INVESTMENT GUARANTEES：MODELING AND RISK MANAGEMENT FOR EQUITY-LINKED LIFE INSURANCE

A comprehensive guide to investment guarantees in equity-linked life insurance
Due to the convergence of financial and insurance markets, new forms of investment guarantees are emerging which require financial service professionals to become savvier in modeling and risk management. With chapters that discuss stock return models, dynamic hedging, risk measures, Markov Chain Monte Carlo estimation, and much more, this one-stop reference contains the valuable insights and proven techniques that will allow readers to better understand the theory and practice of investment guarantees and equity-linked insurance policies.
Mary Hardy, PhD (Waterloo, Ontario, Canada), is an Associate Professor and Associate Chair of Actuarial Science at the University of Waterloo and is a Fellow of the Institute of Actuaries and an Associate of the Society of Actuaries, where she is a frequent speaker. Her research covers topics in life insurance solvency and risk management, with particular emphasis on equity-linked insurance. Hardy is an Associate Editor of the North American Actuarial Journal and the ASTIN Bulletin and is a Deputy Editor of the British Actuarial Journal.

MARY HARDY is an Associate Professor and Associate Chair of Actuarial Science at the University of Waterloo, a Fellow of the Institute of Actuaries, and an Associate of the Society of Actuaries.

Introduction.

Investment Guarantees.

Modeling Long-Term Stock Return.

Maximum Likelihood Estimation for Stock Return Models.

The Left-Tail Calibration Method.

Markov Chain Monte Carlo (MCMC) Estimation.

Modeling the Guarantee Liability.

A Review of Option Pricing Theory.

Dynamic Hedging for Separate Account Guarantees.

Risk Measures.

Emerging Cost Analysis.

Forecast Uncertainty.

Guaranteed Annuity Options.

Equity-Indexed Annuities.

Appendix A: Mortality and Survival Probabilities.

Appendix B: The GMAB Option Price.

Appendix C: Actuarial Notation.

Appendix D: References.

Index.