Professor Jens Perch

Professor of Actuarial Science

Bayes Business School, Faculty of Actuarial Science and Insurance

Contact

Visit Jens Perch

Room BR5058, Bunhill Row

Postal address

Bayes Business School
106 Bunhill Row
London
EC1Y 8TZ
United Kingdom

About

Overview

Actuary from Copenhagen and statistician from UC-Berkeley. Worked as appointed actuary in his young days and led various product development departments before specialising in research and development. He became research director of RSA with responsibilities in life as well as non-life in 1999. From 2006 until 2012 he worked as an entreprenuer and he is still co-owner and board member of Copenhagen based ScienceFirstand Cyprus based Emergent. He is co-author of more than 100 scientific papers in reviewed journals of actuarial science, economics, econometrics and statistics and also one book on quantitative operational risk modelling and associate editor of a number of journals.

Memberships of professional organisations

  • Associated member, Institute of Actuaries, London, Jun 2014 – present
  • Fellow, Royal Society of Statistics, London, Aug 2013 – present
  • Full qualified member. Former member of board., Danish Institute of Actuarial Science, Jan 1993 – present

Award

  • University of Copenhagen (2006) Honory Professor (Adjungated professor)

Languages

Danish.

Expertise

Primary topics

  • Risk Management
  • Actuarial Statistics
  • Annuities
  • Financial Econometrics
  • Simulation Methods
  • Portfolio Choice
  • Insurance
  • Pension Funds
  • Actuarial Science
  • Econometric & Statistical Methods
  • Statistics
  • Risk Modelling
  • Econometrics

Industries

  • financial services
  • insurance

Geographic Areas

  • Europe - Western
  • Scandinavia

Research

Three main area of research are 1) In-Sample Forecasting (developed by Cass academics and co-auhtors) 2) Defined benefit advantages adapted to defined contribution products (implementing Merton's vision) 3) Asbestos mortality forecasting (application of In-Sample Forecasting).

Research topics

In-Sample Forecasting

General forecasting for longevity and reserving as well as many biostatistical forecasting problems

Prediction of stock returns

Take advantage of state-of-the-art smoothing methods while predicting stock returns

Bandwidth selection

The fundamental problem of mathematical statistics: the variance/Bias trade off.

Estimation of outstanding liabilities.

A major non-life actuarial issue. We focus on introducing state-of-the-art methodology of mathematical statistics into this old actuarial theme.

Asbestos mortality forecasting

Application of In-Sample forecasting

Remember Defined benefits methodology when moving to defined contribution pensions

new pension products adapted to current market situation

Research students

1st supervisor

  • Stephan Bischofberger, Research Student
  • Peter Vodicka, Research Student

Alex Isakson

Attendance: Oct 2017 – Jan 2022, full-time

Thesis title: Nonparametric In-sample Forecasting Models for Biostatistics and Reserving

Role: 1st Supervisor

Peter Vodicka

Attendance: Oct 2017 – Feb 2022, full-time

Thesis title: Investment Risk Minimization and Optimization of Future Pension Plans

Role: 1st Supervisor

Parastoo Mousavi

Attendance: Oct 2017 – Mar 2022, full-time

Thesis title: Forecasting Benchmarks of Long-Term Stock Returns via Machine Learning

Role: 1st Supervisor

Stephan Bischofberger

Attendance: Oct 2016 – Sep 2020, full-time

Thesis title: New Adaptions of In-sample Forecasting for Dependent Covariates and Application in Reserving

Role: 1st Supervisor

Carolin Margraff

Attendance: May 2014 – May 2016, full-time

Thesis title: Double Chain Ladder and it's extension

Role: 1st Supervisor

Hiabu Munir

Attendance: Jul 2013 – Jul 2016, full-time

Thesis title: In-Sample Forecasting

Role: 1st Supervisor

Robert Nielsen

Attendance: Jun 2008 – Mar 2012

Thesis title: Innovation contra operations

Role: 2nd Supervisor

Martin Englund

Attendance: Jun 2007 – Oct 2010, full-time

Thesis title: Asymmetric information in non-life insurance

Role: 1st Supervisor

Anders Hedegaard Jessen

Attendance: May 2006 – Aug 2009, full-time

Thesis title: Claims reserving and other topics in non-life insurance

Role: 1st Supervisor

Jim Gustafsson

Attendance: May 2006 – May 2009, full-time

Thesis title: Statistical Modelling of Operational Risk Severity Distributions with Insurance Applications

Role: 1st Supervisor

Di Kuang

Attendance: Sep 2005 – Sep 2008, full-time

Thesis title: The chain ladder method and its extensions in forecasting reserves in general insurance.

Role: 2nd Supervisor

Tine Buch-Kromann

Attendance: Nov 2004 – Aug 2009, full-time

Thesis title: Large models for general insurance

Role: 1st Supervisor

Ana Maria Perez

Attendance: Jan 2003 – Jun 2006, full-time

Thesis title: Survival methods for the analysis of customer lifetime duration in insurance

Role: 2nd Supervisor

Peter Fledelius

Attendance: Aug 1999 – Mar 2004, part-time

Thesis title: Four Essays in Event Analysis with Applications in Finance and Insurance

Role: 2nd Supervisor

Publications

Books (2)

  1. (2020). Machine Learning in Insurance. MDPI. ISBN 978-3-03936-447-3.
  2. Bolance, C., Guillen, M., Gustafsson, J. and Nielsen, J.P. (2012). Quantitative Operational Risk Models. Chapman and Hall/CRC Finance Series. ISBN 978-1-4398-9592-4.

Chapters (6)

  1. Donnelly, C., Guillen, M. and Nielsen, J.P. (2016). Fundamentals of Cost and Risk that Matter to Pension Savers and Life Annuitants. In Mitchell, O.S. and Maurer, R. (Eds.), Retirement System Risk Management Implications of the New Regulatory Order (pp. 171–185). Oxford University Press. ISBN 978-0-19-251232-1.
  2. Donnelly, C., Guillen, M. and Nielsen, J.P. (2016). Fundamentals of Cost and Risk that Matter to Pension Savers and Life Annuitants. In Mitchell, O.S. and Maurer, R. (Eds.), Retirement System Risk Management Implications of the New Regulatory Order (pp. 171–185). Oxford University Press. ISBN 978-0-19-251232-1.
  3. Miranda, M.D.M., Nielsen, J.P. and Sperlich, S.A. (2009). One‐Sided Cross‐Validation for Density Estimation with an Application to Operational Risk. (pp. 177–195). Wiley.
  4. Bolance, C., Guillen, M. and Nielsen, J.P. (2009). Transformation Kernel Estimation of insurance cost claim distributions. In Corazza, M. and Pizzi, C. (Eds.), Mathematical and statistical methods for actuarial science and finance (pp. 223–231). Springer.
  5. Haastrup, S. and Nielsen, J.P. (1998). The historical perspective of the Danish actuarial profession. Transactions of the 26th International Congress of Actuaries (pp. 193–200).
  6. Nielsen, J.P. and Voldsgaard, P. (1996). Structured nonparametric marker dependent hazard estimation: An application to health dependent mortality. Proceedings of 27th Astin Conference in Copenhagen (pp. 634–641).

