R Programming for Actuarial Science

About the Companion Website xxi Introduction 1 1 R : What You Need to Know to Get Started 9 2 Functions in R 33 3 Financial Mathematics (1): Interest Rates and Valuing Cashflows 45 4 Financial Mathematics (2): Miscellaneous Examples 63 5 Fundamental Statistics: A Selection of Key Topics -- Dr A Kume 87 6 Multivariate Distributions, and Sums of Random Variables 139 7 Benefits of Diversification 147 8 Modern Portfolio Theory 155 9 Duration -- A Measure of Interest Rate Sensitivity 171 10 Asset-Liability Matching: An Introduction 177 11 Hedging: Protecting Against a Fall in Equity Markets 187 12 Immunisation -- Redington and Beyond 195 13 Copulas 211 14 Copulas -- A Modelling Exercise 237 15 Bond Portfolio Valuation: A Simple Credit Risk Model 247 16 The Markov 2-State Mortality Model 259 17 Approaches to Fitting Mortality Models: The Markov 2-state Model and an Introduction to Splines 273 18 Assessing the Suitability of Mortality Models: Statistical Tests 295 19 The Lee-Carter Model 311 20 The Kaplan-Meier Estimator 329 21 Cox Proportionate Hazards Regression Model 339 22 Markov Multiple State Models: Applications to Life Contingencies 351 23 Contingencies I 383 24 Contingencies II 403 25 Actuarial Risk Theory -- An Introduction: Collective and Individual Risk Models 447 26 Collective Risk Models: Exercise 473 27 Generalised Linear Models: Poisson Regression 481 28 Extreme Value Theory 501 29 Introduction to Machine Learning: k-Nearest Neighbours (kNN) 513 30 Time Series Modelling in R -- Dr A Kume 523 31 Volatility Models -- GARCH 551 32 Modelling Future Stock Prices Using Geometric Brownian Motion: An Introduction 571 33 Financial Options: Pricing, Characteristics, and Strategies 585 Index 605