Visualizing Weather Financial Impact on Industries and Weather Derivatives

Inga Bondarenko, Priyanka Bhushan Phapale, Stefan Robila

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the accelerating generation of enormous datasets, data processing tools are also increasing in computational efficiency as well as accuracy. Along with data mining and clustering techniques, tools that enable data visualization are also becoming mainstream mechanisms for extracting the maximum available useful information out of data. This is especially true for financial systems. Analyzing all available information and predicting short and long-term market trends with their fluctuations has been the cornerstone of trading strategies and giving investment advice for years. One of the interesting financial instruments, which can potentially utilize big data analysis and algorithms in several different ways are weather derivatives. Unlike other financial instruments, their research combines both market and weather analysis. This is quite complex and fits perfectly as an area we can explore big data processing and visualization capabilities. In this paper, we analyze the relationship between weather derivatives and weather and investigate how predicting the weather leads to predicting index values and therefore prices for weather derivatives. In pursuing this, we develop a web-based tool that employs weather prediction tools and use it to visualize and predict weather future prices. This research provides an example of how converging data streams can be efficiently analyzed.

Original languageEnglish
Title of host publication2019 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728121000
DOIs
StatePublished - 1 May 2019
Event2019 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2019 - Farmingdale, United States
Duration: 3 May 2019 → …

Publication series

Name2019 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2019

Conference

Conference2019 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2019
CountryUnited States
CityFarmingdale
Period3/05/19 → …

Keywords

  • big data
  • futures prices prediction
  • weather derivatives
  • weather prediction algorithm

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  • Cite this

    Bondarenko, I., Phapale, P. B., & Robila, S. (2019). Visualizing Weather Financial Impact on Industries and Weather Derivatives. In 2019 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2019 [8817335] (2019 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LISAT.2019.8817335