Conference papers and proceedings (15)

  1. Nielsen, J.P. (2015). The Link Between Classical Reserving and Granular Reserving Through Double Chain Ladder and its Extensions. Institute and Faculty of Actuaries Sessional Research Event 3 February, London, UK.
  2. Nielsen, , JP, , Gustafsson, , Guillen, and Bolance, (2010). Based on a series of papers. Adding prior knowledge when modelling operational risk Granada,Spain.
  3. Nielsen, , Perch, J., Gustafsson, , Guillen, and Bolance, (2010). Based on a series of papers. Adding prior knowledge when modelling operational risk London, UK.
  4. Nielsen, , Perch, J., gustafsson, , Guillen, and Bolance, (2010). Based on a series of papers. Adding prior knowledge when modelling operational risk Mannheim, Germany.
  5. Bolancé, C., Guillén, M. and Nielsen, J.P. (2010). Transformation kernel estimation of insurance claim cost distributions.
  6. Nielsen, J.P. (2009). Quantifying Operational Risk. Optimizing ERM & Economic Capital London.
  7. Nielsen, J.P. (2008). Beyond Chain Ladder in Claims Reserving. General Insurance Research Organising Committee (GIRO) Conference 2008 Italy, Sorrento.
  8. Nielsen, J.P. (2008). Improving Claims Reserving towards 2012. RSA-Oxford-Conference Nuffield College, Oxford.
  9. Nielsen, J.P. (2008). Qualitative constraints and insurance. STATISTICAL REGULARIZATION AND CONSTRANTS G�ttingen, Germany.
  10. Nielsen, J.P., Margetts, S. and Pezzulli, S. (2007). A Dynamic Approach to the understanding of incurred claims. Giro Newport.
  11. Jessen, A., Verrall, R. and Nielsen, J. (2007). Adding Counts In: A Revolution in Claims Reserving. GIRO (Conference) Newport.
  12. Margetts, S. and Nielsen, J.P. (2007). Granular Reserving � Making best use of your claims and policy data. Giro Newport.
  13. Nielsen, J.P. (2007). Towards a mathematical statistical model of claims reserving: the full cash flow approach. RSA-Oxford-Conference Nuffield College, Oxford.
  14. Nielsen, J.P. (2006). Can One Use the Same Model for Pricing, Budgeting and Reserving? GIRO Vienna, Austria.
  15. Nielsen, J.P. (2006). Reorganisation of pricing and reserving in non-life insurance. RSA-Oxford-Conference Nuffield College, Oxfrod.

Journal articles (150)

  1. Gerrard, R., Kyriakou, I., Nielsen, J.P. and Vodička, P. (2023). On optimal constrained investment strategies for long-term savers in stochastic environments and probability hedging. European Journal of Operational Research, 307(2), pp. 948–962. doi:10.1016/j.ejor.2022.10.003.

    [publisher’s website]

  2. Gámiz, M.L., Mammen, E., Martínez-Miranda, M.D. and Nielsen, J.P. (2022). Missing link survival analysis with applications to available pandemic data. Computational Statistics & Data Analysis, 169, pp. 107405–107405. doi:10.1016/j.csda.2021.107405.

    [publisher’s website]

  3. Hiabu, M., Mammen, E., Martínez-Miranda, M.D. and Nielsen, J.P. (2021). Smooth Backfitting of Proportional Hazards With Multiplicative Components. Journal of the American Statistical Association, 116(536), pp. 1983–1993. doi:10.1080/01621459.2020.1753520.

    [publisher’s website]

  4. Hiabu, M., Nielsen, J.P. and Scheike, T.H. (2021). Nonsmooth backfitting for the excess risk additive regression model with two survival time scales. Biometrika, 108(2), pp. 491–506. doi:10.1093/biomet/asaa058.

    [publisher’s website]

  5. Guillen, M., Nielsen, J.P. and Pérez‐Marín, A.M. (2021). Near‐miss telematics in motor insurance. Journal of Risk and Insurance. doi:10.1111/jori.12340.
  6. Kyriakou, I., Mousavi, P., Nielsen, J.P. and Scholz, M. (2021). Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons. Mathematics, 9(6), pp. 620–620. doi:10.3390/math9060620.

    [publisher’s website]

  7. van den Berg, G., anys, L., Mammen, E. and Perch, J. (2021). A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models. Journal of Econometrics, 221(1), pp. 43–67. doi:10.1016/j.jeconom.2019.05.025.
  8. Kyriakou, I., Mousavi, P., Nielsen, J.P. and Scholz, M. (2021). Forecasting benchmarks of long-term stock returns via machine learning. Annals of Operations Research, 297(1-2), pp. 221–240. doi:10.1007/s10479-019-03338-4.

    [publisher’s website]

  9. Mammen, E., Martínez-Miranda, M.D., Nielsen, J.P. and Vogt, M. (2021). Calendar effect and in-sample forecasting. Insurance: Mathematics and Economics, 96, pp. 31–52. doi:10.1016/j.insmatheco.2020.10.003.

    [publisher’s website]

  10. Kyriakou, I., Mousavi, P., Nielsen, J.P. and Scholz, M. (2020). Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case. Mathematics, 8(6), pp. 927–927. doi:10.3390/math8060927.

    [publisher’s website]

  11. Asimit, V., Kyriakou, I. and Nielsen, J.P. (2020). Special Issue “Machine Learning in Insurance”. Risks, 8(2), pp. 54–54. doi:10.3390/risks8020054.

    [publisher’s website]

  12. Gerrard, R., Hiabu, M., Nielsen, J.P. and Vodička, P. (2020). Long-term real dynamic investment planning. Insurance: Mathematics and Economics, 92, pp. 90–103. doi:10.1016/j.insmatheco.2020.03.002.

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  13. Guillen, M., Nielsen, J.P., Pérez-Marín, A.M. and Elpidorou, V. (2020). Can Automobile Insurance Telematics Predict the Risk of Near-Miss Events? North American Actuarial Journal, 24(1), pp. 141–152. doi:10.1080/10920277.2019.1627221.

    [publisher’s website]

  14. Lee, Y.K., Mammen, E., Nielsen, J.P. and Park, B.U. (2020). Nonparametric regression with parametric help. Electronic Journal of Statistics, 14(2). doi:10.1214/20-ejs1760.

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  15. Mammen, E., Nielsen, J.P., Scholz, M. and Sperlich, S. (2019). Conditional Variance Forecasts for Long-Term Stock Returns. Risks, 7(4), pp. 113–113. doi:10.3390/risks7040113.

    [publisher’s website]

  16. Bischofberger, S.M., Hiabu, M., Mammen, E. and Nielsen, J.P. (2019). A comparison of in-sample forecasting methods. Computational Statistics & Data Analysis, 137, pp. 133–154. doi:10.1016/j.csda.2019.02.009.

    [publisher’s website]

  17. Gerrard, R., Hiabu, M., Kyriakou, I. and Nielsen, J.P. (2019). Communication and personal selection of pension saver’s financial risk. European Journal of Operational Research, 274(3), pp. 1102–1111. doi:10.1016/j.ejor.2018.10.038.

    [publisher’s website]

  18. Guillen, M., Nielsen, J.P., Ayuso, M. and Pérez-Marín, A.M. (2019). The Use of Telematics Devices to Improve Automobile Insurance Rates. Risk Analysis, 39(3), pp. 662–672. doi:10.1111/risa.13172.

    [publisher’s website]

  19. Gámiz, M.L., Martínez-Miranda, M.D. and Nielsen, J.P. (2019). Multiplicative local linear hazard estimation and best one-sided cross-validation. Journal of Machine Learning Research, 20.
  20. Lee, Y.K., Mammen, E., Nielsen, J.P. and Park, B.U. (2019). Generalised additive dependency inflated models including aggregated covariates. Electronic Journal of Statistics, 13(1). doi:10.1214/18-ejs1515.

