Time Varying Volatility Models for Stochastic Finance | Weather Derivatives

Now that we have a defined the parameters of our modified mean-reverting Ornstein-Uhlenbeck process which defines our Temperature dynamics, in this tutorial we will now be looking to implement different models for our time varying volatility patterns.

We have a number of options to model temperature volatility across seasons.
Piece-wise Constant Functions (volatility for each season)
Parametric Regression - Polynomial
Local and Nonparametric Regression - Splines
Fourier Series
Stochastic Differential Equations

Online written tutorial: https://quantpy.com.au/weather-deriva...

In this series we take a deep dive into a type of exotic financial products weather derivatives. Weather derivatives are financial instruments that can be used to reduce risk associated with adverse weather conditions like temperature, rainfall, frost, snow, and wind speeds.

Historical Data, Weather Observations for Sydney, Australia – Observatory Hill: http://www.bom.gov.au/climate/data/st...

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Specific Tutorial Link: https://github.com/TheQuantPy/youtube...

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