[Datasciencecentral] BigDataFr recommends: A Simple Introduction to Complex Stochastic Processes

stochastic processes

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[…] Stochastic processes have many applications, including in finance and physics. It is an interesting model to represent many phenomena. Unfortunately the theory behind it is very difficult, making it accessible to a few ‘elite’ data scientists, and not popular in business contexts.

One of the most simple examples is a random walk, and indeed easy to understand with no mathematical background. However, time-continuous stochastic processes are always defined and studied using advanced and abstract mathematical tools such as measure theory, martingales, and filtration. If you wanted to learn about this topic, get a deep understanding on how they work, but were deterred after reading the first few pages of any textbook on the subject due to jargon and arcane theories, here is your chance to really understand how it works. […]

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By Vincent Granville
Source: datasciencecentral.com

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