    [publisher’s website]

  21. Gerrard, R., Hiabu, M., Kyriakou, I. and Nielsen, J.P. (2018). Self-selection and risk sharing in a modern world of lifelong annuities-Abstract of the London Discussion. British Actuarial Journal. doi:10.1017/S1357321718000272.
  22. Ayuso, M., Guillen, M. and Nielsen, J.P. (2018). Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data. Transportation. doi:10.1007/s11116-018-9890-7.
  23. Nielsen, J.P., Bolance, C., Guillen, M. and Ayuso, M. (2018). Exposure to risk and zero accident claims in automobile insurance. Risks, 6(1). doi:10.3390/risks6010009.
  24. Donnelly, C., Guillen, M., Nielsen, J.P. and Pérez-Marín, A.M. (2018). IMPLEMENTING INDIVIDUAL SAVINGS DECISIONS FOR RETIREMENT WITH BOUNDS ON WEALTH. ASTIN Bulletin, 48(1), pp. 111–137. doi:10.1017/asb.2017.34.

    [publisher’s website]

  25. Lee, Y.K., Mammen, E., Nielsen, J.P. and Park, B.U. (2018). In-sample forecasting: A brief review and new algorithms. Latin American Journal of Probability and Mathematical Statistics, 15(2), pp. 875–875. doi:10.30757/alea.v15-33.

    [publisher’s website]

  26. Gerrard, R., Hiabu, M., Kyriakou, I. and Nielsen, J.P. (2018). Self-selection and risk sharing in a modern world of life-long annuities. British Actuarial Journal, 23. doi:10.1017/s135732171800020x.

    [publisher’s website]

  27. Bräutigam, M., Guillén, M. and Nielsen, J.P. (2017). Facing Up to Longevity with Old Actuarial Methods: A Comparison of Pooled Funds and Income Tontines. Geneva Papers on Risk and Insurance: Issues and Practice, 42(3), pp. 406–422. doi:10.1057/s41288-017-0056-1.
  28. Lee, Y.K., Mammen, E., Nielsen, J.P. and Park, B.U. (2017). Operational time and in-sample density forecasting. The Annals of Statistics, 45(3). doi:10.1214/16-aos1486.

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  29. Hiabu, M., Mammen, E., Martìnez-Miranda, M.D. and Nielsen, J.P. (2016). In-sample forecasting with local linear survival densities. Biometrika, 103(4), pp. 843–859. doi:10.1093/biomet/asw038.

    [publisher’s website]

  30. Gámiz, M.L., Mammen, E., Miranda, M.D.M. and Nielsen, J.P. (2016). Double One-sided Cross-validation of Local Linear Hazards. Journal of the Royal Statistical Society Series B: Statistical Methodology, 78(4), pp. 755–779. doi:10.1111/rssb.12133.

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  31. Martínez-Miranda, M.D., Nielsen, B. and Nielsen, J.P. (2016). Simple benchmark for mesothelioma projection for Great Britain. Occupational and Environmental Medicine, 73(8), pp. 561–563. doi:10.1136/oemed-2015-103303.

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  32. Scholz, M., Sperlich, S. and Nielsen, J.P. (2016). Nonparametric long term prediction of stock returns with generated bond yields. Insurance: Mathematics and Economics, 69, pp. 82–96. doi:10.1016/j.insmatheco.2016.04.007.

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  33. Hiabu, M., Margraf, C., Martínez-Miranda, M.D. and Nielsen, J.P. (2016). Cash flow generalisations of non-life insurance expert systems estimating outstanding liabilities. Expert Systems with Applications, 45, pp. 400–409. doi:10.1016/j.eswa.2015.09.021.

    [publisher’s website]

  34. (2016). The link between classical reserving and granular reserving through double chain ladder and its extensions ‐ Abstract of the London Discussion. British Actuarial Journal, 21(01), pp. 117–133. doi:10.1017/s1357321715000240.

    [publisher’s website]

  35. Haibu, M., Margraf, C., Miranda, M.D.M. and Nielsen, J.P. (2015). The Link Between Classical Reserving and Granular Reserving Through Double Chain Ladder and its Extensions. British Actuarial Journal, 21(1), pp. 97–116. doi:10.1017/S1357321715000288.
  36. Scholz, M., Nielsen, J.P. and Sperlich, S. (2015). Nonparametric Prediction of Stock Returns Based on Yearly Data: The Long-Term View. Insurance: Mathematics and Economics, 65(November 2015), pp. 143–155. doi:10.1016/j.insmatheco.2015.09.011.
  37. Hiabu, M., Martínez-Miranda, M.D., Nielsen, J.P., Spreeuw, J., Tanggaard, C. and Villegas, A.M. (2015). Global Polynomial Kernel Hazard Estimation. Revista Colombiana de Estadística, 38(2), pp. 399–411. doi:10.15446/rce.v38n2.51668.

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  38. Donnelly, C., Gerrard, R., Montserrat, G. and Nielsen, J.P. (2015). Less is more: increasing retirement gains by using an upside terminal wealth constraint. Insurance: Mathematics and Economics, 64(September 2015), pp. 259–267. doi:10.1016/j.insmatheco.2015.06.003.
  39. Kuang, D., Nielsen, B. and Nielsen, J.P. (2015). The geometric chain-ladder. Scandinavian Actuarial Journal, 2015(3), pp. 278–300. doi:10.1080/03461238.2013.821952.

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  40. Lee, Y.K., Mammen, E., Nielsen, J.P. and Park, B.U. (2015). Asymptotics for In-Sample Density Forecasting. Annals of Statistics, 43(2), pp. 620–651. doi:10.1214/14-AOS1288.
  41. Mammen, E., Martínez Miranda, M.D. and Nielsen, J.P. (2015). In-sample forecasting applied to reserving and mesothelioma mortality. Insurance: Mathematics and Economics, 61, pp. 76–86. doi:10.1016/j.insmatheco.2014.12.001.
  42. Donnelly, C., Englund, M., Nielsen, J.P. and Tanggaard, C. (2014). Asymmetric Information, Self-selection, and Pricing of Insurance Contracts: The Simple No-Claims Case. Journal of Risk and Insurance, 81(4), pp. 757–780. doi:10.1111/j.1539-6975.2013.01520.x.
  43. Donnelly, C., Guillén, M. and Nielsen, J.P. (2014). Bringing cost transparency to the life annuity market. Insurance: Mathematics and Economics, 56, pp. 14–27. doi:10.1016/j.insmatheco.2014.02.003.

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  44. Donnelly, C., Englund, M. and Nielsen, J.P. (2014). THE IMPORTANCE OF THE CHOICE OF TEST FOR FINDING EVIDENCE OF ASYMMETRIC INFORMATION. ASTIN Bulletin, 44(2), pp. 173–195. doi:10.1017/asb.2013.33.

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  45. Gerrard, R., Guillén, M., Nielsen, J.P. and Pérez-Marín, A.M. (2014). Long-Run Savings and Investment Strategy Optimization. The Scientific World Journal, 2014, pp. 1–13. doi:10.1155/2014/510531.

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  46. Nielsen, B. and Nielsen, J.P. (2014). Identification and Forecasting in Mortality Models. The Scientific World Journal, 2014, pp. 1–24. doi:10.1155/2014/347043.

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  47. Guillén, M., Jarner, S.F., Nielsen, J.P. and Pérez-Marín, A.M. (2014). Risk-Adjusted Impact of Administrative Costs on the Distribution of Terminal Wealth for Long-Term Investment. The Scientific World Journal, 2014, pp. 1–12. doi:10.1155/2014/521074.

