IDEAS home Printed from https://ideas.repec.org/a/eee/insuma/v26y2000i2-3p289-307.html

Implementing adaptive nonlinear models

Author

Listed:
  • Shapiro, Arnold F.
  • Paul Gorman, R.

Abstract

No abstract is available for this item.

Suggested Citation

  • Shapiro, Arnold F. & Paul Gorman, R., 2000. "Implementing adaptive nonlinear models," Insurance: Mathematics and Economics, Elsevier, vol. 26(2-3), pages 289-307, May.
  • Handle: RePEc:eee:insuma:v:26:y:2000:i:2-3:p:289-307
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-6687(00)00036-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. repec:cup:astinb:v:20:y:1990:i:01:p:33-55_00 is not listed on IDEAS
    2. J. David Cummins & Richard Derrig, 1997. "Fuzzy Financial Pricing of Property-Liability Insurance," North American Actuarial Journal, Taylor & Francis Journals, vol. 1(4), pages 21-40.
    3. Shapiro, Arnold F., 2000. "A Hitchhiker's guide to the techniques of adaptive nonlinear models," Insurance: Mathematics and Economics, Elsevier, vol. 26(2-3), pages 119-132, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Heo, Wookjae & Lee, Jae Min & Park, Narang & Grable, John E., 2020. "Using Artificial Neural Network techniques to improve the description and prediction of household financial ratios," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    2. Sancho Salcedo-Sanz & L. Carro-Calvo & Mercè Claramunt & Anna Castañer & Maite Marmol, 2013. "An Analysis of Black-box Optimization Problems in Reinsurance: Evolutionary-based Approaches," Working Papers XREAP2013-04, Xarxa de Referència en Economia Aplicada (XREAP), revised May 2013.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shapiro, Arnold F., 2002. "The merging of neural networks, fuzzy logic, and genetic algorithms," Insurance: Mathematics and Economics, Elsevier, vol. 31(1), pages 115-131, August.
    2. Ali Azadeh & Mohammad Sheikhalishahi & Ali Boostani, 2014. "A Flexible Neuro-Fuzzy Approach for Improvement of Seasonal Housing Price Estimation in Uncertain and Non-Linear Environments," South African Journal of Economics, Economic Society of South Africa, vol. 82(4), pages 567-582, December.
    3. de Andres-Sanchez, Jorge, 2007. "Claim reserving with fuzzy regression and Taylor's geometric separation method," Insurance: Mathematics and Economics, Elsevier, vol. 40(1), pages 145-163, January.
    4. Shapiro, Arnold F., 2004. "Fuzzy logic in insurance," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 399-424, October.
    5. Lai, Li-Hua, 2008. "An evaluation of fuzzy transportation underwriting systematic risk," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(9), pages 1231-1237, November.
    6. Andreas Lindemann & Christian Dunis & Paulo Lisboa, 2005. "Probability distributions and leveraged trading strategies: an application of Gaussian mixture models to the Morgan Stanley Technology Index Tracking Fund," Quantitative Finance, Taylor & Francis Journals, vol. 5(5), pages 459-474.
    7. Andreas Karathanasopoulos, 2017. "Modelling and trading the London, New York and Frankfurt stock exchanges with a new gene expression programming trader tool," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 24(1), pages 3-11, January.
    8. Andreas Karatahansopoulos & Georgios Sermpinis & Jason Laws & Christian Dunis, 2014. "Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 596-610, December.
    9. Mingzhe Wei & Georgios Sermpinis & Charalampos Stasinakis, 2023. "Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 852-871, July.
    10. Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014. "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 21-54.
    11. Christian L Dunis & Spiros D Likothanassis & Andreas S Karathanasopoulos & Georgios S Sermpinis & Konstantinos A Theofilatos, 2013. "A hybrid genetic algorithm–support vector machine approach in the task of forecasting and trading," Journal of Asset Management, Palgrave Macmillan, vol. 14(1), pages 52-71, February.
    12. Sermpinis, Georgios & Theofilatos, Konstantinos & Karathanasopoulos, Andreas & Georgopoulos, Efstratios F. & Dunis, Christian, 2013. "Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization," European Journal of Operational Research, Elsevier, vol. 225(3), pages 528-540.
    13. Sancho Salcedo-Sanz & L. Carro-Calvo & Mercè Claramunt & Anna Castañer & Maite Marmol, 2013. "An Analysis of Black-box Optimization Problems in Reinsurance: Evolutionary-based Approaches," Working Papers XREAP2013-04, Xarxa de Referència en Economia Aplicada (XREAP), revised May 2013.
    14. Georgios Sermpinis & Andreas Karathanasopoulos & Rafael Rosillo & David Fuente, 2021. "Neural networks in financial trading," Annals of Operations Research, Springer, vol. 297(1), pages 293-308, February.
    15. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Georgios Sermpinis & Charalampos Stasinakis & Konstantinos Theofilatos & Andreas Karathanasopoul, 2014. "Inflation and Unemployment Forecasting with Genetic Support Vector Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 471-487, September.
    16. Jorge De Andrés-Sánchez, 2024. "Calculating Insurance Claim Reserves with an Intuitionistic Fuzzy Chain-Ladder Method," Mathematics, MDPI, vol. 12(6), pages 1-24, March.
    17. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    18. Charalampos Stasinakis & Georgios Sermpinis & Konstantinos Theofilatos & Andreas Karathanasopoulos, 2016. "Forecasting US Unemployment with Radial Basis Neural Networks, Kalman Filters and Support Vector Regressions," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 569-587, April.
    19. Christian Dunis & Jason Laws & Georgios Sermpinis, 2010. "Higher order and recurrent neural architectures for trading the EUR/USD exchange rate," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 615-629.
    20. Sermpinis, Georgios & Stasinakis, Charalampos & Theofilatos, Konstantinos & Karathanasopoulos, Andreas, 2015. "Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms—Support vector regression forecast combinations," European Journal of Operational Research, Elsevier, vol. 247(3), pages 831-846.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:insuma:v:26:y:2000:i:2-3:p:289-307. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505554 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.