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Stochastic Methods for Pension Funds


Stochastic Methods for Pension Funds


1. Aufl.

von: Pierre Devolder, Jacques Janssen, Raimondo Manca

CHF 138.00

Verlag: Wiley
Format: EPUB
Veröffentl.: 04.03.2013
ISBN/EAN: 9781118566268
Sprache: englisch
Anzahl Seiten: 320

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Beschreibungen

Quantitative finance has become these last years a extraordinary field of research and interest as well from an academic point of view as for practical applications. <p>At the same time, pension issue is clearly a major economical and financial topic for the next decades in the context of the well-known longevity risk. Surprisingly few books are devoted to application of modern stochastic calculus to pension analysis.</p> <p>The aim of this book is to fill this gap and to show how recent methods of stochastic finance can be useful for to the risk management of pension funds. Methods of optimal control will be especially developed and applied to fundamental problems such as the optimal asset allocation of the fund or the cost spreading of a pension scheme.  In these various problems, financial as well as demographic risks will be addressed and modelled.</p>
<p><b>Preface xiii</b></p> <p><b>Chapter 1. Introduction: Pensions in Perspective 1</b></p> <p>1.1. Pension issues 1</p> <p>1.2. Pension scheme 7</p> <p>1.3. Pension and risks 11</p> <p>1.4. The multi-pillar philosophy 14</p> <p><b>Chapter 2. Classical Actuarial Theory of Pension Funding 15</b></p> <p>2.1. General equilibrium equation of a pension scheme 15</p> <p>2.2. General principles of funding mechanisms for DB Schemes 21</p> <p>2.3. Particular funding methods 22</p> <p><b>Chapter 3. Deterministic and Stochastic Optimal Control 31</b></p> <p>3.1. Introduction 31</p> <p>3.2. Deterministic optimal control 31</p> <p>3.3. Necessary conditions for optimality 33</p> <p>3.4. The maximum principle 42</p> <p>3.5. Extension to the one-dimensional stochastic optimal control 45</p> <p>3.6. Examples 52</p> <p><b>Chapter 4. Defined Contribution and Defined Benefit Pension Plans 55</b></p> <p>4.1. Introduction 55</p> <p>4.2. The defined benefit method 56</p> <p>4.3. The defined contribution method 57</p> <p>4.4. The notional defined contribution (NDC) method 58</p> <p>4.5. Conclusions 93</p> <p><b>Chapter 5. Fair and Market Values and Interest Rate Stochastic Models 95</b></p> <p>5.1. Fair value 95</p> <p>5.2. Market value of financial flows 96</p> <p>5.3. Yield curve 97</p> <p>5.4. Yield to maturity for a financial investment and for a bond 99</p> <p>5.5. Dynamic deterministic continuous time model for an instantaneous interest rate 100</p> <p>5.6. Stochastic continuous time dynamic model for an instantaneous interest rate 104</p> <p>5.7. Zero-coupon pricing under the assumption of no arbitrage 114</p> <p>5.8. Market evaluation of financial flows 130</p> <p>5.9. Stochastic continuous time dynamic model for asset values 132</p> <p>5.10. VaR of one asset 136</p> <p><b>Chapter 6. Risk Modeling and Solvency for Pension Funds 149</b></p> <p>6.1. Introduction 149</p> <p>6.2. Risks in defined contribution 149</p> <p>6.3. Solvency modeling for a DC pension scheme 150</p> <p>6.4. Risks in defined benefit 170</p> <p>6.5. Solvency modeling for a DB pension scheme 171</p> <p><b>Chapter 7. Optimal Control of a Defined Benefit Pension Scheme 181</b></p> <p>7.1. Introduction 181</p> <p>7.2. A first discrete time approach: stochastic amortization strategy 181</p> <p>7.3. Optimal control of a pension fund in continuous time 194</p> <p><b>Chapter 8. Optimal Control of a Defined Contribution Pension Scheme 207</b></p> <p>8.1. Introduction 207</p> <p>8.2. Stochastic optimal control of annuity contracts 208</p> <p>8.3. Stochastic optimal control of DC schemes with guarantees and under stochastic interest rates 223</p> <p><b>Chapter 9. Simulation Models 231</b></p> <p>9.1. Introduction231</p> <p>9.2. The direct method 233</p> <p>9.3. The Monte Carlo models 250</p> <p>9.4. Salary lines construction 252</p> <p><b>Chapter 10. Discrete Time Semi-Markov Processes (SMP) and Reward SMP 277</b></p> <p>10.1. Discrete time semi-Markov processes 277</p> <p>10.2. DTSMP numerical solutions 280</p> <p>10.3. Solution of DTHSMP and DTNHSMP in the transient case: a transportation example 284</p> <p>10.4. Discrete time reward processes 294</p> <p>10.5. General algorithms for DTSMRWP 304</p> <p><b>Chapter 11. Generalized Semi-Markov Non-homogeneous Models for Pension Funds and Manpower Management 307</b></p> <p>11.1. Application to pension funds evolution 307</p> <p>11.2. Generalized non-homogeneous semi-Markov model for manpower management 338</p> <p>11.3. Algorithms 347</p> <p><b>APPENDICES 359</b></p> <p>Appendix 1. Basic Probabilistic Tools for Stochastic Modeling 361</p> <p>Appendix 2. Itô Calculus and Diffusion Processes 397</p> <p><i>Bibliography 437</i></p> <p><i>Index 449</i></p>
<p><strong>Pierre De Volder</strong>, Full-time Professor, UCL; President of the Institut des Sciences Actuarielles, UCL; Member of The Royal Association of Belgian Actuaries (ARAB / KVBA). <p><strong>Jacques Janssen</strong>, Universite Libre de Bruxelles. <p><strong>Raimondo Manca</strong>, Università degli Studi di Roma La Sapienza.

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