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R Programming for Actuarial Science

Medium: Buch
ISBN: 978-1-119-75497-8
Verlag: Wiley
Erscheinungstermin: 16.10.2023
Lieferfrist: bis zu 10 Tage

R Programming for Actuarial Science

Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples

R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work.

In R Programming for Actuarial Science, readers will find: - Basic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth.
- Topics 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.

- More than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles.
- An overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic.

Providing a highly useful combination of practical discussion and basic theory, R Programming for Actuarial Science is 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.


Produkteigenschaften


  • Artikelnummer: 9781119754978
  • Medium: Buch
  • ISBN: 978-1-119-75497-8
  • Verlag: Wiley
  • Erscheinungstermin: 16.10.2023
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2023
  • Produktform: Gebunden
  • Gewicht: 1255 g
  • Seiten: 640
  • Format (B x H x T): 175 x 250 x 38 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

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