Financial Modeling, Actuarial Valuation and Solvency in by Mario V. Wüthrich

By Mario V. Wüthrich

Threat administration for monetary associations is likely one of the key themes the monetary has to accommodate. the current quantity is a mathematically rigorous textual content on solvency modeling. at the moment, there are lots of new advancements during this quarter within the monetary and coverage (Basel III and Solvency II), yet none of those advancements offers a completely constant and accomplished framework for the research of solvency questions. Merz and Wüthrich mix principles from monetary arithmetic (no-arbitrage thought, identical martingale measure), actuarial sciences (insurance claims modeling, funds circulate valuation) and fiscal thought (risk aversion, chance distortion) to supply a completely constant framework. inside of this framework they then research solvency questions in incomplete markets, examine hedging dangers, and research asset-and-liability administration questions, in addition to concerns just like the restricted legal responsibility strategies, dividend to shareholder questions, the position of re-insurance, and so on. This paintings embeds the solvency dialogue (and long term liabilities) right into a clinical framework and is meant for researchers in addition to practitioners within the monetary and actuarial undefined, specifically these answerable for inner hazard administration platforms. Readers must have a great historical past in likelihood conception and facts, and will be accustomed to renowned distributions, stochastic methods, martingales, etc.

Table of Contents

Cover

Financial Modeling, Actuarial Valuation and Solvency in Insurance

ISBN 9783642313912 ISBN 9783642313929

Acknowledgements

Contents

Notation

Chapter 1 Introduction

1.1 complete stability Sheet Approach
1.2 Solvency Considerations
1.3 additional Modeling Issues
1.4 define of This Book

Part I

bankruptcy 2 country rate Deflator and Stochastic Discounting
2.1 0 Coupon Bonds and time period constitution of curiosity Rates
o 2.1.1 Motivation for Discounting
o 2.1.2 Spot charges and time period constitution of curiosity Rates
o 2.1.3 Estimating the Yield Curve
2.2 uncomplicated Discrete Time Stochastic Model
o 2.2.1 Valuation at Time 0
o 2.2.2 Interpretation of kingdom expense Deflator
o 2.2.3 Valuation at Time t>0
2.3 an identical Martingale Measure
o 2.3.1 checking account Numeraire
o 2.3.2 Martingale degree and the FTAP
2.4 industry expense of Risk
bankruptcy three Spot price Models
3.1 common Gaussian Spot fee Models
3.2 One-Factor Gaussian Affin time period constitution Models
3.3 Discrete Time One-Factor Vasicek Model
o 3.3.1 Spot price Dynamics on a each year Grid
o 3.3.2 Spot fee Dynamics on a per 30 days Grid
o 3.3.3 Parameter Calibration within the One-Factor Vasicek Model
3.4 Conditionally Heteroscedastic Spot expense Models
3.5 Auto-Regressive relocating general (ARMA) Spot fee Models
o 3.5.1 AR(1) Spot expense Model
o 3.5.2 AR(p) Spot expense Model
o 3.5.3 basic ARMA Spot fee Models
o 3.5.4 Parameter Calibration in ARMA Models
3.6 Discrete Time Multifactor Vasicek version 3.6.1 Motivation for Multifactor Spot price Models
o 3.6.2 Multifactor Vasicek version (with autonomous Factors)
o 3.6.3 Parameter Estimation and the Kalman Filter
3.7 One-Factor Gamma Spot cost Model
o 3.7.1 Gamma Affin time period constitution Model
o 3.7.2 Parameter Calibration within the Gamma Spot expense Model
3.8 Discrete Time Black-Karasinski Model
o 3.8.1 Log-Normal Spot price Dynamics
o 3.8.2 Parameter Calibration within the Black-Karasinski Model
o 3.8.3 ARMA prolonged Black-Karasinski Model
bankruptcy four Stochastic ahead fee and Yield Curve Modeling
4.1 basic Discrete Time HJM Framework
4.2 Gaussian Discrete Time HJM Framework 4.2.1 common Gaussian Discrete Time HJM Framework
o 4.2.2 Two-Factor Gaussian HJM Model
o 4.2.3 Nelson-Siegel and Svensson HJM Framework
4.3 Yield Curve Modeling 4.3.1 Derivations from the ahead expense Framework
o 4.3.2 Stochastic Yield Curve Modeling
bankruptcy five Pricing of monetary Assets
5.1 Pricing of money Flows
o 5.1.1 common funds circulate Valuation within the Vasicek Model
o 5.1.2 Defaultable Coupon Bonds
5.2 monetary Market
o 5.2.1 A Log-Normal instance within the Vasicek Model
o 5.2.2 a primary Asset-and-Liability administration Problem
5.3 Pricing of by-product Instruments

