Skip to main content
×
Home
Computation and Modelling in Insurance and Finance
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 2
  • Cited by
    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Huseby, A and Thomsen, J 2015. Safety and Reliability of Complex Engineered Systems. p. 443.

    Bølviken, Erik 2015. Wiley StatsRef: Statistics Reference Online. p. 1.

    ×
  • Export citation
  • Recommend to librarian
  • Recommend this book

    Email your librarian or administrator to recommend adding this book to your organisation's collection.

    Computation and Modelling in Insurance and Finance
    • Online ISBN: 9781139020251
    • Book DOI: https://doi.org/10.1017/CBO9781139020251
    Please enter your name
    Please enter a valid email address
    Who would you like to send this to? *
    ×
  • Buy the print book

Book description

Focusing on what actuaries need in practice, this introductory account provides readers with essential tools for handling complex problems and explains how simulation models can be created, used and re-used (with modifications) in related situations. The book begins by outlining the basic tools of modelling and simulation, including a discussion of the Monte Carlo method and its use. Part II deals with general insurance and Part III with life insurance and financial risk. Algorithms that can be implemented on any programming platform are spread throughout and a program library written in R is included. Numerous figures and experiments with R-code illustrate the text. The author's non-technical approach is ideal for graduate students, the only prerequisites being introductory courses in calculus and linear algebra, probability and statistics. The book will also be of value to actuaries and other analysts in the industry looking to update their skills.

Refine List
Actions for selected content:
Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Send to Kindle
  • Send to Dropbox
  • Send to Google Drive
  • Send content to

    To send content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to .

    To send content to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

    Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

    Find out more about the Kindle Personal Document Service.

    Please be advised that item(s) you selected are not available.
    You are about to send:
    ×

