01-09-2024, 06:53 AM
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Released 1/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Advanced | Genre: eLearning | Language: English + srt | Duration: 57m | Size: 157 MB
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The Wolfram Language contains a complete collection of stochastic processes and statistical distributions that can be fitted to a wide array of market phenomena. This course illustrates this by explaining 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. Learn how to access financial data from the Wolfram Knowledge base, smooth and transform data, build models for examining stock prices and returns, test different types of models, examine distribution patterns of prices and returns, and more.
Homepage
Released 1/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Advanced | Genre: eLearning | Language: English + srt | Duration: 57m | Size: 157 MB
[/center]
The Wolfram Language contains a complete collection of stochastic processes and statistical distributions that can be fitted to a wide array of market phenomena. This course illustrates this by explaining 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. Learn how to access financial data from the Wolfram Knowledge base, smooth and transform data, build models for examining stock prices and returns, test different types of models, examine distribution patterns of prices and returns, and more.
Homepage
Code:
https://rapidgator.net/file/7c8509dd2e19ba9ed74e111db7311cf4/Modeling_Market_Prices_Using_Stochastic_Processes_with_Wolfram_Language.rar.html
https://uploadgig.com/file/download/27f43B3f81f7c1c8/Modeling_Market_Prices_Using_Stochastic_Processes_with_Wolfram_Language.rar