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WeDeAn – The Weather Derivatives Analyzer

Back in 2018, I wrote my bachelor's thesis on weather derivatives, exploring how temperature data can be used to price financial contracts that hedge against adverse temperature deviations.

At that time, I built the prototype entirely in Excel.

Two years later, when I started learning Python, I revisited the project and created my first simple GUI using Tkinter.

The present version is a rewrite of the tool as a Streamlit web application, containerized with Docker for deployment.

What WeDeAn does

WeDeAn links weather data from the German Weather Service (DWD) to financial derivatives — the instruments that energy traders, utilities, and insurers use to hedge demand and revenue fluctuations driven by temperature.

In effect, it estimates fair values of weather derivatives from historical temperature records.

Key features

  • Visualizes historical weather trends (temperature, sunshine, rainfall)
  • Calculates heating degree days (HDDs), a measure of how cold a season was
  • Calculates cooling degree days (CDDs), a measure of how hot a season was
  • Estimates fair values of HDD/CDD options via burn analysis, a data-driven pricing approach

How it works

  1. Historical weather data are loaded for a chosen DWD station.
  2. Seasonal degree-day indices (HDDs and CDDs) are computed.
  3. The historical payoffs of an option written on those indices are evaluated.
  4. A fair value is estimated from the distribution of those historical payoffs.

Watch the demo

Watch the video

Availability

WeDeAn is open source and is distributed as a Docker container.