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
×
References
Abramowitz M. and Stegun I. (1965). Handbook of Mathematical Functions. New York: Dover.
Adelson R. M. (1966). Compound Poisson distributions. Operational Research Quarterly, 17, 73–75.
Ahrens J. and Dieter U. (1974). Computer methods for sampling from Gamma, Beta, Poisson and binomial distributions. Computing, 12, 223–246.
Allen M.B. and Isaacson E.L. (1998). Numerical Analysis for Applied Science. New York: John Wiley & Sons.
Antonio K. and Beirlant J. (2007). Actuarial statistics with generalized linear mixed models. Insurance: Mathematics and Economics, 40, 58–76.
Applebaum D. (2004). Lévy Processes and Stochastic Calculus. Cambridge: Cambridge University Press.
Asmussen p. and Glynn p. w. (2007). Stochastic Simulation. Algorithms and Analysis. New York: Springer-Verlag.
Asmussen s. (2000). Ruin Probabilities. Singapore: World Scientific.
Asmussen s. and Kroese D.p. (2006). Improved algorithms for rare event simulation with heavy tails. Advances in Applied Probability, 38, 545–558.
Atkinson A. C. (1979). The computer generation of poisson random variables. Applied Statistics, 28, 29–35.
Azcue P. and Muler N. (2005). Optimal reinsurance and dividend distribution policies in the Cramér-Lundberg model. Mathematical Finance, 15, 261–308.
Babbel D., Gold J. and Merrill C. B. (2002). Fair value of liabilities: The financial economics perspective. North American Actuarial Journal, 6, 12–27.
Bacro J. N. and Brito M. (1998). A tail bootstrap procedure for estimating the tail Pareto-index. Journal of Statistical Planning and Inference, 71, 245–260.
Baier C. and Katoen J.-P. (2008). Principles of Model Checking. Cambridge, MA: MIT Press.
Balakrishnan N. (2004a). Continuous multivariate distributions. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons; pp. 330–357.
Balakrishnan N. (2004b). Discrete multivariate distributions. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons; pp. 549–571.
Balakrishnan N. and Nevzorov V. B. (2003). A Primer on Statistical Distributions. Hoboken, NJ: John Wiley & Sons.
Ball C. A. and Torous W. N. (2000). Stochastic correlation across international stock markets. Journal of Empirical Finance, 7, 373–388.
Ballotta L., Esposito G. and Haberman s. (2006). The IASB insurance project for life insurance contracts: Impact on reserving methods and solvency. Insurance: Mathematics and Economics, 39, 356–375.
Barndorff-Nielsen O. (1997). Normal inverse Gaussian distributions and stochastic volatility modelling. Scandinavian Journal of Statistics, 24, 1–13.
Barndorff-Nielsen O. and Shepard N. (2004). Econometric analysis of realized covariation: High frequency based covariation, regression and correlation in financial economics. Econometrica, 72, 885–925.
Barndorff-Nielsen O. and Stelzer R. (2005). Absolute moments of generalized hyperbolic distributions and approximate scaling of normal inverse Gaussian Lévy processes. Scandinavian Journal of Statistics, 32, 617–637.
Bäuerle N. (2004). Traditional versus non-traditional reinsurance in a dynamic setting. Scandinavian Actuarial Journal, 5, 355–371.
Bäuerle N. (2005). Benchmark and mean-variance problems for insurers. Mathematical Methods of Operations Research, 62, 159–165.
Bäuerle N. and Griibel R. (2005). Multivariate counting processes. Copulas and Beyond. Astin Bulletin, 35, 379–408.
Bauwens L., Lubrano M. and Richard J.-F. (1999). Bayesian Inference in Dynamic Econometric Models. Oxford: Oxford University Press.
Beirlant J. (2004). Extremes. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons pp. 654–661.
Beirlant J. and Goegebeur Y. (2004). Local polynomial maximum likelihood estimation for pareto type distributions. Journal of Multivariate Analysis, 89, 97–118.
Beirlant J., Teugels J.L. and Vynckier P. (1996). Practical Analysis of Extreme Values. Leuven: Leuven University Press.
Beirlant J., Goegebeur Y., Segers J. and Teugels J. (2004). Statistics of Extremes: Theory and Applications. Chichester: John Wiley & Sons.
Benninga S. (2008). Financial Modelling, 3rd edn. Cambridge, MA: MIT Press.
Benth F. (2004). Option Theory with Stochastic Analysis. An Introduction to Mathematical Finance. Berlin: Springer-Verlag.
Beran J. (1994). Statistics for Long-Memory Processes. New York: Chapman & Hall.
Berkelaar A., Dert C., Oldenkamp B. and Zhang S. (2002). A primal-dual decomposition-based interior point approach to two-stage stochastic linear programming. Operations Research, 50, 904–915.
Bernardo J.M. and Smith A.F.M. (2009). Bayesian Theory. Chichester: John Wiley & Sons.
Best P. J. (1978). Letter to the Editor. Applied Statistics, 28, 181.
Bhar R., Chiarella C. and Runggaldier W. J. (2002). Estimation in models of the instantaneous short term interest rate by use of a dynamic Bayesian algorithm. In Sandmann K. and Schönbucher P. J. (eds), Advances in Finance and Stochastics. Berlin: Springer-Verlag; pp. 177–195.
Bingham N. H. and Kiesel R. (2004). Risk-neutral Valuation, Pricing and Hedging of Financial Derivatives, 2nd edn. London: Springer-Verlag.
Björk T. (2006). Arbitrage Theory in Continuous Time, 2nd edn. Oxford: Oxford University Press.
Black F. and Scholes M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81, 637–654.
Blum P. and Dacorogna M. (2004). DFA - dynamic financial analysis. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons; pp. 505–519.
Bodie Z. and Davis E. P. (eds) (2000). The Foundation of Pension Finance, Vols I and II. Cheltenham: Edward Elgar Publishing.
Boland P. J. (2007). Statistical and Probabilistic Methods in Actuarial Science. Boca Raton, F1: Chapman & Hall/CRC.
Bolia N. and Juneja S. (2005). Monte Carlo methods for pricing financial options. Sadhana, 30, 347–385.
Bollerslev T. (2001). Financial econometrics: past developments and future challenges. Journal of Econometrics, 100, 41–51.
Bølviken E. (2004) Stochastic simulation. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons; pp. 1613–1615.
Booth P., Chadburn R., Cooper D., Haberman s. and James D. (1999). Modern Actuarial Theory and Practice. London: Chapman & Hall/CRC.
Bos C. S. and Shephard N. (2006). Inference for adaptive time series models: Stochastic volatility and conditionally gaussian state space form. Econometric Reviews, 25, 219–244.
Box G. E. P. and Muller M. E. (1958). A note on the generation of random normal deviates. Annals of Mathematical Statistics, 29, 610–611.
Boyarchenko S.I. and Levendorskiῐ Z. (2002) Non-Gaussian Merton-Black-Scholes Theory. River Edge, NJ: World Scientific.
Brennan M. J. and Schwartz E. S. (1976). The pricing of equity-linked insurance policies with an asset value guarantee. Journal of Financial Economics, 3, 195–213.
Brigo D. and Mercurio F. (2001). Interest Rate Models. Theory and Practice. Berlin: Springer-Verlag.
Brito M. and Freitas A. C. M. (2006). Weak convergence of bootstrap geometric-type estimator with applications to risk theory. Insurance: Mathematics and Economics, 38, 571–584.
Brockwell P. J. and Davis R. A. (2011). Introduction to Time Series and Forecasting. New York: Springer-Verlag.
Brouhns N., Denuit M. and Van Keilegom I. (2005). Bootstrapping the Poisson log-linear model for forecasting. Scandinavian Actuarial Journal, 3, 212–224.
Biihlmann H. and Gisler A. (2005). A Course in Credibility Theory and its Applications. Berlin: Springer-Verlag.
Bühlmann H. and Straub E. (1970). Glaubwüdigkeit für Schadebsätze. Mitteleiungen der Vereinigung Scweizerischer Versicherungsmatematiker, 70, 111–133.
Buhmann M. D. (2003). Radial Basis Functions: Theory and Implementations. Cambridge: Cambridge University Press.
Butenko S., Golodnikov A. and Uryasev S. (2005). Optimal security liquidation algorithms. Computational Optimization and Applications, 32, 9–27.
Butt Z. and Haberman S. (2004). Application of frailty-based mortality models using generalized linear models. Astin Bulletin, 34, 175–197.
