PREDICTION OF CATASTROPHIC BOND PREMIUM USING FINANCIAL LOSS PREMIUM PRINCIPLE: CASE STUDY ON PRECIPITATION DATA FORT MCMURRAY, CANADA

A Catastrophic Bond (CAT Bond) is a financial instrument which transfers an insurance risk caused by a natural disaster to a capital market. The prices of CAT bond premiums have changed since the 2008 financial crisis attributed to investors being risk-averse. In this Final Project, a study on a...

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Bibliographic Details
Main Author: Wialldi, Gland
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/36246
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:A Catastrophic Bond (CAT Bond) is a financial instrument which transfers an insurance risk caused by a natural disaster to a capital market. The prices of CAT bond premiums have changed since the 2008 financial crisis attributed to investors being risk-averse. In this Final Project, a study on a new premium principle, called a financial loss premium principle, is reproduced. In this premium principle prediction methodology, a variable which measure the loss caused by the 2008 financial crisis is added. The variable is the conditional tail expectation of the negative daily log-return of the S&P 500 index. Empirically, it could be concluded that this principle is more suitable to predict a catastrophic bond premium post the 2008 financial crisis. In this Final Project, the prediction of the expected loss of a catastrophic bond using an extreme value theory with peak-over threshold approach, is also discussed. The assumptions needed for the application of the extreme value theory are met by the peak-over threshold approach. A set of data which exceed a certain threshold may be modeled by a generalized pareto distribution or GPD( ; ) with an upper limit l. This methodology is applied to a precipitation data for Fort McMurray, Canada. It is obtained that for a threshold of u = 3; 7, the estimates of the GPD parameters are ^ = ????0:3597464 and ^ = 1:8293861 with ^l = 8:785210304. An analysis of catastrophic bond prices based on the precipitation data in 2016 using the extreme value theory approach was carried out. An extreme value theory approach may be applied to predict the expected loss of a catastrophic bond; and the catastrophic bond could be designed as such that it is attractive to the investors and the insurers.