Pricing Air Pollution Options Based นn Binomial Tree Model

Abstract

In recent years, Thailand has experienced severe air pollution. This air pollution is known as PM2.5 air pollution and hazardous dust. PM2.5 means size of dust is smaller than 2.5 microns. This affects in Thai business in many sectors such as tourism and services, etc. Each year, this issue lasts for several months and the duration trends to increase every year. Therefore, it is in need of a solution to reduce the risk that may occur to mentioned businesses. Financial tools are used in this study case. Derivative product will mainly be the topic and describing the finding value of the local air pollution with option products.

The study focuses on the process of Ornstein-Uhlenbeck, and investigating the modeling of the air quality index in Bangkok and metropolitan region between 1 August 2016 – 29 February 2020. Bangkok is a crucial location in Thai business and tourism. The result values describe how to solve the Option Pricing of air pollution in option contracts by Binomial tree solution.

The study results from Ornstein-Uhlenbeck process gives a tend to the cost of the modeling value but there are some fluctuations, when the average air quality index from collection and the study’s result from modeling by Binomial tree solution with call option and put option. The final result is not deviate from each other especially in case of 6 months option contact.