Cai J. and Tan K. s. (2007). Optimal retention for a stop-loss reinsurance under the VaR and CTE risk measure. Astin Bulletin, 37, 93–112.
Cairns A. (2000a). A discussion of parameter and model uncertainty in insurance. Insurance: Mathematics and Economics, 27, 313–330.
Cairns A. (2000b). Some notes on the dynamics and optimal control of stochastic pension fund models in continuous Time. Astin Bulletin, 30, 19–55.
Cairns A. (2004). Interest Rate Models: An Introduction. Princeton, NJ: Princeton University Press.
Cairns A., Blake D. and Dowd K. (2006). Pricing death: Frameworks for the valuation and securization of mortality risk. Astin Bulletin, 36, 79–120.
Cairns A., Blake D., Dowd K., Couglan G. D., Epstein D. and Khalaf-Allah M. (2011). Mortality density forecasts. An analysis of six stochastic mortality models. Insurance: Mathematics and Economics, 48, 355–367.
Capinski M. and Zastavniak T. (2003). Mathematics for Finance. An Introduction to Financial Engineering. London: Springer-Verlag.
Carlin B.P. (1992). State space modelling of nonstandard actuarial time series. Insurance: Mathematics and Economics, 11, 209–222.
Carmona R. A. (2004). Statistical Analysis of Financial Data in S-plus. New York: Springer-Verlag.
Carmona R. A. and Tehranchi M. R. (2006). Interest Rate Models. An Infinite Dimensional Stochastic Analysis Perspective. Berlin: Springer-Verlag.
Carriére J. F. (2000). Bivariate survival models for coupled lives. Scandinavian Actuarial Journal, 1, 17–32.
Casti J. (1997). Would-be World: How Simulation is Changing Frontiers of Science. New York: John Wiley & Sons.
Castillo E., Hadi A. S., Balakrishnan N. and Sarabia J.-M. (2005). Extreme Value and Related Models with Applications in Engineering and Science. Hoboken, NJ: John Wiley & Sons.
Chan N. H. and Wong H. Y. (2006). Simulation Techniques in Financial Risk Management. Hoboken, NJ: John Wiley & Sons.
Chen H. C. and Asau Y. (1974). On generating random variates from an empirical distribution. AIEE Transactions, 6, 163–166.
Chen X. and Fan Y. (2006). Estimation of copula-based semi-parametric time series models. Journal of Econometrics, 130, 307–335.
Cheng R. C. H. and Feast G. M. (1979). Some simple gamma variable generators. Applied Statistics, 28, 290–295.
Cherubini U., Luciano E. and Vecchiato W. (2004). Copula Methods in Finance. Chichester: John Wiley & Sons.
Chib s. (2004). Markov Chain Monte Carlo technology. In Gentle J.E., Härdle W. and Mori Y. (eds), Handbook of Computational Statistics. Concepts and Methods. New York: Springer-Verlag; pp. 71–102.
Chib S., Nardari F. and Shepard N. (2006). Analysis of high dimensional stochastic volatility models. Journal of Econometrics, 134, 341–371.
Chiu M. C. and Li D. (2006). Asset and liability management under a continuous-time mean-variance optimization framework. Insurance: Mathematics and Economics, 39, 330–355.
Chivers I. and Sleightholme J. (2006). Introduction to Programming with Fortran. London: Springer-Verlag.
Christof fersen R. (2003). Elements of Financial Risk Management. San Diego, CA: Academic Press.
Commandeur J.J.F. and Koopman S.J. (2007). An Introduction to State Space Time Series Analyis. Oxford: Oxford University Press.
Congdon P. (2003). Applied Bayesian Modelling. Chichester: John Wiley & Sons.
Cont R. (2006). Model uncertainty and its impact on the pricing of derivative instruments. Mathematical Finance, 16, 519–547.
Cont R. and Tankov R. (2004). Financial Modelling with Jump Processes. Boca Raton, FL: Chapman & Hall/CRC.
Cook R. D. and Weisberg S. (1982). Residuals and Influence in Regression. London: Chapman & Hall.
Copeland T. E., Weston J. F. and Shastri K. (2005). Financial Theory and Corporate Policy, 4th edn. Upper Saddle River, NJ: Prentice Hall.
Cornil J.-M. and Testud P. (2000). Introduction to Maple V. Berlin: Springer-Verlag.
Cox D. R. (1955). Some statistical methods connected with series of events. Journal of the Royal Statistical Society, Series B, 17, 129–164.
Cox J., Ingersoll J. and Ross S. (1985). A theory of the term structure of interest rates. Econometrica, 53, 385–407.
Czado C., Delwarde A. and Denuit M. (2005). Bayesian Poisson log-bilinear mortality projections. Insurance: Mathematics and Economics, 36, 260–284.
Dagpunar J. S. (1989). An easily implemented generalised inverse Gaussian generator. Communications in Statistics. Simulation and Computation, 18, 703–710.
Dagpunar J. S. (2007). Simulation and Monte Carlo with Applications in Finance and MCMC. Chichester: John Wiley & Sons.
Dahl M. (2004). Stochastic mortality in life Insurance: Market reserves and mortality-linked insurance contracts. Insurance: Mathematics and Economics, 35, 113–136.
Dana R.-A. and Jeanblanc-Picqué M. (2003). Financial Markets in Continuous Time. Berlin: Springer-Verlag.
Danthine J.-P. and Donaldson J. B. (2005). Intermediate Financial Theory. San Diego, CA: Academic Press.
Dassios A. and Jang J.-W. (2003). Pricing of catastrophe reinsurance and derivatives using the cox process with shot noise intensity. Finance and Stochastics, 7, 73–95.
Dassios A. and Jang J.-W. (2005). Kalman-Busy filtering for linear systems driven by the cox process with shot noise intensity and its Application to the pricing of reinsurance contracts. Journal of Applied Probability, 42, 93–107.
David H. A. (1981) Order Statistics, 2nd edn. New York: John Wiley & Sons.
Davison A. C. and Hinkley D. V. (1997). Bootstrap Methods and their Application. Cambridge: Cambridge University Press.
Davison A. C. and Smith R. L. (1990). Models for exceedances over high thresholds. Journal of the Royal Statistical Society, Series B, 5, 393–442.
Daykin c. D., Pentikäinen T. and Pesonen M. (1994). Practical Risk Theory for Actuaries. London: Chapman & Hall/CRC.
De Alba E. (2004). Bayesian claims reserving. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons; pp. 146–153.
De Alba E. (2006). Claims reserving when there are negative values in the run off triangle: Bayesian analysis the three-parameter log-normal distribution. North American Actuarial Journal, 10, 45–59.
Deb P., Munkin M. K. and Trivedi P. K. (2006). Private insurance, selection and health care use: A Bayesian analysis of a Roy-type model. Journal of Business & Economic Statistics, 24, 403–415.
De Haan L. and Ferreira F. (2006). Extreme Value Theory: An Introduction. New York: Springer-Verlag.
De Jong P. and Ferris S. (2006). Adverse selection spirals. Astin Bulletin, 36, 589–628.
De Jong P. and Heller G. Z. (2008). Generalized Linear Models for Insurance Data. Cambridge: Cambridge University Press.
De Jong P. and Tickle L. (2006). Extending Leesarter mortality forecasting. Mathematical Population Studies, 13, 1–18.
De Jong P. and Zehnwirth B. (1983). Credibility theory and the Kalman filter. Insurance: Mathematics and Economics, 2, 281–286.
De Lange P.E., Fleten S.-E. and Gaivorinsky A.A. (2004). Modeling financial reinsurance in the casualty insurance business via stochastic programming. Journal of Economic Dynamics and Control, 28, 991–1012.
Delbaen F. and Schachermayer W. (2006). The Mathematics of Arbitrage. Berlin: Springer-Verlag.
Denuit M. and Lang S. (2004). Non-life rate making with Bayesian GAMs. Insurance: Mathematics and Economics, 35, 627–647.
Denuit M., Maréchal x., Pitrebois S. and Wahlin J.-F. (2007). Actuarial Modelling of Claim Counts: Risk Classification, Credibility and Bonus-Malus Systems. Chichester: John Wiley & Sons.
De Santis G., Litterman B., Vesval A. and Winkelman K. (2003). Covariance matrix estimation. In Litterman B. (ed.), Modern Investment Management: An Equilibrium Approach. Hoboken, NJ: John Wiley & Sons; pp. 224–248.
Devroye L. (1986). Non-uniform Random Variate Generation. New York: Springer-Verlag.
Devroye L. and Györfi L. (1985). Nonparametric Density Estimation>: The L1 View. New York: John Wiley & Sons.
Dickson D. C. M. (2005). Insurance Risk and Ruin. Cambridge: Cambridge University Press.
