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How to model stock prices, portfolios, index returns, bonds, option prices, exchange rates and conditional risk using stochastic processes such as the ARCH process, vector-valued time series, ARMA model, Chen's model, Ito process and Merton jump diffusion.
Course Overview
This video talks about the modeling of stock prices, portfolios, index returns, bonds, option prices, exchange rates and conditional risk using stochastic processes such as the ARCH process, vector-valued time series, the ARMA model, Chen's model, the Ito process and Merton jump diffusion. In doing so, it shows that the Wolfram Language contains a complete collection of stochastic processes and statistical distributions that can be fitted to a wide array of market phenomena. Requirements: Wolfram Language (available in Mathematica and Wolfram|One), Wolfram Data Framework, Wolfram Finance Platform, Wolfram Knowledgebase
You'll Learn To
Access financial data from the Wolfram Knowledgebase
Smooth and transform data
Build models for examining stock prices and returns
Test different types of models
Examine distribution patterns of prices and returns
Use different stochastic processes to model financial data
Create visualizations of time series data
Course Overview
This video talks about the modeling of stock prices, portfolios, index returns, bonds, option prices, exchange rates and conditional risk using stochastic processes such as the ARCH process, vector-valued time series, the ARMA model, Chen's model, the Ito process and Merton jump diffusion. In doing so, it shows that the Wolfram Language contains a complete collection of stochastic processes and statistical distributions that can be fitted to a wide array of market phenomena. Requirements: Wolfram Language (available in Mathematica and Wolfram|One), Wolfram Data Framework, Wolfram Finance Platform, Wolfram Knowledgebase
You'll Learn To
Access financial data from the Wolfram Knowledgebase
Smooth and transform data
Build models for examining stock prices and returns
Test different types of models
Examine distribution patterns of prices and returns
Use different stochastic processes to model financial data
Create visualizations of time series data
