HEGY method tests for seasonal unit roots in time series data, crucial for accurate modeling. Multivariate GARCH models capture the interaction between volatilities of different assets, essential for calculating the optimal hedge ratio. Threshold GARCH (TARCH) models account for the asymmetric effects of positive and negative shocks on volatility, important for financial markets where negative returns often have a larger impact on volatility than positive returns.
The study aims to minimize price risk by using these advanced econometric models to find the optimal combination of futures and spot positions in a commodity portfolio.
Results and Discussion
The seasonal unit root test for daily data of hazelnut pistachio contracts using the HEGY method examines the presence of unit roots at seasonal and non-seasonal frequencies. The results indicate significant seasonal and non-seasonal fluctuations, with stronger seasonal effects. Regression analysis reveals significant relationships between the returns of commodity deposit contracts and futures contracts, highlighting the impacts of past returns and shocks on current returns. The optimal ratio of hazelnut pistachio deposit contracts in combination with futures contracts varies across different days and seasons, reflecting market demand and investor preferences.
Conclusion
Based on the results, several policy recommendations for the hazelnut pistachio market can be made:
1. Strengthen and Manage Seasonal Fluctuations: Policymakers and market participants should analyze seasonal fluctuations more closely and plan to counteract unusual seasonal fluctuations. This could include introducing financial derivatives like options or futures contracts to help manage volatility risks.
2. Support Risk Hedging Tools: Developing and promoting risk hedging tools, such as futures contracts and other derivatives, can help investors better manage risks from volatility, especially during periods of high market volatility.
3. Consider Seasonal and Daily Patterns in Portfolio Composition: Policymakers and investors should adjust their investment portfolios based on a detailed analysis of seasonal and daily changes to reduce risk and increase returns.
4. Monitor and Control Volatility During Critical Periods: Given higher demand and volatility in certain months like February and December, it is recommended to closely monitor the market during these periods to prevent abnormal fluctuations. Using price control tools or trading restrictions can help stabilize the market.
5. Develop Supportive Policies in Low-Volatility Months: In months with lower volatility (like July and August), supportive policies such as providing facilities or financial incentives can help maintain market activity and prevent a drop in demand, maintaining stability and reducing risk during low-volatility periods.
These recommendations can help improve the performance of the hazelnut pistachio market and increase efficiency in investment decision-making.
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