Time Varying Volatility Models for Stochastic Finance | Weather Derivatives скачать в хорошем качестве

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... ★ ★ Code Available on GitHub ★ ★ GitHub: https://github.com/TheQuantPy Specific Tutorial Link: https://github.com/TheQuantPy/youtube... ★ A data driven path to getting a job in Quant Finance https://www.quantpykit.com/ ★ QuantPy GitHub Collection of resources used on QuantPy YouTube channel. https://github.com/thequantpy Disclaimer: All ideas, opinions, recommendations and/or forecasts, expressed or implied in this content, are for informational and educational purposes only and should not be construed as financial product advice or an inducement or instruction to invest, trade, and/or speculate in the markets. Any action or refraining from action; investments, trades, and/or speculations made in light of the ideas, opinions, and/or forecasts, expressed or implied in this content, are committed at your own risk an consequence, financial or otherwise.