    [publisher’s website]

  48. Agbeko, T., Hiabu, M., Miranda, M.D.M., Nielsen, J.P. and Verrall, R. (2014). Validating the Double Chain Ladder Stochastic Claims Reserving Model. Variance: advancing the science of risk, 8(2), pp. 138–160.
  49. Martínez Miranda, M.D., Nielsen, B. and Nielsen, J.P. (2014). Inference and forecasting in the age-period-cohort model with unknown exposure with an application to mesothelioma mortality. Journal of the Royal Statistical Society. Series A: Statistics in Society. doi:10.1111/rssa.12051.
  50. Spreeuw, J., Nielsen, J.P. and Jarner, S.F. (2013). A nonparametric visual test of mixed hazard models. SORT - Statistics and Operations Research Transactions, 37(2), pp. 153–174.
  51. Gámiz Pérez, M.L., Janys, L., Martínez Miranda, M.D. and Nielsen, J.P. (2013). Bandwidth selection in marker dependent kernel hazard estimation. Computational Statistics & Data Analysis, 68, pp. 155–169. doi:10.1016/j.csda.2013.06.010.

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  52. Guillén, M., Konicz, A.K., Nielsen, J.P. and Pérez-Marín, A.M. (2013). Do not pay for a Danish interest guarantee. The law of the triple blow. Annals of Actuarial Science, 7(2), pp. 192–209. doi:10.1017/s1748499512000176.

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  53. Nielsen, J.P. (2013). The Future of Financial Planning and Fund Distribution: Entering the Digital Age. Shorex.
  54. Martinez-Miranda, M.D., Nielsen, J.P., Verrall, R. and Wüthrich, M.V. (2013). Double chain ladder, claims development inflation and zero-claims. Scandinavian Actuarial Journal, 2015(5), pp. 383–405. doi:10.1080/03461238.2013.823459.
  55. Thuring, F., Nielsen, J.P., Guillén, M. and Bolancé, C. (2013). Segmenting and selecting cross-sale prospects using dynamic pricing. ICORES 2013 - Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems pp. 103–108.
  56. Martínez Miranda, M.D., Nielsen, J.P., Sperlich, S. and Verrall, R. (2013). Continuous Chain Ladder: Reformulating and generalizing a classical insurance problem. Expert Systems with Applications, 40(14), pp. 5588–5603. doi:10.1016/j.eswa.2013.04.006.
  57. Kaishev, V.K., Nielsen, J.P. and Thuring, F. (2013). Optimal customer selection for cross-selling of financial services products. Expert Systems with Applications, 40(5), pp. 1748–1757. doi:10.1016/j.eswa.2012.09.026.

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  58. Martínez-Miranda, M.D., Nielsen, J.P. and Verrall, R. (2013). Double Chain Ladder and Bornhuetter-Ferguson. North American Actuarial Journal, 17(2), pp. 101–113. doi:10.1080/10920277.2013.793158.
  59. Bolancé, C., Guillén, M., Gustafsson, J. and Nielsen, J.P. (2013). Adding prior knowledge to quantitative operational risk models. Journal of Operational Risk, 8(1), pp. 17–32. doi:10.21314/JOP.2013.120.
  60. Gámiz Pérez, M.L., Martínez Miranda, M.D. and Nielsen, J.P. (2013). Smoothing survival densities in practice. Computational Statistics and Data Analysis, 58(1), pp. 368–382. doi:10.1016/j.csda.2012.09.011.
  61. Donnelly, C., Guillén, M. and Nielsen, J.P. (2013). Exchanging uncertain mortality for a cost. Insurance: Mathematics and Economics, 52(1), pp. 65–76. doi:10.1016/j.insmatheco.2012.11.001.
  62. Guillen, M., Nielsen, J.P., Perez-Marin, A.M. and Petersen, K.S. (2013). Performance measurement of pension strategies: a case study of Danish life-cycle products. SCANDINAVIAN ACTUARIAL JOURNAL, 2013(1), pp. 49–68. doi:10.1080/03461238.2010.546138.
  63. Mammen, E., Martínez Miranda, M.D., Nielsen, J.P. and Sperlich, S. (2013). Further theoretical and practical insight to the do-validated bandwidth selector. Journal of the Korean Statistical Society.
  64. Nielsen, J.P., Gerrard, G. and Baden-Fuller, C. (2013). Can digital technology bring quality financial advice to the masses? .
  65. Guillén, M., Perch Nielsen, J., Pérez-Marín, A.M. and Petersen, K.S. (2012). Performance measurement of pension strategies: a case study of Danish life cycle products. Scandinavian Actuarial Journal, 2012(4), pp. 258–277. doi:10.1080/03461238.2010.537835.

    [publisher’s website]

  66. Thuring, F., Nielsen, J.P., Guillén, M. and Bolancé, C. (2012). Selecting prospects for cross-selling financial products using multivariate credibility. Expert Systems with Applications, 39(10), pp. 8809–8816. doi:10.1016/j.eswa.2012.02.011.
  67. Miranda, M.D.M., Nielsen, J.P. and Verrall, R. (2012). Double chain ladder. ASTIN Bulletin, 42(1), pp. 59–76. doi:10.2143/AST.42.1.216071.
  68. Martínez-Miranda, M.D., Nielsen, J.P. and Wüthrich, M.V. (2012). Statistical modelling and forecasting of outstanding liabilities in non-life insurance. SORT, 36(2), pp. 195–218.
  69. Buch-Kromann, T. and Nielsen, J.P. (2012). Multivariate density estimation using dimension reducing information and tail flattening transformations for truncated or censored data. Annals of the Institute of Statistical Mathematics, 64(1), pp. 167–192. doi:10.1007/s10463-010-0313-6.
  70. Nielsen, J.P., Bolance, C., Guillen, M. and Gustafsson, J. (2012). Quantitative modeling of operational risk losses when combining internal and external data sources. Capco Journal of Financial Transformation, 35(4), pp. 179–185.
  71. Mammen, E., Nielsen, J.P. and Fitzenberger, B. (2011). Generalized linear time series regression. Biometrika, 98(4), pp. 1007–1014. doi:10.1093/biomet/asr044.
  72. Kuang, D., Nielsen, B. and Perch Nielsen, J. (2011). Forecasting in an Extended Chain-Ladder-Type Model. Journal of Risk and Insurance, 78(2), pp. 345–359. doi:10.1111/j.1539-6975.2010.01395.x.

    [publisher’s website]

