A COMPARISON BETWEEN PERT DISTRIBUTION AND SEASONAL ARIMA MODEL TO FORECAST RAINFALL PATTERN

Abstract

Weather is becoming more and more unpredictable for farmers, and the frequency of extreme weather events is also increasing. Small households in Kenya are vulnerable to these extreme weather shocks, and failures in effective hedging will make sustainable production extremely difficult for them. The goal of this thesis is to use historical rainfall record in Kenya to forecast rainfall and take quantile of the rainfall distribution to get a trigger for a put-option embedded innovative financial instrument. There are two methods to develop this lower 20% band trigger, which are pert distribution and time series method. Finally, I get two sets of results from two methods. With the help of the simulation results, insurance companies will be able to design a weather-index insurance for small households in Kenya. For farmers, they will use this flexible insurance as an effective substitute for traditional deposit, which requires productive assets as collateral.