eprintid: 746
rev_number: 8
eprint_status: archive
userid: 17
dir: disk0/00/00/07/46
datestamp: 2019-01-21 22:42:42
lastmod: 2019-01-21 22:42:42
status_changed: 2019-01-21 22:42:42
type: report
metadata_visibility: show
creators_name: Connaughton, Colm
creators_name: Herman, John
creators_name: Johansen, Adam
creators_name: Kawabata, Emily
creators_name: Kerr, Robert
creators_name: Pegg, Michael
creators_name: Reizenstein, Jeremy
creators_name: Sakrajda, Piotr
creators_name: Tawn, Nick
creators_name: Whincop, Luke
corp_creators: Jon Gascoigne
title: African Drought Risk Pay-Out Benchmarking
ispublished: pub
subjects: finance
studygroups: esgi130
companyname: Willis Towers Watson
full_text_status: public
abstract: This report contains exploratory data analysis of rainfall and Water Resource Sufficiency Index (WRSI) data provided by African Risk Ca- pacity (ARC). The purpose is to assess the predictability of droughts in Africa. We assess the appropriateness of the historical WRSI bench- marks set by ARC members compared to the observed WRSI values for different regions. We conclude that the benchmarks are broadly sensible. We then compare a number of linear time series models based on their ability to fit and forecast the WRSI time series. We conclude that sim- pler models like Simple Moving Average and Moving Median are more appropriate than more sophisticated models containing trends and sea- sonality like Holt Winter and TBATS. We also investigate the use of the SARIMA and TBATS models to forecast the seasonal patterns observed in rainfall data and conclude that both models can generate structured forecasts that reflect seasonal variability. The statistical evidence how- ever favoured TBATS over SARIMA. Attempts to measure the influence of the El Nin ̃o-Southern Oscillation on rainfall levels are inconclusive for the areas studied. Finally we perform a simple application of univariate Extreme Value Theory to rainfall data and conclude that further inves- tigation is necessary to understand how the catastrophic famine that affected Ethiopia in the early 1980’s would be reflected in the data if a similar event were to reoccur today.
date: 2017
citation:   Connaughton, Colm and Herman, John and Johansen, Adam and Kawabata, Emily and Kerr, Robert and Pegg, Michael and Reizenstein, Jeremy and Sakrajda, Piotr and Tawn, Nick and Whincop, Luke  (2017) African Drought Risk Pay-Out Benchmarking.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/746/1/2017-11-20_ESGI130_ARC_final.pdf