  73. Mammen, E., Miranda, M.D.M., Nielsen, J.P. and Sperlich, S. (2011). Do-validation for Kernel density estimation. Journal of the American Statistical Association, 106(494), pp. 651–660. doi:10.1198/jasa.2011.tm08687.
  74. Linton, O., Mammen, E., Nielsen, J.P. and Van Keilegom, I. (2011). Nonparametric regression with filtered data. Bernoulli, 17(1), pp. 60–87. doi:10.3150/10-BEJ260.
  75. Buch-Kromann, T., Guillén, M., Linton, O. and Nielsen, J.P. (2011). Multivariate density estimation using dimension reducing information and tail flattening transformations. Insurance: Mathematics and Economics, 48(1), pp. 99–110. doi:10.1016/j.insmatheco.2010.10.002.
  76. Martinez Miranda, M.D., Nielsen, B., Nielsen, J.P. and Verrall, R. (2011). Cash flow simulation for a model of outstanding liabilities based on claim amounts and claim numbers. Astin Bulletin, 41, pp. 107–129. doi:10.2143/AST.41.1.2084388.
  77. Guillén, M., Nielsen, J.P., Scheike, T.H. and Pérez-Marín, A.M. (2011). Time-varying effects in the analysis of customer loyalty: A case study in insurance. Expert Systems with Applications.
  78. Buch Kromann, T. and Nielsen, J.P. (2011). Multivariate density estimation using dimension reducing information and tail flattening transformations for truncated and censored data. Annals of the Institute of Mathematical Statistics, 53, pp. 730–745.
  79. Buch Kromann, T., Guillen, M., Linton, O. and Nielsen, J.P. (2011). Multivariate density estimation using dimension reducing information and tail flattening transformations. Insurance: Mathematics and Economics, 48, pp. 99–110.
  80. Verrall, R., Nielsen, J.P. and Jessen, A.H. (2010). Prediction of RBNS and IBNR claims using claim amounts and claim counts. ASTIN Bulletin, 40(2), pp. 871–887. doi:10.2143/AST.40.2.2061139.
  81. Buch-Kromann, T. and Nielsen, J.P. (2010). Multivariate density estimation using dimension reducing information and tail flattening transformations for truncated or censored data. Annals of the Institute of Statistical Mathematics pp. 1–26.
  82. Nielsen, J.P., Poulsen, R. and Mumford, P. (2010). Capital Allocation for Insurance Companies: Issues and Methods. Belgian Actuarial Bulletin, 9(1), p. 1.
  83. Gustafsson, J., Hagmann, M., Nielsen, J.P. and Scaillet, O. (2009). Local transformation kernel density estimation of loss distributions. Journal of Business and Economic Statistics, 27(2), pp. 161–175. doi:10.1198/jbes.2009.0011.
  84. Linton, O., Nielsen, J.P. and Nielsen, S.F. (2009). Non-parametric regression with a latent time series. Econometrics Journal, 12(2), pp. 187–207. doi:10.1111/j.1368-423X.2009.00278.x.
  85. Englund, M., Gustafsson, J., Nielsen, J.P. and Thuring, F. (2009). Multidimensional credibility with time effects: An application to commercial business lines. Journal of Risk and Insurance, 76(2), pp. 443–453. doi:10.1111/j.1539-6975.2009.01306.x.
  86. Nielsen, J.P., Tanggaard, C. and Jones, M.C. (2009). Local linear density estimation for filtered survival data, with bias correction. Statistics, 43(2), pp. 167–186. doi:10.1080/02331880701736648.
  87. Kuang, D., Nielsen, B. and Nielsen, J.P. (2009). Chain-Ladder as Maximum Likelihood Revisited. Annals of Actuarial Science, 4(1), pp. 105–121. doi:10.1017/s1748499500000610.

    [publisher’s website]

  88. Guillen, M., Nielsen, J.P. and Perez-Marin, A.M. (2009). Compra cruzada y fidelidad del cliente en el sector asegurador. Esic Market, 132, pp. 107–136.
  89. Guillen, M., Nielsen, J.P. and Perez-Marin, A.M. (2009). Cross-buying behaviour and customer loyalty in the insurance sector. Esic Market, 132(January - April), pp. 77–105.
  90. Nielsen, J.P., Tanggaard, C. and Jones, C. (2009). Local linear density estimation for filtered survival data, with bias correction. Statistics, 43(2), pp. 167–186. doi:10.1080/02331880701736648.
  91. Gustafsson, J., Hagmann, M., Nielsen, J.P. and Scaillet, O. (2009). Transformation Kernel Density Estimation of Loss Distributions. Journal of Business and Economic Statistics, 27, p. 15.
  92. Guillen, M., Gustafsson, J. and Perch Nielsen, J. (2008). Combining underreported internal and external data for operational risk measurement. The Journal of Operational Risk, 3(4), pp. 3–24. doi:10.21314/jop.2008.050.

    [publisher’s website]

  93. Kuang, D., Nielsen, B. and Nielsen, J.P. (2008). Identification of the age-period-cohort model and the extended chain-ladder model. Biometrika, 95(4), pp. 979–986. doi:10.1093/biomet/asn026.
  94. Kuang, D., Nielsen, B. and Nielsen, J.P. (2008). Forecasting with the age-period-cohort model and the extended chain-ladder model. Biometrika, 95(4), pp. 987–991. doi:10.1093/biomet/asn038.
  95. Bolancé, C., Guillén, M. and Nielsen, J.P. (2008). Inverse beta transformation in kernel density estimation. Statistics and Probability Letters, 78(13), pp. 1757–1764. doi:10.1016/j.spl.2008.01.028.
  96. Guillén, M., Høgh, N., Nielsen, J.P. and Pérez-Marín, A.M. (2008). Froot and Stein Revisited Once Again. Annals of Actuarial Science, 3(1-2), pp. 121–126. doi:10.1017/s1748499500000488.

    [publisher’s website]

  97. Brockett, P.L., Golden, L.L., Guillen, M., Nielsen, J.P., Parner, J. and Perez-Marin, A.M. (2008). Survival Analysis of a Household Portfolio of Insurance Policies: How Much Time Do You Have to Stop Total Customer Defection? Journal of Risk & Insurance, 75(3), pp. 713–737. doi:10.1111/j.1539-6975.2008.00281.x.

    [publisher’s website]

  98. Englund, M., Guillén, M., Gustafsson, J., Nielsen, L.H. and Nielsen, J.P. (2008). Multivariate latent risk: A credibility approach. ASTIN Bulletin, 38(1), pp. 137–146. doi:10.2143/AST.38.1.2030406.
  99. Englund, M., Guillén, M., Gustafsson, J., Nielsen, L.H. and Nielsen, J.P. (2008). Multivariate Latent Risk: A Credibility Approach. ASTIN Bulletin, 38(01), pp. 137–146. doi:10.2143/ast.38.1.2030406.

    [publisher’s website]

  100. Guillen, M., Nielsen, J.P. and Pérez-Marín, A.M. (2008). The need to monitor customer loyalty and business risk in the European insurance industry. Geneva Papers on Risk and Insurance: Issues and Practice, 33(2), pp. 207–218. doi:10.1057/gpp.2008.1.
  101. Gustafsson, J. and Nielsen, J.P. (2008). A Mixing Model for Operational Risk. Journal of Operational Risk, 3(3), pp. 25–37. doi:10.21314/JOP.2008.049.
  102. Guillen, M., Jim Gustafsson, J.P.N. and Nielsen, J. (2008). Combining under-reported Internal and External Data For Operational Risk Measurement. Journal of Operational Risk, 3, p. 22.
  103. Brockett, P.L., Golden, L., Guillen, M., Nielsen, J.P., Parner, J. and Perez Marin, A.M. (2008). Household multiple policy retention effects of first policy cancellation: How much time do you have to stop total customer defection? Journal of Risk and Insurance, 75, pp. 713–737.
  104. Mammen, E. and Nielsen, J.P. (2007). A general approach to the predictability issue in survival analysis with applications. Biometrika, 94(4), pp. 873–892. doi:10.1093/biomet/asm062.
  105. Buch-Kromann, T., Englund, M., Gustafsson, J., Perch Nielsen, J. and Thuring, F. (2007). Non-parametric estimation of operational risk losses adjusted for under-reporting. Scandinavian Actuarial Journal, 2007(4), pp. 293–304. doi:10.1080/03461230701642471.

    [publisher’s website]

  106. Guillen, M., Gustafsson, J., Nielsen, J.P. and Pritchard, P. (2007). Using External Data in Operational Risk. The Geneva Papers on Risk and Insurance Issues and Practice, 32(2), pp. 178–189.
  107. Mammen, , Enno, and Nielsen, J.P. (2007). A general approach to the predictability issue in survival analyses. Biometrika, 94(4), pp. 873–892.
  108. Guillen, M., Nielsen, J.P. and Perez-Marin, A.M. (2007). Improving the efficiency of the Nelson-Aalen estimator: the naive local constant estimator. Scandinavian Journal of Statistics, 34, pp. 419–431.
  109. Guillen, M., Nielsen, J.P. and Perez-Marin, A.M. (2006). Multiplicative Hazard Models for Studying the Evolution of Mortality. Annals of Actuarial Science, 1(1), pp. 165–177. doi:10.1017/s1748499500000099.

