{"product_id":"r-programming-for-actuarial-science-isbn-9781119754978","title":"R Programming for Actuarial Science","description":"\u003cb\u003eR Programming for Actuarial Science\u003c\/b\u003e \u003cp\u003e\u003cb\u003eProfessional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eR Programming for Actuarial Science \u003c\/i\u003eprovides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work. \u003c\/p\u003e\u003cp\u003eIn \u003ci\u003eR Programming for Actuarial Science\u003c\/i\u003e, readers will find: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eBasic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth.\u003c\/li\u003e \u003cli\u003eTopics covered include compound interest, statistical inference, asset-liability matching, time series, loss distributions, contingencies, mortality models, and option pricing plus many more typically covered in university courses. \u003c\/li\u003e \u003cli\u003eMore than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles.\u003c\/li\u003e \u003cli\u003eAn overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eProviding a highly useful combination of practical discussion and basic theory, \u003ci\u003eR Programming for Actuarial Science \u003c\/i\u003eis an essential reference for BSc\/MSc students in actuarial science, trainee actuaries studying privately, and qualified actuaries with little programming experience, along with undergraduate students studying finance, business, and economics. \u003c\/p\u003e\u003cp\u003eAbout the Companion Website xxi\u003c\/p\u003e \u003cp\u003eIntroduction 1\u003c\/p\u003e \u003cp\u003e1 R : What You Need to Know to Get Started 9\u003c\/p\u003e \u003cp\u003e2 Functions in R 33\u003c\/p\u003e \u003cp\u003e3 Financial Mathematics (1): Interest Rates and Valuing Cashflows 45\u003c\/p\u003e \u003cp\u003e4 Financial Mathematics (2): Miscellaneous Examples 63\u003c\/p\u003e \u003cp\u003e5 Fundamental Statistics: A Selection of Key Topics -- Dr A Kume 87\u003c\/p\u003e \u003cp\u003e6 Multivariate Distributions, and Sums of Random Variables 139\u003c\/p\u003e \u003cp\u003e7 Benefits of Diversification 147\u003c\/p\u003e \u003cp\u003e8 Modern Portfolio Theory 155\u003c\/p\u003e \u003cp\u003e9 Duration -- A Measure of Interest Rate Sensitivity 171\u003c\/p\u003e \u003cp\u003e10 Asset-Liability Matching: An Introduction 177\u003c\/p\u003e \u003cp\u003e11 Hedging: Protecting Against a Fall in Equity Markets 187\u003c\/p\u003e \u003cp\u003e12 Immunisation -- Redington and Beyond 195\u003c\/p\u003e \u003cp\u003e13 Copulas 211\u003c\/p\u003e \u003cp\u003e14 Copulas -- A Modelling Exercise 237\u003c\/p\u003e \u003cp\u003e15 Bond Portfolio Valuation: A Simple Credit Risk Model 247\u003c\/p\u003e \u003cp\u003e16 The Markov 2-State Mortality Model 259\u003c\/p\u003e \u003cp\u003e17 Approaches to Fitting Mortality Models: The Markov 2-state Model and an Introduction to Splines 273\u003c\/p\u003e \u003cp\u003e18 Assessing the Suitability of Mortality Models: Statistical Tests 295\u003c\/p\u003e \u003cp\u003e19 The Lee-Carter Model 311\u003c\/p\u003e \u003cp\u003e20 The Kaplan-Meier Estimator 329\u003c\/p\u003e \u003cp\u003e21 Cox Proportionate Hazards Regression Model 339\u003c\/p\u003e \u003cp\u003e22 Markov Multiple State Models: Applications to Life Contingencies 351\u003c\/p\u003e \u003cp\u003e23 Contingencies I 383\u003c\/p\u003e \u003cp\u003e24 Contingencies II 403\u003c\/p\u003e \u003cp\u003e25 Actuarial Risk Theory -- An Introduction: Collective and Individual Risk Models 447\u003c\/p\u003e \u003cp\u003e26 Collective Risk Models: Exercise 473\u003c\/p\u003e \u003cp\u003e27 Generalised Linear Models: Poisson Regression 481\u003c\/p\u003e \u003cp\u003e28 Extreme Value Theory 501\u003c\/p\u003e \u003cp\u003e29 Introduction to Machine Learning: k-Nearest Neighbours (kNN) 513\u003c\/p\u003e \u003cp\u003e30 Time Series Modelling in R -- Dr A Kume 523\u003c\/p\u003e \u003cp\u003e31 Volatility Models -- GARCH 551\u003c\/p\u003e \u003cp\u003e32 Modelling Future Stock Prices Using Geometric Brownian Motion: An Introduction 571\u003c\/p\u003e \u003cp\u003e33 Financial Options: Pricing, Characteristics, and Strategies 585\u003c\/p\u003e \u003cp\u003eIndex 605\u003c\/p\u003e  \u003cp\u003e\u003cb\u003ePeter McQuire\u003c\/b\u003e,\u003cb\u003e FIA,\u003c\/b\u003e is a Lecturer in Actuarial Science at the University of Kent. He has 18 years of experience in pension scheme consultancy and risk management, and more than 10 years teaching at the University. He is a Fellow of the Institute and Faculty of Actuaries. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eDr. Alfred Kume\u003c\/b\u003e is a Senior Lecturer in Statistics at the University of Kent with more than 20 years of teaching experience and exposure to general insurance.    \u003c\/p\u003e\u003cp\u003e\u003cb\u003eProfessional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eR Programming for Actuarial Science \u003c\/i\u003eprovides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work. \u003c\/p\u003e\u003cp\u003eIn \u003ci\u003eR Programming for Actuarial Science\u003c\/i\u003e, readers will find: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eBasic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth.\u003c\/li\u003e \u003cli\u003eTopics covered include compound interest, statistical inference, asset-liability matching, time series, loss distributions, contingencies, mortality models, and option pricing plus many more typically covered in university courses. \u003c\/li\u003e \u003cli\u003eMore than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles.\u003c\/li\u003e \u003cli\u003eAn overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eProviding a highly useful combination of practical discussion and basic theory, \u003ci\u003eR Programming for Actuarial Science \u003c\/i\u003eis an essential reference for BSc\/MSc students in actuarial science, trainee actuaries studying privately, and qualified actuaries with little programming experience, along with undergraduate students studying finance, business, and economics.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989902311653,"sku":"NP9781119754978","price":71.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119754978.jpg?v=1761785853","url":"https:\/\/k12savings.com\/products\/r-programming-for-actuarial-science-isbn-9781119754978","provider":"K12savings","version":"1.0","type":"link"}