Abstract.This article analyses temperature data for Seoul based on a well defined daily average temperature (DAT) derived from records dating from 1954 to 2009, and considers related weather derivatives using a previous methodology. The temperature data exhibit some quite distinctive features, compared to other cities that have been considered before. Thus Seoul has: (i) four clear seasons; (ii) a significant seasonal range, with high temperature and humidity in the summer but low temperature and very dry weather in winter; and (iii) cycles of three cold days and four warmer days in winter. Due to these characteristics, seasonal variance and oscillation in Seoul is more apparent in winter and less evident in summer than in the other cities. We construct a deterministic model for the average temperature and then simulate future weather patterns, before pricing various weather derivative options and calculating the market price of risk (MPR).
Weather Derivatives and the Market Price of Risk