    [publisher’s website]

  110. Høgh, N., Linton, O. and Nielsen, J.P. (2006). The Froot-Stein Model Revisited. Annals of Actuarial Science, 1(1), pp. 37–47. doi:10.1017/s174849950000004x.

    [publisher’s website]

  111. Gustafsson, J., Perch Nielsen, J., Pritchard, P. and Roberts, D. (2006). Quantifying operational risk guided by kernel smoothing and continuous credibility: A practitioner's view. The Journal of Operational Risk, 1(1), pp. 43–55. doi:10.21314/jop.2006.005.

    [publisher’s website]

  112. Guillen, M., Nielsen, J.P. and Perez-Marin, A. (2006). La gestion seguradora bajo el enfoque del multicontrado. Revista Espana de Seguros, 127(JUL-SEP), pp. 529–539.
  113. Gustafsson, J., Nielsen, J.P., Pritchard, P. and Roberts, D. (2006). Quantifying Operational Risk Guided by Kernel Smoothing and Continuous Credibility. Journal of Finance Risk Management, 3(2), pp. 23–47.
  114. Guillen, M., Nielsen, J.P. and Pérez-Marín, A. (2006). La duración de distintos contratos de seguros en los hogares. Un enfoque integrado. Gerencia de Riesgos y Seguros, 96(4), pp. 23–32.
  115. Guillen, M., Jorgensen, J.P.N. and Nielsen, J. (2006). Return smoothing mechanisms in life and pension insurance: Path dependent contingent claims. Insurance: Mathematics and Economics, 38(2), pp. 229–258. doi:10.1016/j.insmatheco.2005.06.014.
  116. Buch-larsen, T., Nielsen, J.P., Guillén, M. and Bolancé, C. (2005). Kernel density estimation for heavy-tailed distributions using the champernowne transformation. Statistics, 39(6), pp. 503–516. doi:10.1080/02331880500439782.

    [publisher’s website]

  117. Nielsen, J.P. and Sandqvist, B.L. (2005). Proportional Hazard Estimation Adjusted by Continuous Credibility. ASTIN Bulletin, 35(1), pp. 239–258. doi:10.1017/s0515036100014148.

    [publisher’s website]

  118. Nielsen, J.P. and Sperlich, S. (2005). Smooth backfitting in practice. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67(1), pp. 43–61. doi:10.1111/j.1467-9868.2005.00487.x.

    [publisher’s website]

  119. Fledelius, P., Guillen, M., Nielsen, J.P. and Petersen, K.S. (2004). A comparative study of parametric and nonparametric estimators of old-age mortality in Sweden. Journal of Actuarial Practice, 11, pp. 103–128.
  120. Fledelius, P., Lando, D. and Nielsen, J.P. (2004). Nonparametric analyses of rating transitions and default data. Journal of Investment Management (JOIM), 2(2), pp. 71–85.
  121. Fledelius, P., Guillen, M., Nielsen, J.P. and Vogelius, M. (2004). Two-dimensional hazard estimation for longevity analyses. Scandinavian Actuarial Journal, 2, pp. 133–156. doi:10.1080/034612301101016516.
  122. Nielsen, J.P. and Sperlich, S. (2003). Prediction of Stock Returns: A New Way to Look at It. ASTIN Bulletin, 33(2), pp. 399–417. doi:10.1017/s0515036100013532.

    [publisher’s website]

  123. Nielsen, J.P. (2003). Variable bandwidth kernel hazard estimators. Journal of Nonparametric Statistics, 15(3), pp. 355–376. doi:10.1080/1048525031000120260.

    [publisher’s website]

  124. Linton, O., Nielsen, J.P. and Geer, S.V.D. (2003). Estimating multiplicative and additive marker dependent hazard functions by backfitting with the assistance of marginal integration. Annals of Statistics, 23(2), pp. 464–492.
  125. Nielsen, J.P. (2003). Smoothing and Prediction with a View to Actuarial Science, Biostatistics and Finance. Scandinavian Actuarial Journal, 2003(1), pp. 51–74. doi:10.1080/03461230308484.

    [publisher’s website]

  126. Bolancé, C., Guillen, M. and Nielsen, J.P. (2003). Kernel density estimation of actuarial loss functions. Insurance: Mathematics and Economics, 32(1), pp. 19–36. doi:10.1016/s0167-6687(02)00191-9.

    [publisher’s website]

  127. Bolance, C., Guillen, M. and Nielsen, J.P. (2003). Kernel estimation of actuarial loss functions. Insurance: Mathematics and Economics, 28, pp. 191–204.
  128. Mammen, , Enno, and Nielsen, J.P. (2003). Generalised Structured Models. Biometrika, 90(3), pp. 551–566.
  129. Nielsen, J.P. and Tanggaard, C. (2001). Boundary and Bias Correction in Kernel Hazard Estimation. Scandinavian Journal of Statistics, 28(4), pp. 675–698. doi:10.1111/1467-9469.00262.

    [publisher’s website]

  130. Linton, O., Mammen, E., Nielsen, J.P. and Tanggaard, C. (2001). Yield curve estimation by kernel smoothing methods. Journal of Econometrics, 105(1), pp. 185–223. doi:10.1016/s0304-4076(01)00075-6.

    [publisher’s website]

  131. Felipe, A., Guillen, M. and Nielsen, J.P. (2001). Longevity studies based on kernel hazard estimation. Insurance: Mathematics and Economics, 28(2), pp. 191–204. doi:10.1016/s0167-6687(00)00076-7.

    [publisher’s website]

  132. Nielsen, J.P. and Tanggaard, C. (2001). Simple boundary and bias correction in kernel density estimation. Scandinavian Journal of Statistics, 28, pp. 695–724.
  133. Nielsen, J.P. and Sandqvist, B.L. (2000). Credibility Weighted Hazard Estimation. ASTIN Bulletin, 30(2), pp. 405–417. doi:10.2143/ast.30.2.504643.

    [publisher’s website]

  134. Nielsen, J.P. (2000). Super-Efficient Prediction Based on High-Quality Marker Information. ASTIN Bulletin, 30(2), pp. 295–303. doi:10.2143/ast.30.2.504636.

    [publisher’s website]

  135. Yang, L., Hardle, W. and Nielsen, J. (1999). Nonparametric Autoregression with Multiplicative Volatility and Additive mean. Journal of Time Series Analysis, 20(5), pp. 579–604. doi:10.1111/1467-9892.00159.

    [publisher’s website]

  136. Nielsen, J. (1999). Super-efficient hazard estimation based on high-quality marker information. Biometrika, 86(1), pp. 227–232. doi:10.1093/biomet/86.1.227.

    [publisher’s website]

  137. Nielsen, J.P. (1999). Multivariate kernels from local linear estimation. Scandinavian Actuarial Journal, 1, pp. 93–95. doi:10.1080/03461230050131902.
  138. Nielsen, J.P. (1999). Super-efficient kernel hazard estimation based on high quality markers. Biometrika, 86, pp. 227–232.
  139. Mammen, E., Linton, O. and Nielsen, J.P. (1999). The existence and asymptotic properties of a backfitting algorithm under weak conditions. Annals of Statistics, 27, pp. 1443–1490.
  140. Nielsen, J.P. (1998). Marker dependent kernel hazard estimation from local linear estimation. Scandinavian Actuarial Journal, 1998(2), pp. 113–124. doi:10.1080/03461238.1998.10413997.

