The following paper discusses industry loss warranties (ILWs). The aim of this essay is to analyze basis risk with the help of Excel simulation study and to perform a risk and pricing sensitivity analysis. Furthermore, on the basis of obtained results the hedging effectiveness of ILW contracts in comparison to traditional reinsurance shall be assessed.
In company with traditional reinsurance and catastrophic bonds (cat bonds) ILWs protect buyers against natural catastrophes. The increased number of natural disasters in last years (Hurricane Katrina and Ivan in 2005, Hurricane Irene in 2011) led to lack of supply capacity in the traditional reinsurance and retrocession market. Insurers required additional capital. Therefore new and innovative catastrophic instruments – such as industry loss warranties or cat bonds – were developed (see Gatzert and Schmeiser, 2009, p.2).
These new index-linked instruments have several advantages in comparison to traditional reinsurance, e.g. reduction of moral hazard or lower underwriting costs, but a potential buyer has also to consider the drawbacks: The most important one is basis risk (see Gatzert and Kellner, 2011a, p. 132).
In the beginning this paper describes the characteristics of ILWs and discusses their pros and cons in comparison to other insurance instruments. In addition, the most common definitions of basis risk are introduced. An introduction of simulation study follows, beginning with a theoretical presentation of the approach used in the study. Subsequently, every single step as well as the formulas and the methods used are described. A following numerical analysis discusses the obtained results from the simulation study and sensitivity analysis. Lastly a conclusion is drawn, where ILWs and their hedging effectiveness on the basis of gained information are compared to the traditional reinsurance.
Table of Contents
1 Introduction
2 Characteristics of Industry Loss Warranties
2.1 Examples of an Industry Loss Warranty contract
2.2 Basis Risk
2.3 Comparison with other risk-transfer instruments
3 Simulation Study
3.1 Approach
3.1.1 Measuring basis risk
3.1.2 Premium calculation
3.1.3 Risk measurement
3.2 Numerical analysis
3.2.1 Value at risk and tail value at risk
3.2.2 Varying coefficient of correlation
3.2.3 Varying industry loss trigger
3.2.4 Varying retention
3.2.5 Varying limit of protection
4 Summary
Research Objectives and Core Topics
This paper examines the fundamental characteristics of Industry Loss Warranties (ILWs) and evaluates their hedging effectiveness compared to traditional reinsurance through a Monte Carlo simulation. The study specifically analyzes the sensitivity of basis risk and pricing to various input parameters to determine the practical suitability of these instruments for risk management.
- Analysis of ILW characteristics and comparison to traditional reinsurance.
- Investigation of basis risk as a primary drawback of index-linked instruments.
- Simulation-based quantitative comparison of binary and indemnity-based ILWs.
- Risk and pricing sensitivity analysis regarding correlation, triggers, and protection limits.
- Assessment of ILWs as a modern, flexible alternative for catastrophe risk transfer.
Excerpt from the Book
2.2 Basis Risk
As the preceding paragraphs indicate the industry loss warranties always contain a certain basis risk. Zeng (2000) defines basis risk as a “conditional probability that the ILW policy does not pay off given the actual loss sustained by the policyholder exceeds a critical level.” (Zeng, 2000, p. 27). It means that sustained losses of the insured company are severe while the industry-wide losses are not triggered, so the damage is not covered. It can occur if the policyholder’s losses and industry-wide losses are not fully correlated. (see Zeng, 2000, p. 27; World Economic Forum (WEF), 2008, p. 18-19). Basis risk means a difference between index based payoff and the company’s actual losses (see Gatzert, Schmeiser and Toplek, 2007, p. 3; WEF, p. 8). On the opposite side, the discrepancy can also lead to a basis gain (see Zeng, 2000, p. 27), i.e. the actual loss is quite small whereas the industry-wide loss is substantial and exceeds the threshold leading to pay out.
Basis risk varies on the trigger used, on the portfolio of sponsor, on the index data quality and on the specific peril (see WEF, 2008, p. 18). There are various types of triggers; some of them imply greater basis risk than others:
- An industry loss index is based on the industry-wide index of losses provided by an independent reporting agency like PCS in the US.
- An indemnity trigger depends on the actual loss of the policyholder.
- A modeled loss trigger determines the losses by entering the actual physical data into an agreed-upon model, which then calculates the losses.
- In a Modeled Industry Trigger Transaction (“MITT”) the industry index is calculated post-event using modeled loss techniques.
- A pure parametric trigger is based on the actual reported peril, e.g. earthquake magnitude or wind speed of hurricane.
- A parametric index is a refined version of a pure parametric trigger using more complicated formulas and more detailed measurements (see WEF, 2008, p. 10; SwissRe, 2009, p. 6).
Summary of Chapters
1 Introduction: This chapter outlines the research goal of analyzing basis risk and pricing sensitivity of ILWs using an Excel-based simulation study.
2 Characteristics of Industry Loss Warranties: Provides an overview of ILW types, triggers, and a comparison with other risk-transfer instruments like cat bonds and reinsurance.
3 Simulation Study: Details the methodological approach, including Monte Carlo simulation and Gaussian Copula concepts, and performs a numerical sensitivity analysis on key drivers.
4 Summary: Concludes the paper by synthesizing the findings regarding the competitive advantages and limitations of ILWs in modern risk management.
Keywords
Industry Loss Warranties, ILW, Basis Risk, Risk Transfer, Reinsurance, Monte Carlo Simulation, Gaussian Copula, Catastrophe Bonds, Indemnity Trigger, Industry Trigger, Pricing Sensitivity, Hedging Effectiveness, Value at Risk, Tail Value at Risk, Insurance-linked Securities.
Frequently Asked Questions
What is the core focus of this research paper?
The paper focuses on Industry Loss Warranties (ILWs) and specifically analyzes their potential basis risk and pricing sensitivities through simulation.
Which insurance instruments are compared in this study?
The study primarily compares Industry Loss Warranties (both binary and indemnity-based) with traditional reinsurance contracts.
What is the primary goal of the simulation conducted?
The primary goal is to perform a risk and pricing sensitivity analysis to assess the hedging effectiveness of ILWs in different catastrophe scenarios.
Which scientific methodology is applied?
The author uses a Monte Carlo simulation approach combined with the Gaussian Copula concept to generate dependent random variables for company and industry losses.
What topics are covered in the main body?
The main body covers the characteristics of ILW contracts, the definition and measurement of basis risk, and a detailed numerical analysis of how parameters like correlation and triggers impact premiums.
How are the key terms defining this work?
The work is characterized by terms such as Basis Risk, ILW, Insurance-linked Securities, and Hedging Effectiveness.
Why is the correlation coefficient considered a key driver?
The correlation coefficient is crucial because higher correlation between company and industry losses significantly reduces basis risk, making the instrument more attractive to buyers.
What happens when the industry loss trigger is increased?
Increasing the industry loss trigger leads to higher basis risk, which often makes the ILW contract less attractive to potential buyers despite potential shifts in premium pricing.
How does binary ILW differ from indemnity-based ILW regarding payouts?
Binary ILWs pay out based solely on the industry index trigger, whereas indemnity-based ILWs require both the industry trigger and the sponsor's own loss threshold to be met.
- Arbeit zitieren
- Elena Rudnikevic (Autor:in), 2012, On the Basis Risk of Industry Loss Warranties, München, GRIN Verlag, https://www.grin.com/document/190947
