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Moving Average (MA) and ARMA Models | Chan`s Jupyter
Moving Average (MA) and ARMA Models | Chan`s Jupyter
A Summary of lecture “Time Series Analysis in Python”, via datacamp
This post offers a comprehensive overview of the Moving Average (MA) model, specifically focusing on the MA(1) process and its practical applications, like stock price analysis.
The detailed explanation of simulating time series data, calculating the autocorrelation function (ACF), and estimating MA parameters using statsmodels is very insightful.
The examples, including high-frequency stock prices, effectively demonstrate how MA models can be applied to real-world data.
Overall, it’s an excellent resource for those interested in time series analysis and financial forecasting.
Regards, https://dicc.in/stock-market-courses.html