Dickson D. C. M. and Waters H. (2006). Optimal dynamic reinsurance. Astin Bulletin, 36, 415–432.
Dimakos X. K. and Frigessi A. (2002). Bayesian premium rating with latent stracture. Scandinavian Actuarial Journal, 3, 162–184.
Djehiche B. and Hörfelt p. (2005). Standard approaches to asset & liability risk. Scandinavian Actuarial Journal, 5, 377–400.
Dobson A. J. and Barnett A. G. (2008). An Introduction to Generalized Linear Models, 3rd edn. Boca Raton, FL: CRC Press.
Doucet A., De Freitas N. and Gordon N. (eds) (2001). Sequential Monte Carlo in Practice. New York: Springer-Verlag.
Dunteman G. H. and Ho M.-H. R. (2006). An Introduction to Generalized Linear Models. Thousand Oaks, CA: Sage Publications.
Dupuis D. J. (1998). Exceedances over high thresholds: A guide to threshold selection. Extremes, 1, 251–261.
Durbin J. and Koopman S.J. (2001). Time Series Analysis by State Space Methods. Oxford: Oxford University Press.
Efron B. (1979). Bootstrap methods: An other look at the jacknife. Annals of Statistics, 7, 1–26.
Efron B. and Tibshirani R. J. (1993). An Introduction to the Bootstrap. New York: Chapman & Hall.
Elliott R. J. and Kopp P. E. (2005). Mathematics of Financial Markets, 2nd edn. New York: Springer-Verlag.
Ellis T.M.R., Philips I.R. and Lahey T.M. (1994). Fortran 90 Programming. Harlow: Addison-Wesley.
Embrechts P. and Maejima M. (2002). Selfsimilar Processes. Princeton, NJ: Princeton University Press.
Embrechts P., Kliippelberg C. and Mikosch T. (1997). Modelling Extremal Events for Insurance and Finance. Berlin: Springer-Verlag.
Embrechts P., Lindskog F. and Mcneil A. (2003). Modelling dependence with copulas and applications to risk management. In Rachev S. T. (ed.), Handbook of Heavy Tailed Distributions in Finance. Amsterdam: Elsevier; pp. 329–384.
England P. and Verrall R. (1999). Analytic and bootstrap estimates of prediction errors in claimreserving. Insurance: Mathematics and Economics, 25, 281–293.
England P. D. and Verrall R. J. (2006). Predictive distributions of outstanding liabilities in general insurance. Annals of Actuarial Science, 1, 221–270.
Engle R.F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation. Econometrica, 50, 987–1007.
Escarela G. and Carrière J. F. (2006). A bivariate model of claim frequencies and severities. Journal of Applied Statistics, 33, 867–883.
Evans J. R. and Olson D. L. (2002). Introduction to Simulation and Risk Analysis. Upper Saddle River, NJ: Prentice Hall.
Evans M. and Schwarz T. (2000). Approximating Integrals via Monte Carlo and Deterministic Methods. Oxford: Oxford University Press.
Fabozzi F. J. (ed.) (2002). Interest Rate, Term Structure and Valuation Modeling. Hoboken, NJ: John Wiley & Sons.
Falk M., Hiisler J. and Reiss R.-D. (2010). Laws of Small Numbers: Extremes and Rare Events. 3rd edn. Basel: Birkhauser-Verlag.
Fang K.T., Kotz S. and Ng K.w. (1990). Symmetric Multivariate and Related Distributions. London: Chapman & Hall.
Faraway J. J. (2006). Extending the Linear Model with R, generalized, mixed effects and non-parametric regression models. Boca Raton, FL: Chapman & Hall/CRC.
Feller W. (1968). An Introduction to Probability Theory and its Applications, New York: Vol. I. John Wiley & Sons.
Feller W. (1971). An Introduction to Probability Theory and its Applications, Vol. II. New York: John Wiley & Sons.
Ferguson N. (2008). The Ascent of Money. A Financial History of the World. London: Penguin Press.
Fieller E. C. and Hartley H. O. (1954). Sampling with control variables. Biometrika, 41, 494–501.
Finkelstädt B. and Rootzén H. (eds) (2004). Extreme Values in Finance, Telecommunications and the Environment. Boca Raton, FL: Chapman & Hall/CRC.
Finkelstein A. and Poterba J. (2002). Selection effects in the United Kingdom Individual annuities market. The Economic Journal, 112, 28–50.
Fishman G. S. (2001). Discrete-Event Simulation, Modeling, Programming and Analysis. New York: Springer-Verlag.
Fishman G. S. (2006). A First Course in Monte Carlo. Belmont, CA: Thomson Brooks/Cole.
Fletcher R. (1987). Practical Methods of Optimization. Chichester: John Wiley & Sons.
Fleten S.-E., Høyland K. and Wallace S. W. (2002). The performance of stochastic dynamic and fixed mix portfolios models. European Journal of Operational Research, 140, 37–39.
Fomby T. B. and Carter Hill R. (eds) (2003). Maximum Likelihood of Misspecified Models. Twenty Years Later. Amsterdam: Elsevier.
Forfar D. O. (2004). Life table. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science, Chichester: John Wiley & Sons; pp. 1005–1009.
Fornari F. and Mele A. (2000). Stochastic Volatility in Financial Markets. Crossing the Bridge to Continuous Time. Dordrecht: Kluwer.
Fouque J.-P., Papanicolaou G. and Sircar K.R. (2000). Derivatives in Financial Markets with Stochastic Volatility. Cambridge: Cambridge University Press.
Franke J., Härdle w. and Hafner C. (2004). Statistics of Financial Markets. Berlin: Springer-Verlag.
Franses p. H. and Van Dijk D. (2000). Non-linear Time Series Models in Empirical Finance. Cambridge: Cambridge University Press.
Frees E. (2003). Multivariate credibility for aggregate loss models. North American Actuarial Journal, 7, 13–37.
Frees E.W. and Valdez E.A. (1998). Understanding relationships using copulas. North American Actuarial Journal, 2, 1–25.
Frees E. and Wang P. (2006). Copula credibility for aggregate loss models. Insurance: Mathematics and Economics, 38, 360–373.
Fries C. (2007). Mathematical Finance. Theory, Modelling, Implementation. Hoboken, NJ: John Wiley & Sons.
Frigessi A., Haug O. and Rue H. (2002). A dynamic mixture model for unsupervised tail estimation without threshold selection. Extremes, 5, 219–235.
Fu M. and Hu J.-Q. (1997). Conditional Monte Carlo. Gradient Estimation and Optimization Applications. Boston, MA: Kluwer.
Fuh C.-D. (2006). Efficient likelihood estimation in state space models. Annals of Statistics, 34, 2026–2068.
Gajek L. (2005). Axiom of solvency and portfolio immunization under random interest rates. Insurance: Mathematics and Economics, 36, 317–328.
Gajek L. and Zagrodny D. (2004). Optimal reinsurance under general risk measures. Insurance: Mathematics and Economics, 34, 227–240.
Gamerman D. and Lopes H.F. (2006). Markov Chain Monte Carlo. Stochastic Simulation for Bayesian Inference. Boca Raton, FL: Chapman & Hall/CRC.
Gelb A. (ed.) (1974). Applied Optimal Estimation. Cambridge, MA: MIT Press.
Genest c. and MacKay J. (1986). Thejoy of copulas: Bivariate distributions with uniform marginals. The American Statistician, 40, 280–283.
Genon-Catalot V., Jeantheau T. and Larédo C. (2000). Stochastic volatility models as hidden markov models and statistical applications. Bernoulli, 6, 1051–1079.
Gentle J.E. (1998). Numerical Linear Algebrafor Applications in Statistics. New York: Springer-Verlag.
Gentle J.E. (2002). Elements of Computational Statistics. New York: Springer-Verlag.
Gentle J. E. (2003). Random Number Generation and Monte Carlo Methods, 2nd edn. New York: Springer-Verlag.
Gentle J.E., Härdle W. and Mori Y. (eds) (2004). Handbook of Computational Statistics. Concepts and Methods. New York: Springer-Verlag.
Gerber H.U. (1997). Life Insurance Mathematics, 3rd edn. Berlin: Springer-Verlag.
Gerber H. U. and Shiu E. S. W. (2003). Geometrie brownian motion models for assets and liabilities: From pension funding to optimal dividends. North American Actuarial Journal, 7, 37–51.
Gilks W.R., Richardson S. and Spiegelhalter D.J. (eds) (1996). Markov Chain Monte Carlo in Practice. London: Chapman & Hall.
Gill R E., Murray W. and Wright M. H. (1981). Practical Optimization. London: Academic Press.
Gisler A. (2006). The estimation error in the chain ladder reserving method: A bayesian approach. Astin Bulletin, 36, 554–565.
Glasserman p. (2004). Monte Carlo Methods in Financial Engineering. New York: Springer-Verlag.
Gloter A. (2007). Efficient estimation of drift parameters in stochastic volatility models. Finance and Stochastics, 11, 495–519.
