دورية أكاديمية

An Actuarial Pricing Method for Air Quality Index Options

التفاصيل البيبلوغرافية
العنوان: An Actuarial Pricing Method for Air Quality Index Options
المؤلفون: Zhuoxin Liu, Laijun Zhao, Chenchen Wang, Yong Yang, Jian Xue, Xin Bo, Deqiang Li, Dengguo Liu
المصدر: International Journal of Environmental Research and Public Health; Volume 16; Issue 24; Pages: 4882
بيانات النشر: Multidisciplinary Digital Publishing Institute
سنة النشر: 2019
المجموعة: MDPI Open Access Publishing
مصطلحات موضوعية: air quality index, options, Ornstein–Uhlenbeck model, actuarial pricing, risk hedging
جغرافية الموضوع: agris
الوصف: Poor air quality has a negative impact on social life and economic production activities. Using financial derivatives to hedge risks is one of the important methods. Air quality index (AQI) options are designed to help enterprises cope with the operational risk caused by air pollution. First, the expanded Ornstein–Uhlenbeck model is established using an autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH) method to predict AQI for a city. Next, the average AQI is constructed to be as the underlying index for the AQI options. We then priced AQI options using an actuarial method with an Esscher transform. Meanwhile payoff functions for the options are established to let enterprises hedge against the operational risk caused by air pollution. Finally, we determined the price of AQI options using data from Xi’an, China, and the example of a tourism enterprise as a case study of how AQI options can be applied to hedge against operational risk for enterprises. With AQI options trading, enterprises can hedge against operational risks caused by air pollution. The applicability of AQI options is wide, it can also be applied in other cities or regions.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
العلاقة: https://dx.doi.org/10.3390/ijerph16244882Test
DOI: 10.3390/ijerph16244882
الإتاحة: https://doi.org/10.3390/ijerph16244882Test
حقوق: https://creativecommons.org/licenses/by/4.0Test/
رقم الانضمام: edsbas.B77E6B40
قاعدة البيانات: BASE