Design of Derivative Contracts of Meteorological Indicators of Agricultural Sector in Iran (Case Study: Shiraz)

مجله اقتصاد و توسعه کشاورزی

Article 6, Volume 32, Issue 3 - Serial Number 41, October 2018, Pages 259-268   

Document Type: Research Article

DOI: 10.22067/jead2.v32i3.74311

Authors

Z. Nematollahi¹; S.A. Hosseini Yekani^{* 2}; H. Amirnejad³

¹Sari University of Agricultural Science and Natural Resources.

²Sari University of Agricultural Science and Natural Resources

³Sari University of Agricultural Science and Natural Resources, Sari

Abstract

Introduction: Weather factors such as temperature has an enormous influence on agriculture. Therefore, efficient weather risk management has become an urgent requirement for this sector. In recent years, a new instrument named weather derivatives has been introduced to cope with production risk. So, this paper aims at designing and pricing the temperature-based weather derivatives (WD) in order to reduce risk exposure for Iranian agriculture industry. For this purpose, a put option with cumulated growing degree days (GDD) as its underlying index has been selected
Materials and Methods: We first examine the relationship behavior of temperature and yield for wheat and Rice in Shiraz. Then, for designing and pricing WD in agriculture, GDD index has been selected as one of the most widely used temperature indicators in agricultural sector. We design this contract for each stage of wheat and rice life cycles instead of designing one contract for crop’s growing seasons. So, the life cycles of two crops (Wheat and Rice) divided into 7 stages titled: Emergence, Tillering, and stem elongation, Gravidity, Flowering, Milky ripe and Maturity. Since contract design happens during these stages, we have 6 contracts for each product. Each contract starts with the beginning of one stage and continues until the other stagestarts.
The GDD index is calculated based on the temperature data and the life cycles of the wheat and rice in Shiraz. So, the long-term mean of GDD is calculated as the Strike level of put option contract. The simulation method based on daily temperature data is used for pricing the contracts. Finally, the expected payoff and the price of the options are determined using the Monte Carlo simulation method.
Results and Discussion: The results revealed a significantly positive relationship between wheat yield and GDD as well as a positive impact of GDD on Rice yield. This implies that increasing growing degree days would increase wheat and rice yield. The R2 coefficient also indicates that 76 percent of the variations in yield of wheat and rice are explained by the growing degree day's index. Therefore, the design of temperature based weather derivatives contracts will have high efficiency in order to cover the risk of farmers.
As expected, rice has a relatively higher strike price than wheat as rice-groups accumulate GDD in warm seasons. We assume that the annual risk-free interest rate r is 15 percent and the expected payoff also the price of the contract put option is calculated based on 10000 Monte Carlo simulations. Based on the results, the most wheat payoff in Shiraz was related to the second contract (from the November 21st to the March 6st). Therefore, the use of the temperature option in this period will compensate farmers for their loss. In terms of rice, the most payoffs in Shiraz have occurred in the twelfth contract (Aug 19st to Oct 17st).
Conclusion: Financial weather derivatives (WD) are designed to serve as hedging instruments against weather risk and to balance the income of producers such as farmers. WD was first traded in 1997 and since then their popularity has increased. However, weather derivatives as well as designing and pricing of contracts based on weather has not been introduced in Iran. Therefore, in present research, while introducing the mechanism of the weather derivatives and options based on weather indicators the designing and pricing of put option contracts based on temperature have been discussed in Shiraz. For this purpose, GDD index has been selected as one of the most widely used temperature indicators in agricultural sector. The GDD index is calculated based on the temperature data and the life cycles of the wheat and rice in Shiraz. So, the long-term mean of GDD is calculated as the Strike level of put option contract. The simulation method based on daily temperature data is used for pricing the contracts. Finally, the expected payoff and the price of the options are determined using the Monte Carlo simulation method. As discussed before, the temperature options for each city and product are designed based on the different stages of life cycles of the crops so we plan and set the price of put options for six different time periods. Based on the results, the most wheat payoff in Shiraz was related to the second contract during the November 21st to the March 6st. Therefore, the utilization of the temperature option in this period will compensate farmers for their loss. In the case of rice, the most payoffs in Shiraz have occurred in the twelfth contract (Aug 19st to Oct 17st). Therefore, it is recommended to use the results of the present study to launch a weather derivative’s market. In addition, it is vital to change and revise these contracts by conducting various studies about the effects of changing contracts specifications on farmers and other Contributors in the market.

Keywords

Production Risk; Agricultural; Weather Derivatives; GDD Index

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