Góméz-Déniz E., Vázquez-Polo F. and Pérez J. (2006). A note on computing bonus-malus insurance premiums using a hierarchical bayesian framework. Sociedad de Estadísticae Investigación Operativa, 15, 345–359.
Gondzio J. and Kouwenberg R. (2001). High-performance computing for asset-liability management. Operations Research, 49, 879–891.
Goovaerts M. J. and Hoogstad W. J. (1987). Credibility Theory. Surveys of Actuarial Studies, Vol. 4, Rotterdam: Nationale-Nederlanden N.V.
Grama A., Gupta A., Karypis G. and Kumar V. (2003). Introduction to Parallel Computing, 2nd edn. Harlow: Pearson/Addison-Wesley.
Grandell J. (2004). Poisson processes. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons, pp. 1296–1301.
Greenwood M. and Yule G. U. (1920). An inquiry into the nature of frequency-distributions of multiple happenings, with particular reference to the occurrence of multiple attacks of disease or repeated accidents. Journal of Royal Statistical Society, 83, 255–279.
Guerra M. and Centeno M. (2008). Optimal reinsurance policy: The adjustment coefficient and the expected utility criteria. Insurance: Mathematics and Economics, 42, 529–539.
Haberman S. and Pitacco E. (1999). Actuarial Modelsfor Disability Insurance. Boca Raton, FL: Chapman & Hall/CRC.
Haberman S. and Renshaw A. E. (1996). Generalized linear models and actuarial science. The Statistician, 45, 407–436.
Haberman S. and Sibbett T.A. (eds) (1995). History of Actuarial Science. London: Pickering and Chatto.
Hafner R. (2004). Stochastic Implied Volatility. A Factor-Based Model. Berlin: Springer-Verlag.
Hall P. (1992). The Bootstrap and Edgeworth Expansion. New York: Springer-Verlag.
Hämmerlin G. and Hof fmann K.-H. (1991). Numerical Mathematics. Berlin: Springer-Verlag.
Hammersley J. M. and Handscomb D. C. (1964). Monte Carlo Methods. London: Methuen.
Hammersley J. M. and Morton K. W. (1956). A new Monte Carlo technique: Antithetic variates. Proceedings of the Cambridge Philosophical Society, 52, 449–475.
Hanson D.R. (1997). CInterfaces and Implementations: Techniquesfor Creating Reusable Sof tware. Reading, MA: Addison-Wesley.
Harbison S. P. and Steele G. L. (2002). A Reference Manual, 5th edn. Engle-wood Cliffs, NJ: Prentice-Hall.
Hardy M. (2002). Bayesian risk management for equity-linked insurance. Scandinavian Actuarial Journal, 3, 185–211.
Hardy M. (2003). Investment Guarantees. Modeling and Risk Managementfor Equity-Linked Insurance. Hoboken, NJ: John Wiley & Sons.
Harel A. and Harpaz G. (2007). Fair actuarial values for deductible insurance policies in the presence of parameter uncertainty. International Journal of Theoretical and Applied Finance, 10, 389–397.
Harvey A., Ruiz E. and Shephard N. (1994). Multivariate stochastic variance models. Review of Economic Studies, 61, 247–264.
Harvey A., Koopman S. J. and Shephard N. (eds) (2004). State Space and Unobserved Components Models: Theory and Applications. Cambridge: Cambridge University Press.
Hastings W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97–109.
Herold U. and Maurer R. (2006). Portfolio choice and estimation risk: A comparison of bayesian to heuristic approaches. Astin Bulletin, 36, 135–160.
Hilbe J. M. (2007). Negative Binomial Regression. Cambridge: Cambridge University Press.
Hilli P., Koivu M., Pennanen T. and Ranne A. (2007). A stochastic programming model for asset liability management of a finnish pension company. Annals of Operations Research, 152, 115–139.
Hoedemakers T., Beirlant J., Goovaerts M. J. and Dhaene J. (2005). On the distribution of discounted loss reserves using generalized linear models. Scandinavian Actuarial Journal, 1, 25–45.
Højgaard B. and Taksar M. (2004). Optimal dynamic portfolio selection for a corporation with controllable risk and dividend distribution policy. Quantitative Finance, 4, 315–327.
Hörmann w., Leydold J. and Derflinger G. (2004). Automatic Non-Uniform Random Variate Generation. Berlin: Springer-Verlag.
Howison S. D., Kelly F. P. and Wilmott P. (eds) (1995). Mathematical Models in Finance. London: Chapman & Hall.
Huang X., Song L. and Liang Y. (2003). Semiparametric credibility ratemaking using a piecewise linear prior. Insurance: Mathematics and Economics, 33, 585–593.
Huber P. (1967). The behaviour of maximum likelihood estimates under nonstandard conditions. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, CA: University of California Press; pp. 221–233.
Hughston L. (ed.) (2000). The New Interest Rate Models. London: RISK Books.
Hull J. C. (2006). Options, Futures and Other Derivatives, 6th edn. Upper Saddle River, NJ: Prentice Hall, New Jersey.
Hunt B.R., Lipsman R.L. and Rosenberg J. (2001). A Guide to MATLAB:for Beginners and Experienced Users. Cambridge: Cambridge University Press.
Hiirlimann w. (2002). On immunization, stop-loss order and the maximum shiu measure. Insurance: Mathematics and Economics, 31, 315–325.
Irgens C. and Paulsen J. (2004). Optimal control of risk exposure, reinsurance and investments for insurance portfolios. Insurance: Mathematics and Economics, 35, 21–51.
Jäckel P. (2002). Monte Carlo Methods in Finance. Chichester: John Wiley & Sons.
Jacobsen M. (2006). Point Process Theory and Applications. Marked Point and Piecewise Deterministic Processes. Boston, MA: Birkhäuser.
James J. and Webber N. (2000). Interest Rate Modelling. Chichester: John Wiley & Sons.
Jensen J.L. (1995). Saddle point Approximations. New York: Oxford University Press.
Jewell W. S. (1974). Credible means are exact Bayesian for exponential families. Astin Bulletin, 8, 77–90.
Joe H. (1997). Multivariate Models and Dependence Concepts. London: Chapman & Hall.
Johnson N.L., Kotz S. and Balakrishnan N. (1994). Continuous Univariate Distributions. New York: John Wiley & Sons.
Johnson N. L., Kotz S. and Balakrishnan N. (1997). Discrete Multivariate Distributions. New York: John Wiley & Sons.
Johnson N.L., Kemp A.W. and Kotz S. (2005). Univariate Discrete Distributions, 3rd edn. Hoboken, NJ: John Wiley & Sons.
Jørgensen B. and Paes De Souza M. C. (1994). Fitting Tweedie's compound poisson model to insurance claims data. Scandinavian Actuarial Journal, 1, 69–93.
Jorion P. (2001). Value at Risk: The New Benchmark for Managing Financial Risk, 2nd edn. New York: McGraw-Hill.
Josa-Fombellida R. and Rincón-Zapatero J.P. (2006). Optimal investment decisions with a liability: The case of defined benefit pension plans. Insurance: Mathematics and Economics, 39, 81–98.
Josa-Fombellida R. and Rincón-Zapatero J. P. (2008). Mean-variance portfolio and contribution selection in stochastic pension funding. European Journal of Operational Research, 187, 120–137.
Journel A. G. and Huijbregts C. J. (1978). Mining Geostatistics. New York: Academic Press.
Kaas R.Dannenburg D. and Goovaerts M. (1997). Exact credibility for weighted observations. Astin Bulletin, 27, 287–295.
Kaluszka M. (2004). Mean-variance optimal reinsurance arrangements. Scandinavian Actuarial Journal, 1, 28–31.
Kaluszka M. (2005). Truncated stop loss as optimal reinsurance agreementin One-period Models. Astin Bulletin, 35, 337–349.
Kaminsky K. (1987). Prediction of IBNR claim counts by modeling the distribution of report lags. Insurance: Mathematics and Economics, 6, 151–159.
Kaner C., Falk J. and Ngyuen H. (1999). Testing Computer Sof tware, 2nd edn. Hoboken, NJ: John Wiley & Sons.
Karlin s. and Taylor H. M. (1975). A First Course in Stochastic Processes. New York: Academic Press.
Karlis D. and Kostaki A. (2002). Bootstrap techniques for mortality models. Bio-metrical Journal, 44, 850–866.
Karlis D. and Lillestöl J. (2004). Bayesian estimation of NIG models via Markov chain Monte Carlo methods. Applied Stochastic Models in Business and Industry, 20, 323–338.
Kendall M. G. and Stuart A. (1977). The Advanced Theory of Statistics. Volume 1. Distribution Theory, 4th edn. London: Edward Arnold.
Kendall M. G. and Stuart A. (1979). The Advanced Theory of Statistics. Volume 2. Inference and Relationship, 4th edn. London: Edward Arnold.
