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Learning pandas - Second Edition by Michael Heydt

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Stochastic models

Stochastic models are a form of statistical modeling that includes one or more random variables, and typically includes use of time series data. The purpose of a stochastic model is to estimate the chance that an outcome is within a specific forecast to predict conditions for different situations.

An example of stochastic modeling is the Monte Carlo simulation. The Monte Carlo simulation is often used for financial portfolio evaluation by simulating the performance of a portfolio based upon repeated simulation of the portfolio in markets that are influenced by various factors and the inherent probability distributions of the constituent stock returns.

pandas gives us the fundamental data structure for stochastic models in ...

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