    [publisher’s website]

  141. Linton, , Oliver, and Nielsen, J.P. (1998). An optimization interpretation of integration and backfitting estimators for seperable nonparametric models. Journal of Royal Statistical Society, Series B, 60, pp. 217–222.
  142. Nielsen, J.P. (1998). Multiplicative bias correction in kernel hazard estimation. Scandinavian Journal of Statistics, 25, pp. 541–553.
  143. Nielsen, J.P., Linton, O. and Bickel, P. (1998). On a semiparametric survival model with flexible covariate effect. Annals of Statistics, 26(1), pp. 215–241.
  144. LINTON, O. and NIELSEN, J.P. (1995). A kernel method of estimating structured nonparametric regression based on marginal integration. Biometrika, 82(1), pp. 93–100. doi:10.1093/biomet/82.1.93.

    [publisher’s website]

  145. Nielsen, J.P. and Linton, O. (1995). Kernel Estimation in a Nonparametric Marker Dependent Hazard Model. Annals of Statistics, 23(5), pp. 1735–1748.
  146. JONES, M.C., LINTON, O. and NIELSEN, J.P. (1995). A simple bias reduction method for density estimation. Biometrika, 82(2), pp. 327–338. doi:10.1093/biomet/82.2.327.

    [publisher’s website]

  147. Linton, , Oliver, and Nielsen, J.P. (1994). A multiplicative bias reduction method for nonpametric regression. Statistics and Probability Letters, 19, pp. 181–187.
  148. Fusaro, R.E., Nielsen, J.P. and Scheike, T.H. (1993). Marker-dependent hazard estimation: An application to AIDS. Statistics in Medicine, 12(9), pp. 843–865. doi:10.1002/sim.4780120905.

    [publisher’s website]

  149. JEWELL, N.P. and NIELSEN, J.P. (1993). A framework for consistent prediction rules based on markers. Biometrika, 80(1), pp. 153–164. doi:10.1093/biomet/80.1.153.

    [publisher’s website]

  150. Malani, H., Nielsen, J.P. and Readfearn, B. (1993). A note on the asymptotic variance of a survival function in the semi-Markov model. Statistics and Probability Letters, 18, pp. 19–25.

Scholarly editions (12)

  1. van den Berg, G.J., Janys, L., Mammen, E. and Nielsen, J.P. (2021). A general semiparametric approach to inference with marker-dependent hazard rate models.
  2. van den Berg, G.J., Janys, L., Mammen, E. and Nielsen, J.P. (2016). A general semiparametric approach to inference with marker-dependent
    hazard rate models.
  3. Scholz, M., Nielsen, J.P. and Sperlich, S. (2012). Nonparametric prediction of stock returns guided by prior knowledge.
  4. Hansen, L.H., Nielsen, B. and Nielsen, J.P. (2004). Two sided analysis of variance with a latent time series.
  5. Nielsen, J.P., Tanggaard, C. and Jones, M.C. (2003). Local Linear Density Estimation for Filtered Survival Data, with
    Bias Correction.
  6. Linton, O., Nielsen, J.P. and Geer, S.V.D. Estimating Multiplicative and Additive Hazard Functions by Kernel Methods.
  7. Guillen, M., Nielsen, J.P. and Bolance, C. ESTIMATION OF ACTUARIAL LOSS FUNCTIONS AND THE TAIL INDEX USING TRANSFORMATIONS IN KERNEL DENSITY ESTIMATION.
  8. Guillen, M., Nielsen, J.P., Scheike, T. and Perez-Marin, A.M. Time-varying effects when analysing customer lifetime duration, application to the insurance market.
  9. Gustafsson, J., Hagmann, M., Nielsen, J.P. and Scaillet, O. Local Transformation Kernel Density Estimation of Loss Distributions.
  10. Ayuso, M., Guillln, M. and Nielsen, J.P. Improving Automobile Insurance Ratemaking Using Telematics: Incorporating Mileage and Driver Behaviour Data.
  11. Guillen, M., Pérez-Marín, A., Ayuso, M. and Nielsen, J.P. “Exposure to risk increases the excess of zero accident claims frequency in automobile insurance”.
  12. Kyriakou, I., Mousavi, P., Nielsen, J.P. and Scholz, M. Choice of Benchmark When Forecasting Long-term Stock Returns.

Professional activities

Editorial activity (23)

  1. Journal of Digital Finance, Associate Editor, 2015 – present.
  2. PlosOne, Referee, 2015 – present.
  3. Risk, Referee, 2015 – present.
  4. European Journal of Operational Research, Referee, 2014 – present.
  5. Insurance: Mathematics and Economics, Referee, 2013 – present.
  6. Journal of Econometrics, Referee, 2013 – present.
  7. Journal of Time Series, Referee, 2013 – present.
  8. Geneva Papers, Referee, 2012 – present.
  9. Astin Bulletin, Referee, 2011 – present.
  10. Annals of Actuarial Science, Referee, 2010 – present.
  11. Statistics and Probability Letters, Referee, 2009.
  12. Annals of Institute of Mathematical Statistics, Referee, 2009 – present.
  13. Canadian Journal of Statistics, Referee, 2009 – present.
  14. Econometrika, Referee, 2004 – 2006.
  15. Journal of Econometrics, Referee, 2004.
  16. Statistics, Referee, 2003 – 2009.
  17. Biometrical Journal, Referee, 2002.
  18. Journal of Royal Statistical Society Series B, Referee, 2000 – 2006.
  19. Biometrika, Referee, 2000 – present.
  20. JASA, Referee, 2000 – present.
  21. Annals of Statistics, Referee, 1995 – present.
  22. Scandinavian Actuarial Journal, Referee, 1995 – present.
  23. Scandinavian Journal of Statistics, Referee, 1995 – present.

Events/conferences (37)