Keyfitz N. and Caswell H. (2005). Applied Mathematical Demography, 3rd edn. New York: Springer-Verlag.
Kijima M. (2003). Stochastic Processes with Applications to Finance. Boca Raton, FL: Chapman & Hall/CRC.
Kimberling C. H. (1974). A probabilistic interpretation of complete monotonicity. Aequationes Mathematicae, 10, 152–164.
Kinderman A. J. and Monahan J. F. (1977). Computer generation of random variables using ratio of uniform deviates. ACM Transactions of Mathematical Sof tware, 3, 257–260.
Kinderman A. J. and Monahan J. F. (1980). New methods for generating Student's t and Gamma variables. Computing, 25, 369–377.
Kleiber C. and Kotz S. (2003). Statistical Size Distributions in Economic and Actuarial Sciences. Hoboken, NJ: John Wiley & Sons.
Klugman S. A. (1992). Bayesian Statistics in Actuarial Science: with Emphasis on Credibility. Dordrecht: Kluwer.
Klugman S.A. (2004). Continuous parametric distributions. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons, pp. 357–362.
Klugman S. A. and Parsa R. (1999). Fitting bivariate loss distributions with copulas. Insurance: Mathematics and Economics, 24, 139–148.
Klugman S. A., Panjer H. H. and Willmot G. E. (2008). Loss Models: From Data to Decisions, 3rd edn. New York: John Wiley & Sons.
Knight J. and Satchell S. (eds) (2001). Return Distributions in Finance. Oxford: Butterworth-Heinemann.
Knight J. and Satchell S. (eds) (2002). Forecasting Volatility in the Financial Markets, 2nd edn. Oxford: Butterworth-Heinemann.
Koissi M.-C., Shapiro A.F. and Högnäs G. (2006). Evaluating and extending the Lee-Carter model for mortality forecasting: Bootstrap confidence interval. Insurance: Mathematics and Economics, 38, 1–20.
Kolb R. W. and Overdahl J. A. (2003). Financial Derivatives, 3rd edn. Hoboken, NJ: John Wiley & Sons.
Kontoghiorges E. J., Rustem B. and Siokos S. (eds) (2002). Computational Methods in Decision-Making, Economics and Finance. Dordrecht: Kluwer.
Kotz S. and Nadarajah S. (2000). Extreme Value Distributions: Theory and Applications. London: Imperial College Press.
Kotz S. and Nadarajah S. (2004). Multivariatet Distributions and their Applications. Cambridge: Cambridge University Press.
Kotz S., Balakrishnan N. and Johnson N.L. (2000). Continuous, Multivariate, Distributions. Volume 1. Models and Applications, 2nd edn. New York: John Wiley & Sons.
Kouwenberg R. (2001). Scenario generation and stochastic programming models for asset liability management. European Journal of Operational Research, 134, 279–292.
Krause A. and Olson M. (2005). The Basics of S-plus, 4th edn. New York: Springer-Verlag.
Krokhmal P. and Uryasev S. (2007). A sample-path approach to optimal position liquidation. Annals of Operations Research, 152, 193–225.
Krokhmal P., Uryasev S. and Palmquist J. (2002). Portfolio optimization with conditional value-at-risk objective and constraints. Journal of Risk, 4, 43–68.
Krvavych Y. and Sherris M. (2006). Enhancing reinsurer value through reinsurance optimization. Insurance: Mathematics and Economics, 38, 495–517.
Lamberton D. and Lapeyre B. (1996). Introduction to Stochastic Calculus Applied to Finance. Boca Raton, FL: Chapman & Hall/CRC.
Lancaster H. O. (1957). Some properties of the bivariate normal distribution considered in the form of a contingency table. Biometrika, 44, 289–292.
Landau R. H. (ed.) (2005). A First Course in Scientific Computing: Symbolic, Graphic, and Numerical Modeling Using Maple, Java, Mathematica and Fortran 90. Princeton, NJ: Princeton University Press.
Lange K. (1999). Numerical Analysis for Statisticians. New York: Springer-Verlag.
Lange K. (2004). Optimization. New York: Springer-Verlag.
Langtangen H. P. (2003). Computational Partial Differential Equations: Numerical Methods and Diffpack Programming, 2nd edn. Berlin: Springer-Verlag.
Lawless J.F. (1987). Negative binomial and mixed poisson regression. Canadian Journal of Statistics, 15, 209–225.
Lee R. D. and Carter L. w. (1992). Modeling and forecasting us mortality (with discussion). Journal of the American Statistical Association, 87, 659–675.
Lee J.-P. and Yu M.-T. (2007). Valuation of catastrophe reinsurance with catastrophe bonds. Insurance: Mathematics and Economics, 41, 264–278.
Lee P. J. and Wilkie A. D. (2000). A comparison of stochastic asset models. Proceedings of AFIR 2000, Tromsø, Norway.
Lee S.-Y., Poon W.-Y. and Song X.-Y. (2007). Bayesian analysis of the factor model with finance applications. Quantitative Finance, 7, 343–356.
Lee Y., Nelder J. A. and Pawitan Y. (2006). Generalized Linear Models with Random Effects: Unified Analysis via H-Likelihood. Boca Raton, FL: Chapman & Hall/CRC.
Lehmann E. and Casella G. (1998). Theory of Point Estimation, 2nd edn. New York: Springer-Verlag.
Leippold M., Trojani F. and Vanini p. (2004). A geometric approach to multi-period mean variance optimization of assets and liabilities. Journal of Economic Dynamics and Control, 28, 1079–1113.
Levy G. (2004). Computational Finance. Numerical Methodsfor Pricing Financial Instruments. Oxford: Butterworth-Heinemann.
Levy M., Levy H. and Solomon S. (2000). Microscopic Simulation of Financial Markets. From Investor Behaviour to Market Phenomena. London: Academic Press.
Liang Z. and Guo J. (2007). Optimal proportional reinsurance and ruin probability. Stochastic Models, 23, 333–350.
Lin X. S. (2006). Introductory Stochastic Analysis for Finance and Insurance. Hoboken, NJ: John Wiley & Sons.
Litterman B. (2003). Beyond Equilibrium, the Black-Litterman approach. In Litterman B. (ed.), Modern Investment Management: An Equilibrium Approach. Hoboken, NJ: John Wiley & Sons; pp. 76–88.
Liu J. S. (2001). Monte Carlo Strategies in Scientific Computing. New York: Springer-Verlag.
C.H., Fung W.K. and Zhu Z.Y. (2006). Generalized estimating equations for variance and covariance parameters in regression credibility models. Insurance: Mathematics and Economics, 39, 99–113.
Longin F. and Solnik B. (2001). Extreme correlation of international equity markets. Journal of Finance, 56, 649–676.
Luenberger D. G. (1998). Investment Science. Oxford: Oxford University, Press.
Luo Y., Young V.R and Frees E. W. (2004). Credibility ratemaking using collateral information. Scandinavian Actuarial Journal, 448–461.
Luo S., Taksar M. and Tsoi A. (2008). On reinsurance and investment for large insurance portfolios. Insurance: Mathematics and Economics, 42, 434–444.
Lütkepohl H. and Krätzig M. (eds) (2004). Applied Time Series Econometrics. Cambridge: Cambridge University Press.
Lütkepohl H. (2005). New Introduction to Multiple Time Series Analysis. Springer-Verlag, Berlin.
Lyuu Y. D. (2002). Financial Engineering and Computation. Principles, Mathematics, Algorithms. Cambridge: Cambridge University Press.
Maddala G. S. and Rao C.R. (1996). Statistical Methods in Finance, Handbook of Statistics 14. Amsterdam: Elsevier.
Makov u. (2001). Principal applications of Bayesian methods in actuarial science: A perspective. North American Actuarial Journal, 5, 53–57.
Mardia K. V., Kent J. T. and Bibby J. M. (1979). Multivariate Analysis. New York: Academic Press.
Markowitz H. (1952). Portfolio selection. Journal of Finance, 7, 77–91.
Marsaglia G.(1980). Generating random variables with a i-distribution. Mathematics of Computation, 34, 235–236.
Marshall A. and Olkin I. (1988). Families of multivariate distributions. Journal of American Statistical Association, 83, 834–841.
McCullagh P. and Nelder J. A. (1989). Generalized Linear Models, 2nd edn. London: Chapman & Hall.
McDonald R. L. (2009). Derivatives Markets. Boston, MA: Addison-Wesley.
McLeish D. L. (2005). Monte Carlo Simulation and Finance. Hoboken, NJ: John Wiley & Sons.
McMahon D. and Topa D. M. (2006). A Beginner's Guide to Mathematica. Boca Raton, FL: Chapman & Hall/CRC.
Merton R.C. (1973). Theory of rational option pricing. Bell Journal of Economics and Management Science, 4, 141–183.
