Skip to main content
×
Home
Weather Derivative Valuation
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 42
  • Cited by
    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Göncü, Ahmet Liu, Yaning Ökten, Giray and Hussaini, M. Yousuff 2016. Monte Carlo and Quasi-Monte Carlo Methods.


    Kermiche, L. and Vuillermet, N. 2016. Weather derivatives structuring and pricing: a sustainable agricultural approach in Africa. Applied Economics, Vol. 48, Issue. 2, p. 165.


    Zong, Lu and Ender, Manuela 2016. Comparison of Stochastic and Spline Models for Temperature-based Derivatives in China. Pacific Economic Review,


    Erhardt, R. J. 2015. Mid-twenty-first-century projected trends in North American heating and cooling degree days. Environmetrics, Vol. 26, Issue. 2, p. 133.


    Mori, Hiroyuki and Fujita, Hajime 2015. 2015 IEEE Congress on Evolutionary Computation (CEC). p. 325.

    2015. Financial Risk Management.


    Chan, Ngai H. and Wong, Chun Y. 2014. Wiley StatsRef: Statistics Reference Online.


    Erhardt, Robert J. and Smith, Richard L. 2014. Weather Derivative Risk Measures for Extreme Events. North American Actuarial Journal, Vol. 18, Issue. 3, p. 379.


    Little, L. Richard Parslow, John Fay, Gavin Grafton, R. Quentin Smith, Anthony D.M. Punt, André E. and Tuck, Geoffrey N. 2014. Environmental Derivatives, Risk Analysis, and Conservation Management. Conservation Letters, Vol. 7, Issue. 3, p. 196.


    2014. Wavelet Neural Networks.


    2014. Wavelet Neural Networks.


    2014. Commodity Option Pricing.


    Alexandridis, A. and Zapranis, A. 2013. Wind Derivatives: Modeling and Pricing. Computational Economics, Vol. 41, Issue. 3, p. 299.


    Brands, S. 2013. Skillful Seasonal Predictions of Boreal Winter Accumulated Heating Degree-Days and Relevance for the Weather Derivative Market. Journal of Applied Meteorology and Climatology, Vol. 52, Issue. 6, p. 1297.


    Gombos, Daniel and Hoffman, Ross N. 2013. Ensemble-Based Exigent Analysis. Part I: Estimating Worst-Case Weather-Related Forecast Damage Scenarios. Weather and Forecasting, Vol. 28, Issue. 3, p. 537.


    Hood, John Stein, Bill and Jarman, Mark 2013. Public Sector Risk Financing: Exploring the Potential Use of Weather Derivatives by Fire and Rescue Services. Local Government Studies, Vol. 39, Issue. 4, p. 562.


    Watkins, N. W. 2013. Bunched black (and grouped grey) swans: Dissipative and non-dissipative models of correlated extreme fluctuations in complex geosystems. Geophysical Research Letters, Vol. 40, Issue. 2, p. 402.


    Barrieu, Pauline Bensusan, Harry El Karoui, Nicole Hillairet, Caroline Loisel, Stéphane Ravanelli, Claudia and Salhi, Yahia 2012. Understanding, modelling and managing longevity risk: key issues and main challenges. Scandinavian Actuarial Journal, Vol. 2012, Issue. 3, p. 203.


    Botoş, Horia Mircea and Ciumaş, Cristina 2012. The use of the Black-Scholes Model in the Field of Weather Derivatives. Procedia Economics and Finance, Vol. 3, p. 611.


    Schiller, Frank Seidler, Gerold and Wimmer, Maximilian 2012. Temperature models for pricing weather derivatives. Quantitative Finance, Vol. 12, Issue. 3, p. 489.


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

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

    Weather Derivative Valuation
    • Online ISBN: 9780511493348
    • Book DOI: https://doi.org/10.1017/CBO9780511493348
    Please enter your name
    Please enter a valid email address
    Who would you like to send this to? *
    ×
  • Buy the print book

Book description

Originally published in 2005, Weather Derivative Valuation covers all the meteorological, statistical, financial and mathematical issues that arise in the pricing and risk management of weather derivatives. There are chapters on meteorological data and data cleaning, the modelling and pricing of single weather derivatives, the modelling and valuation of portfolios, the use of weather and seasonal forecasts in the pricing of weather derivatives, arbitrage pricing for weather derivatives, risk management, and the modelling of temperature, wind and precipitation. Specific issues covered in detail include the analysis of uncertainty in weather derivative pricing, time-series modelling of daily temperatures, the creation and use of probabilistic meteorological forecasts and the derivation of the weather derivative version of the Black-Scholes equation of mathematical finance. Written by consultants who work within the weather derivative industry, this book is packed with practical information and theoretical insight into the world of weather derivative pricing.

Reviews

Review of the hardback:‘Weather Derivative Valuation draws on both finance and meteorology, with a healthy dose of mathematics and statistics, to provide the practitioner with a comprehensive guide to the various methods for pricing and hedging weather derivative contracts. While no perfect model may exist, Jewson and Brix give the reader the background necessary to make informed choices between competing techniques.’

William Gebhardt - Merrill Lynch

Review of the hardback:‘The weather derivatives market is exciting, dynamic and growing. This book is the most complete treatment I have seen of the many issues surrounding valuation of weather derivatives, starting from the basic principles, and then covering all the bases including meteorological data analysis, pricing, portfolio management, incorporation of forecasts and risk management. As a practitioner in the market, I found this book comprehensive and excellently written. Jewson and Brix have taken a complex subject and made it both interesting to read and easy to understand. I would have no hesitation in recommending it to others, both experts in the field and those approaching the subject for the first time.’

Gearóid Lane - Centrica

Review of the hardback:‘The book covers all of the latest topics in weather derivative pricing, valuation and risk management in a way that is rigorous, and yet also accessible to the non-mathematician. Highly recommended for all involved in weather derivatives, whether they are hedgers, traders, investors, marketers or risk managers.’

Martin Jones - Chief Investment Officer, Coriolis Capital Limited

    • Aa
    • Aa
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.
×

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 350 *
Loading metrics...

Book summary page views

Total views: 133 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 25th June 2017. This data will be updated every 24 hours.