  1. (Almost all Danish non-life actuaries in the room. About 75). Astin day for Danish non-life insurers. (Seminar) KPMG conference room Copenhagen Denmark (2016). Invited speaker.
    Paper: Double Chain Ladder and its extensions
    Author: Nielsen J.P.
  2. (256 actuaries in the room). Institute of Actuaries: ACA Sessional Meeting. (Seminar) St Ermin’s Hotel, Caxton Street, London SW1 UK (2016). Invited speaker.
    Paper: Minimising longevity and investment risk while optimising future pension plans
    Author: Nielsen J.P.
  3. (156 actuaries in the room). 2016 Seminar - Institute of Actuaries: CILA Meeting. (Seminar) 30 Euston Square in London UK (2016). Invited speaker.
    Paper: Minimising longevity and investment risk while optimising future pension plans
    Author: Nielsen J.P.
  4. Sessional meeting Institute of Actuaries. (Public lecture) London (2015). Invited speaker.
    Paper: The Link Between Classical Reserving and Granular Reserving Through Double Chain Ladder and its Extensions
    Author: Nielsen J.P.
  5. Oxford-Cass conference on reserving. (Conference) (2015). Invited speaker.
    Paper: Double Chain Ladder and it's extensions
    Author: Nielsen J.P.
  6. Enno Mammen's 60 years birthday on structural nonparametric statistics. (Conference) (2015). Invited speaker.
    Paper: In-Sample Forecasting
    Author: Nielsen J.P.
  7. The Cyprus Institute of Actuaries. (Seminar) Cyprus (2014).
    Paper: Double Chain Ladder and it's extensions
    Author: Nielsen J.P.
  8. IME conference Copenhagen. (Conference) (2014). Invited speaker.
    Paper: Continuous Chain Ladder
    Author: Nielsen J.P.
  9. GIRO. (Conference) (2014). Invited speaker.
    Paper: Double Chain Ladder and it's extensions
    Author: Nielsen J.P.
  10. Cass Consulting public lecture. (Public lecture) London (2013). Invited speaker.
    Paper: Don't throw the baby out with the bathwater: on granular reserving.
    Author: Nielsen J.P
    Co-authors: Martinez-Miranda, Sperlich, Verrall
  11. Can digital technology bring quality financial advice to the masses? (Public lecture) Cass Business School (2013). Invited speaker.
    Paper: Can digital technology bring quality financial advice to the masses?
    Author: Nielsen J.P
  12. Yearly meeting in Newcastle, Royal Statistical Society. (Conference) Newcastle (2013). Invited speaker.
    Paper: A comparative study of new cross-validated bandwidth selectors for kernel density estimation
    Author: Nielsen J.P
    Co-authors: Mammen, Martinez-Miranda, Sperlich
  13. IME conference. (Conference) Copenhagen (2013). Invited speaker.
    Paper: Continuous Chain Ladder
    Author: Nielsen J.P
    Co-authors: Martinez-Miranda, Sperlich, Verrall
  14. GIRO. (Conference) Edinburgh (2013). Invited speaker.
    Paper: Don't throw the baby out with the bathwater: going granular respecting classical chain ladder.
    Author: Martinez-Miranda M
    Co-authors: Nielsen, J.P.
  15. ETF&Indexing Investments. Strategy and Opportunity for ETF investors, managers, issuers and their partners. (Conference) ETC Venues, St. Pauls, London, UK (2013). Invited speaker.
    Paper: Are ETFs becoming less transparent with innovation? Are we overcomplicating ETFs natural simplicity?
    Author: Nielsen J.P.
  16. ETF&Indexing Investments. Strategy and Opportunity for ETF investors, managers, issuers and their partners. (Conference) ETC Venues, St. Pauls, London, UK (2013). Invited speaker.
    Paper: Will the next big innovations perform as well as actively managed ETFs?
    Author: Nielsen J.P
  17. ETF&Indexing Investments. Strategy and Opportunity for ETF investors, managers, issuers and their partners. (Conference) ETC Venues, St. Pauls, London, UK (2013). Invited speaker.
    Paper: Analysing the risks of ETF proliferation: Do providers need to take a step backwards when it comes to new product launches and cross launches?
    Author: Nielsen J.P
  18. Seminar Granada doctoral program. (Seminar) Granada (2012). Invited speaker.
    Paper: Smooth Densities in Practise
    Author: Nielsen J.P
  19. Econometricians meet Biostatisticians: Survival Analysis. (Workshop) Mannheim (2012).
    Paper: Smooth Densities in Practise
    Author: Gámiz Pérez M.L
    Co-authors: Martínez Miranda, M.D., Nielsen, J.P
  20. Tower perrin. (Conference) London (2012). Invited speaker.
    Paper: Transparency and excess returns in the Scandinavian ETF market
    Author: Nielsen J.P
  21. Inside ETFs Europe: Building better portfolios with ETFs. (Conference) Amsterdam (2012). Invited speaker.
    Paper: How to increase your income with ETFs
    Author: Nielsen J.P
  22. GIRO. (Conference) Brussel, Belgium (2012). Invited speaker.
    Paper: Quantitative Operational Risk Models: A new monograph from Chapman and Hall.
    Author: Bolance C
    Co-authors: Guillen, M., Gustafsson, J. and Nielsen, J.P.
  23. Giro 2012. (Conference) Brussel, Belgium (2012). Invited speaker.
    Paper: Adding prior knowledge to double chain ladder
    Author: Martinez-Miranda M.D
    Co-authors: and Nielsen, J.P
  24. GIRO. (Conference) Liverpool (2011). Invited speaker.
    Paper: Double Chain Ladder with a touch of Bornhutter-Ferguson.
    Author: Nielsen J.P
    Co-authors: Roberts, D
  25. Adding prior knowledge when modelling operational risk. (Seminar) London, UK (2010). Invited speaker.
    Paper: Based on a series of papers
    Author: Nielsen Jens Perch
    Co-authors: Gustafsson, Guillen, Bolance
  26. Adding prior knowledge when modelling operational risk. (Seminar) Granada,Spain (2010). Invited speaker.
    Paper: Based on a series of papers
    Author: Nielsen JP
    Co-authors: Gustafsson, Guillen, Bolance
  27. Adding prior knowledge when modelling operational risk. (Seminar) Mannheim, Germany (2010). Invited speaker.
    Paper: Based on a series of papers
    Author: Nielsen jens Perch
    Co-authors: gustafsson, Guillen, Bolance
  28. Optimizing ERM & Economic Capital. (Conference) London (2009). Invited speaker.
    Paper: Quantifying Operational Risk
    Author: Nielsen J.P
  29. STATISTICAL REGULARIZATION AND CONSTRANTS. (Conference) Gøttingen, Germany (2008). Invited speaker.
    Paper: Qualitative constraints and insurance
    Author: Nielsen J.P
  30. RSA-Oxford-Conference. (Conference) Nuffield College, Oxford (2008). Invited speaker.
    Paper: Improving Claims Reserving towards 2012
    Author: Nielsen J.P
  31. Giro. (Conference) Italy, Sorrento (2008). Invited speaker.
    Paper: Beyond Chain Ladder in Claims Reserving
    Author: Nielsen J.P
  32. RSA-Oxford-Conference. (Conference) Nuffield College, Oxford (2007). Invited speaker.
    Paper: Towards a mathematical statistical model of claims reserving: the full cash flow approach.
    Author: Nielsen J.P
  33. Giro. (Conference) Newport (2007). Invited speaker.
    Paper: Granular Reserving – Making best use of your claims and policy data
    Author: Margetts S
    Co-authors: J.P. Nielsen
  34. Giro. (Conference) Newport (2007). Invited speaker.
    Paper: A Dynamic Approach to the understanding of incurred claims
    Author: Nielsen J.P
    Co-authors: Margetts, S and Pezzulli, S.
  35. GIRO. (Conference) Newport (2007). Invited speaker.
    Paper: Adding Counts In: A Revolution in Claims Reserving
    Author: Jessen A
    Co-authors: Verrall, Richard
  36. RSA-Oxford-Conference. (Conference) Nuffield College, Oxfrod (2006). Invited speaker.
    Paper: Reorganisation of pricing and reserving in non-life insurance
    Author: Nielsen J.P
  37. GIRO. (Conference) Vienna, Austria (2006). Invited speaker.
    Paper: Can One Use the Same Model for Pricing, Budgeting and Reserving?
    Author: Nielsen J.P

Keynote lectures/speeches (7)

  1. Monitoring a developing pandemic with available data. London (2021). Opened the conference of Computational Statistics and Data Analyses as keynote speaker
  2. Monitoring a developing pandemic with available data. Prague, Charles University (2021). Keynote speaker at conference organized by Jozef Barunik and Wolfgang Haerdle on Big Data and Econometrics
  3. Monitoring a developing pandemic with available data. Connecticut (2021). Invited speaker at Connecticut University invited by Bin Zou
  4. Monitoring a developing pandemic with available data. Wisconsin, USA (2021). Invited speaker at Wisconsin invited by Peng Zhi
  5. Self-selection and risk sharing in a modern world of life-long annuities. Institute of Actuaries, Stable Inn, London (2018). Sessional meeting published in British Actuarial Journal with discussion
  6. Communication and self control of a pension saver's financial risk. Institute of Actuaries, Stable Inn, London (2017). Keynote speaker at Webinar
  7. In-Sample Forecasting in insurance, longevity and the labour market. London (2015). Seminar talk and organization of session at Computational Statistics and Data analyses

Media appearance

  1. Don't throw baby out with the bath water. (2013) The Actuary.