Metropolis N., Rosenbluth A. W., Rosenbluth M. N., Teller A. H. and Teller E. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–1092. [Reprinted in Kotz S. and Johnson N.L. (eds) (1997). Breakthroughs in Statistics, Volume III. New York: Springer-Verlag; pp. 127-139].
Migon H. S. and Moura F. A. S. (2005). Hierarchical Bayesian collective risk model: An application to health insurance. Insurance: Mathematics and Economics, 36, 119–135.
Mikosch T. (2004). Non-Life Insurance Mathematics: An Introduction with Stochastic Processes. Berlin: Springer-Verlag.
Mikosch T. (2006). Copulas: Facts and tales. Extremes, 9, 3–20.
Mikosch T. and Stărică C. (2000). Is it really long memory we see in financial returns? In Embrechts P. (ed), Extremes and Risk Management. London: RISK Books, pp. 149–168.
Milevsky M. A. and Promislow D. (2001). Mortality derivatives and the Option to Annuitise. Insurance: Mathematics and Economics, 29, 299–318.
Mills T. C. and Markellos R. N. (2008). The Econometric Modelling of Financial Time Series, 3rd edn. Cambridge: Cambridge University Press.
Mitchell O. S. and McCarthy D. (2002). Estimating international adverse selection in annuities. North American Actuarial Journal, 6, 38–54.
Nakano J. (2004). Parallel computing techniques. In Gentle J.E., Härdle W. and Mori Y. (eds), Handbook of Computational Statistics. Concepts and Methods. New York: Springer-Verlag; pp. 237–266.
Nelsen R. B. (2006). An Introduction to Copulas, 2nd edn. New York: Springer-Verlag.
Neftci S. N. (2000). An Introduction to the Mathematics of Financial Derivatives, Second Edition. San Diego, CA: Academic Press.
Neuhaus w. (1987). Early warning. Scandinavian Actuarial Journal, 128–156.
Niederreiter H. (1992). Random Number Generation and Quasi-Monte Carlo Methods. Philadelphia, PA: SIAM.
Nietert B. (2003). Portfolio Insurance and model uncertainty. OR Spectrum, 25, 295–316.
Nordberg R. (1989). Empirical Bayes in the unbalanced case: Basic theory and applications to insurance. Doctoral Thesis, Department of Mathematics, University of Oslo.
Nordberg R. (1999). Ruin problems with assets and liabilities of Diffusion Type. Stochastic Processes and their Applications, 81, 255–269.
Nordberg R. (2004a). Credibility theory. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science, Chichester: John Wiley & Sons, pp. 398–406.
Nordberg R. (2004b). Life insurance mathematics. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science, Chichester: John Wiley & Sons, pp. 986–997.
Ntzoufras I., Katsis A. and Karlis D. (2005). Bayesian assessment of the distribution of insurance claim counts using reversible jump MCMC. North American Actuarial Journal, 9, 90–108.
Odeh R. E. and Evans J.O. (1974). Algorithm A570: The percentage points of the normal distribution. Applied Statistics, 23, 96–97.
Ohlsson E. and Johansson B. (2006). Exact credibility and Tweedie models. Astin Bulletin, 36, 121–133.
Oksendal B. (2003). Stochastic Differential Equations: An Introduction with Applications, 6th edn. Berlin: Springer-Verlag.
Omori Y., Chib S., Shephard N. and Nakajima J. (2007). Stochastic volatility with leverage: Fast and efficient likelihood inference. Journal of Econometrics, 140, 425–449.
Otto S. R. and Denier J. p. (2005). An Introduction to Programming and Numerical Methods in MATLAB. London: Springer-Verlag.
Owadally M. I. (2003). Pension funding and the actuarial assumption concerning investment returns. Astin Bulletin, 33, 289–312.
Owadally M. I. and Haberman s. (1999). Pension fund dynamics and gainsosses due to random Rates of investment returns. North American Actuarial Journal, 3, 105–117.
Panjer H. (1981). Recursive evaluation of a family of compound distributions. Astin Bulletin, 12, 22–26.
Panjer H. (ed.) (1998). Financial Economics: with Applications to Investments, Insurance and Pensions. Schaumburg, IL: The Actuarial Foundation.
Panjer H. and Willmot G. E. (1992). Insurance Risk Models. Schaumburg, IL: Society of Actuaries.
Papi M. and Sbaraglia S. (2006). Optimal asset-liability management with constraints: A dynamic programming approach. Applied Mathematics and Computation, 173, 306–349.
Pickands J. III (1975). Statistical inference using extreme order statistics. Annals of Statistics, 3, 119–131.
Pitacco E. (2004). Survival models in a dynamic context: A survey. Insurance: Mathematics and Economics, 35, 279–298.
Pitselis G. (2004). A seemingly unrelated regression model in a credibility framework. Insurance: Mathematics and Economics, 34, 37–54.
Pitselis G. (2008). Robustregression credibility. The Influence Function Approach. Insurance: Mathematics and Economics, 42, 288–300.
Pliska S. (1997). Introduction to Mathematical Finance. Discrete Time Models. Oxford: Blackwell.
Pollard J. (2004). Decrement analysis. In Teugels J. and Sundt B. (eds), Encyclopedia of Actuarial Science, Chichester: John Wiley & Sons; pp. 436–445.
Press W. H., Teukolsky S. A., Vetterling W. T. and Hannery B. P. (2007). Numerical Recipes in c, 3rd edn. Cambridge: Cambridge University Press.
Priestley M.B. (1981). Spectral Analysis and Time Series. San Diego, CA: Academic Press.
Promislow S. D. (2006). Fundamentals of Actuarial Mathematics. Chichester: John Wiley & Sons.
Purcaru O. and Denuit M. (2003). Dependence in dynamic claim frequency credibility models. Astin Bulletin, 33, 23–40.
Rachev S.T. (ed.) (2003). Handbook of Heavy Tailed Distributions in Finance. Amsterdam: Elsevier.
Rachev S. T. and Mittnik S. (2000). Stable Paretian Models in Finance, Chichester: John Wiley & Sons.
Rachev S.T., Hsu J.S.J., Bagasheva B.S. and Fabozzi F.J. (2008). Bayesian Methods in Finance. Hoboken, NJ: John Wiley & Sons.
Rebonato R. (2004). Volatility and Correlation. The Perfect Hedger and the Fox, 2nd edn. Chichester: John Wiley & Sons.
Reddington F. M. (1952). Review of the principles of life of fice valuations. Journal of the Institute of Actuaries, 78, 286–340.
Rempala G. A. and Szatzschneider K. (2004). Bootstrapping parametric models of mortality. Scandinavian Actuarial Journal, 53–78.
Renshaw A.E. and Haberman S. (2003a). Leearter mortality forecasting with age-specific enhancement. Insurance: Mathematics and Economics, 33, 255–272.
Renshaw A.E. and Haberman S. (2003b). Lee-Carter mortality forecasting: A parallel generalized linear modelling approach for england and wales mortality projections. Journal of the Royal Statistical Society, c, 52, 119–137.
Resnick S. I. (2006). Heavy-Tail Phenomena. Probabilistic and Statistical Modeling. New York: Springer-Verlag.
Ripley C. (2006). Stochastic Simulation, 2nd edn. Hoboken, NJ: John Wiley & Sons.
Robert C. R. and Casella G. (2004). Monte Carlo Statistical Methods, 2nd edn. Berlin: Springer-Verlag.
Robinson R M. (ed.) (2003). Time Series with Long Memory. Oxford: Oxford University Press.
Rockafeller R. T. and Uryasev S. (2000). Optimization of conditional value atrisk. Journal of Risk, 2, 21–41.
Rolski T., Schmidli H., Schmidt V. and Teugels J. (1999). Stochastic Processes for Insurance and Finance. Chichester: John Wiley & Sons.
Roman S. (2004). Introduction to the Mathematics of Finance. New York: Springer-Verlag.
Rose C. and Smith M. D. (2001). Mathematical Statistics with Mathematica. New York: Springer-Verlag.
Ross S. M. (2002). Simulation, 3rd edn. New York: Academic Press.
Rubinstein R.Y. and Melamed B. (1998). Modern Simulation and Modelling. New York: John Wiley & Sons.
Rudolf M. and Ziemba W. T. (2004). Intertemporal surplus management. Journal of Economic Dynamics and Control, 28, 975–990.
Ruppert D. (2004). Statistics and Finance: An Introduction. New York: Springer-Verlag.
Salleh S., Zomaya A. Y. and Bakar S. A. (2008). Computing for Numerical Methods Using Visual c++. Hoboken, NJ: John Wiley & Sons.
Savitch W. (1995). Pascal: An Introduction to the Art and Science of Programming. Redwood City, CA: Benjamin Cummings.
