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Lecture
Time Series: Modeling and Analysis
Description
This lecture introduces time series as a set of measurements recorded over time, focusing on modeling temporal dependence. Topics include trend, periodic components, regression analysis, harmonic regression, stationarity testing, autocorrelation function, and independence testing. Practical examples with CO₂ data and financial data are discussed, emphasizing the importance of white noise testing in finance.
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