Three multidecadal daily time series of mid-latitude near-surface air temperature are analysed. Long-range dependence can be detected in all 3 time series with 95% statistical significance. It is shown that fractionally integrated time-series models can accurately and parsimoniously reproduce the autocovariance structure of the observed data. The concept of weather derivatives is introduced and problems surrounding their pricing are discussed. It is shown that the fractionally integrated time-series models provide much more accurate pricing as compared with traditional autoregressive models employing a similar number of parameters. Finally, it is suggested that a simple explanation for the presence of long memory in the time series may be given in terms of aggregation of several short-memory processes.
KEY WORDS: Surface temperature · Long memory · Weather derivativeResale or republication not permitted without written consent of the publisher
Abstract:The extent to which the North Atlantic Oscillation (NAO) is in¯uenced by changes in the ocean state is an issue that has attracted much recent attention. Although there have been counter claims, the weight of evidence clearly suggests that forcing by the ocean of year-to-year changes in the NAO is a weak in¯uence by comparison with atmospheric internal variability. The NAO is thus very different in character to the Southern Oscillation (SO), and its predictabilityÐat least on seasonal-to-interannual timescalesÐis almost certainly much lower. Although weak, the in¯uence of the ocean on the NAO is not negligible. In a previous study we found that wintertime North Atlantic climate, including the NAO, was signi®cantly in¯uenced by a tripole pattern of North Atlantic SST anomalies. Here we report the results of experiments to further elucidate the nature of this in¯uence. We show that the tripole pattern induces a signi®cant response both in the tropical Atlantic and at mid-to-high latitudes. The low latitude response is forced by the low latitude SST anomalies, but the high latitude response is in¯uenced by the extratropical SST anomalies as well as those in the tropics. Furthermore, we ®nd evidence of nonlinear interaction between the in¯uence of the tropical and extratropical SST anomalies. Lastly, we investigate the feedback from the atmosphere onto the SST tripole. We ®nd that the expected negative feedback is signi®cantly modi®ed at low latitudes by the dynamical response of the atmosphere. *
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.