Sbaraglia S., Papi M., Briani M., Bernaschi M. and Gozzi F. (2003). A model for optimal asset-liability management for insurance companies. International Journal of Theoretical and Applied Finance, 6, 277–299.
Sc-Häl M. (2004). On discrete-time dynamic programming in Insurance: exponential utility and minimising the ruin probability. Scandinavian Actuarial Journal, 1, 189–210.
Schmidly H. (2006). Optimisation in non-life insurance. Stochastic Models, 22, 689–722.
Schneider D. I. (2006). An Introduction to Programming Using Visual Basic 2005. Upper Saddle River, NJ: Pearsonentice Hall.
Schnieper R. (2004). Robust Bayesian experience rating. Astin Bulletin, 34, 125–150.
Schoutens w. (2003). Lévy Processes in Finance: Pricing Financial Derivatives. Chichester: John Wiley & Sons.
Schrager D.F. (2006). Affine stochastic mortality. Insurance: Mathematics and Economics, 38, 81–97.
Schumway R. H. and Stof fer R. S. (2006). Time Series Analysis and its Applications with R Examples. New York: Springer-Verlag.
Scott R. W. (1992). Multivariate Density Estimation: Theory, Practice and Visualization, 2nd edn. New York: John Wiley & Sons.
Seydel R. (2009). Tools for Computational Finance, 2nd edn. Berlin: Springer-Verlag.
Shaw W. (1998). Modelling Financial Derivatives with Mathematica. Cambridge: Cambridge University Press.
Shephard N. (1994). Local scale models: State space alternative to integrated GARCH processes. Journal of Econometrics, 60, 181–202.
Shephard N. (ed), (2005). Stochastic Volatility. Selected Readings. Oxford: Oxford University Press.
Shreve S.E. (2004a). Stochastic Calculus for Finance I. The Binomial Asset Pricing Model. New York: Springer-Verlag.
Shreve S. E. (2004b). Stochastic Calculus for Finance II. Continuous Time Models. New York: Springer-Verlag.
Sklar A. (1959). Fonctions de répartition à n dimensions et leur marges. Publications de l'Institut de Statistique de l'Université de Paris, 8, 229–231.
Sokal R. S. and Rohlf F. J., (1981). Biometry, 2nd edn. New York: W.H. Freeman.
Stoustrup B. (2013). The c++ Programming Language, 4th edn. Reading, MA: Addison-Wesley.
Straub E. (1997). Non-life Insurance Mathematics. Berlin: Springer-Verlag.
Stuart A. (1962). Gamma-distributed products of independent random variables. Biometrika, 49, 564–565.
Stuart A. and Ord K. (1987). Kendall's Advanced Theory of Statistics. Volume 1. Distribution Theory, 5th edn. London: Edward Arnold.
Sundt B. (1979). An insurance model with collective seasonal random factors. Mitteilungen der Vereinigung Schweizericher Versicherungsmatemathematiker, 79, 57–64.
Sundt B. (1983). Parameter estimation in some credibility models. Scandinavian Actuarial Journal, 239–255.
Sundt B. (1999). An Introduction to Non-Life Insurance Mathematics. Karlsruhe: Verlag-Versicherungswirtschaft.
Sundt B. and Vernic R. (2009). Recursions for Convolutions and Compound Distributions with Insurance Applications. Berlin: Springer-Verlag.
Szabo F. E. (2004). Actuaries' Survival Guide. How to Succeed in One of the Most Desirable Prof essions. San Diego, CA: Elsevier Academic Press.
Taksar M. and Hunderup C. L. (2007). The influence of bankruptcy value on optimal risk control for diffusion models with proportional reinsurance. Insurance: Mathematics and Economics, 40, 311–321.
Tapiero C. (2004). Risk and Financial Management. Mathematical and Computational Methods. Chichester: John Wiley & Sons.
Taylor G. (2000). Loss Reserving: An Actuarial Perspective. Boston, MA: Kluwer.
Taylor G. and McGuire G. (2007). A synchronous bootstrap to account for dependencies between lines of business in the estimation of loss reserve prediction error. North American Actuarial Journal, 3, 70–88.
Taylor S. (1986). Modelling Financial Time Series. Chichester: John Wiley & Sons.
Teugels J. and Sundt B. (eds) (2004). Encyclopedia of Actuarial Science. Chichester: John Wiley & Sons.
Tsay R. (2010). Analysis of Financial Time series, 3rd edn. Hoboken, NJ: John Wiley & Sons.
Tuljapurkar s., Li N. and Boe c. (2000). A universal pattern of decline in the G7 countries. Nature, 405, 789–792.
Valdez E., Piggott J. and Wang L. (2006). Demand and adverse selection in a pooled annuity fund. Insurance: Mathematics and Economics, 39, 251–266.
Van der Hoeck J. and Elliot R. J. (2006). Binomial Models in Finance. New York: Springer-Verlag.
Vasicek O. (1977). An equilibrium characterization of the term structure. Journal of Financial Economics, 5, 177–188.
Venables w. N. and Ripley B. (2002). Modern Applied Statistics with S-plus, 4th edn. New York: Springer-Verlag.
Venables W. N. and Smith D. M. (2010). An Introduction to R. Version 2.11.1, at http://www.r-project.org.
Venter c. G. (2003). Quantifying correlated reinsurance exposures with copulas. In Casualty Actuarial Society Forum, Spring, 215–229.
Vose D. (2008). Risk Analysis. A Quantitative Guide, 3rd edn. Chichester: John Wiley & Sons.
Wand M.P. and Jones M.C. (1995). Kernel Smoothing. Boca Raton, FL: Chapman & Hall/CRC.
Wang P. (2003). Financial Econometrics: Methods and Models. London: Rout-ledge.
Wang D. and Lu P. (2005). Modelling and forecasting mortality distributions in england and wales using the Leearter model. Journal of Applied Statistics, 32, 873–885.
Wasserman L. (2006). All of Nonparametric Statistics. New York: Springer-Verlag.
West M. and Harrison J. (1997). Bayesian Forecasting and Dynamic Models, 2nd edn. New York: Springer-Verlag.
Whelan N. (2004). Sampling from Archimedean copulas. Quantitative Finance, 4, 339–352.
White H. (1982). Maximum likelihood estimation of misspecified models. Econometrica, 50, 1–25.
Wilkie A. D. (1995). More on a stochastic asset model for actuarial use (with discussion). British Actuarial Journal, 1, 777–964.
Williams C.A., Smith M.L. and Young P.C. (1998). Risk Management and Insurance, 8th edn. Boston MA: Irwin/McGraw-Hill.
Williams R. J. (2006). Introduction to the Mathematics of Finance. Providence, RI: American Mathematical Society.
Wilmoth J. R., Andreev K., Jdanov D. and Glei D. A. (2007). Methods Protocol forthe Human Mortality Database. Available at http://www.mortality.org.
Wilmott P., Howison S. and Dewynne J. (1995). The Mathematics of Financial Derivatives. Cambridge: Cambridge University Press.
Wolfram s. (2003). The Mathematica Book, 5th edn. Champaign, IL: Wolfram Media.
Wood s. N. (2006). Generalized Additive Models: An Introduction with R. Boca Raton, FL: Chapman & Hall.
Wiitrich M. V. (2004). Extreme value theory and archimedean copulas. Scandinavian Actuarial Journal, 211–228.
Wiitrich M. V. and Merz M. (2008). Stochastic Claim Reserving Methods in Insurance. Chichester: John Wiley & Sons.
Wiitrich M. V., Biihlmann H. and Furrer H. (2010). Market-Consistent Actuarial Valuation, 2nd edn. Berlin: Springer-Verlag.
Yau K., Yip K. and Yuen H.K. (2003). Modelling repeated insurance claim frequency data using the generalized linear mixed model. Journal of Applied Statistics, 30, 857–865.
Yeo K. L. and Valdez E. A. (2006). Claim dependence with common effects in credibility models. Insurance: Mathematics and Economics, 38, 609–623.
Young V. R. (2004). Premium principles. In Teugels J., and Sundt B. (eds), Encyclopedia of Actuarial Science, Chichester: John Wiley & Sons; pp. 1322–1331.
Zhang L., Mykland P. A. and Ai't-Sahalia Y. (2005). A tale of two time scales: Determining integrated volatility with noisy high-frequency data. Journal of American Statistical Association, 100, 1394–1411.
Zhang x., Zhou M. and Guo J. (2007). Optimal combination of quota-share and excess-of-loss reinurance policies in a dynamic setting: Research articles. Applied Stochastic Models in Business and Industry, 23, 63–71.
Zivot E. and Wang J. (2003). Modelling Financial Time Series with S-plus. New York: Springer-Verlag.

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 1167 *
Loading metrics...

Book summary page views

Total views: 1016 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 20th November 2017. This data will be updated every 24 hours.