Part II

bankruptcy 6 Actuarial and monetary Modeling
6.1 monetary marketplace and monetary Filtration
6.2 uncomplicated Actuarial Model
6.3 enhanced Actuarial Model
bankruptcy 7 Valuation Portfolio
7.1 development of the Valuation Portfolio
o 7.1.1 monetary Portfolios and funds Flows
o 7.1.2 development of the VaPo
o 7.1.3 Best-Estimate Reserves
7.2 Examples
o 7.2.1 Examples in existence Insurance
o 7.2.2 instance in Non-life Insurance
7.3 Claims improvement consequence and ALM
o 7.3.1 Claims improvement Result
o 7.3.2 Hedgeable Filtration and ALM
o 7.3.3 Examples Revisited
7.4 Approximate Valuation Portfolio
bankruptcy eight safe Valuation Portfolio
8.1 development of the secure Valuation Portfolio
8.2 Market-Value Margin 8.2.1 Risk-Adjusted Reserves
o 8.2.2 Claims improvement results of Risk-Adjusted Reserves
o 8.2.3 Fortuin-Kasteleyn-Ginibre (FKG) Inequality
o 8.2.4 Examples in existence Insurance
o 8.2.5 instance in Non-life Insurance
o 8.2.6 extra chance Distortion Examples
8.3 Numerical Examples
o 8.3.1 Non-life assurance Run-Off
o 8.3.2 existence assurance Examples
bankruptcy nine Solvency
9.1 chance Measures 9.1.1 Definitio of (Conditional) danger Measures
o 9.1.2 Examples of danger Measures
9.2 Solvency and Acceptability 9.2.1 Definitio of Solvency and Acceptability
o 9.2.2 unfastened Capital and Solvency Terminology
o 9.2.3 Insolvency
9.3 No assurance Technical Risk
o 9.3.1 Theoretical ALM resolution and loose Capital
o 9.3.2 normal Asset Allocations
o 9.3.3 constrained legal responsibility Option
o 9.3.4 Margrabe Option
o 9.3.5 Hedging Margrabe Options
9.4 Inclusion of assurance Technical Risk
o 9.4.1 assurance Technical and monetary Result
o 9.4.2 Theoretical ALM resolution and Solvency
o 9.4.3 normal ALM challenge and assurance Technical Risk
o 9.4.4 Cost-of-Capital Loading and Dividend Payments
o 9.4.5 possibility Spreading and legislations of enormous Numbers
o 9.4.6 obstacles of the Vasicek monetary Model
9.5 Portfolio Optimization
o 9.5.1 ordinary Deviation dependent chance Measure
o 9.5.2 Estimation of the Covariance Matrix
bankruptcy 10 chosen issues and Examples
10.1 severe price Distributions and Copulas
10.2 Parameter Uncertainty
o 10.2.1 Parameter Uncertainty for a Non-life Run-Off
o 10.2.2 Modeling of toughness Risk
10.3 Cost-of-Capital Loading in perform 10.3.1 normal Considerations
o 10.3.2 Cost-of-Capital Loading Example
10.4 Accounting yr components in Run-Off Triangles 10.4.1 version Assumptions
o 10.4.2 Predictive Distribution
10.5 top class legal responsibility Modeling
o 10.5.1 Modeling Attritional Claims
o 10.5.2 Modeling huge Claims
o 10.5.3 Reinsurance
10.6 threat dimension and Solvency Modeling
o 10.6.1 assurance Liabilities
o 10.6.2 Asset Portfolio and top class Income
o 10.6.3 price strategy and different threat Factors
o 10.6.4 Accounting and Acceptability
o 10.6.5 Solvency Toy version in Action
10.7 Concluding Remarks

Part III

bankruptcy eleven Auxiliary Considerations
11.1 priceless effects with Gaussian Distributions
11.2 swap of Numeraire strategy 11.2.1 basic adjustments of Numeraire
o 11.2.2 ahead Measures and ecu thoughts on ZCBs
o 11.2.3 eu recommendations with Log-Normal Asset Prices

References

Index

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Example text

Theoretically, we can choose any strictly positive price process as reference unit. The choice of such a reference unit is called choice of numeraire. There is one specific numeraire which we are going to discuss and analyze in this section, the so-called bank account numeraire. 16, we obtain the discrete time bank account numeraire. Let us describe how this is done. We define the one-year risk-free returns by the continuously-compounded spot rates as def. rt = R(t, t + 1) = − log P (t, t + 1).

6). 3 Valuation at Time t > 0 In the previous subsections, we have only defined valuation at time t = 0. We now extend the valuation to any time point t ∈ J which then leads to price processes (Qt [X])t∈J for the cash flows X ∈ Lϕ . This extension should be done such that we obtain consistent or arbitrage-free price dynamics. 12 Assume a fixed state price deflator ϕ ∈ L1n+1 (Ω, F , P, F) is given. We define the price processes (Qt [X])t∈J for cash flows X ∈ Lϕ as follows: Qt [X] = 1 E ϕt ϕk Xk Ft , for t ∈ J .

Thus, on the Hilbert space of square integrable cash flows there is a one-to-one correspondence between valuation functionals Q and random vectors ϕ. The assumption of square integrability is often too restrictive for pricing insurance cash flows. Therefore, we relax this assumption which provides the following comprehensive valuation framework. 10 (State price deflator) Assume ϕ = (ϕ0 , . . , ϕn )∈L1n+1 (Ω, F , P, F) is a strictly positive random vector with normalization ϕ0 ≡ 1. Then ϕ and its components ϕk , k ∈ J , are called state price deflator (actuarial mathematics), financial pricing kernel (financial mathematics) or state price density (economic theory).

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