Home›Lesson 5: Time Series Analysis
Lesson 5

Time Series Analysis

ARIMA, SARIMA, GARCH, State-Space Models, Kalman Filter, LSTM
40Frames40Charts
Download Slides (PDF) Visual Guide (PDF) Take Quiz (20 Q) Simple Quiz (Beginner) Quiz PDF

Sections

Part 1
Foundations
Part 2
Classical Time Series Models
Part 3
Volatility Models
Part 4
Forecasting and Evaluation
Part 5
Advanced Topics
Part 6
Summary and Key Takeaways

Charts (40)

TS IntroductionTS Introduction DecompositionDecomposition StationarityStationarity White NoiseWhite Noise Random WalkRandom Walk ADF TestADF Test DifferencingDifferencing ACF / PACFACF / PACF AR ProcessAR Process AR(1) ExamplesAR(1) Examples MA ProcessMA Process MA(1) ExamplesMA(1) Examples ARMA ExampleARMA Example ARIMA IdentificationARIMA Identification ARIMA NotationARIMA Notation ARIMA ExampleARIMA Example Box-Jenkins FlowBox-Jenkins Flow Seasonal PatternsSeasonal Patterns SARIMA ForecastSARIMA Forecast ETS WeightsETS Weights ETS vs ARIMAETS vs ARIMA AIC / BIC CompareAIC / BIC Compare Residuals (Good)Residuals (Good) Residuals (Bad)Residuals (Bad) Volatility ClusteringVolatility Clustering GARCH FitGARCH Fit GARCH ExampleGARCH Example State SpaceState Space Kalman FilterKalman Filter LSTM ArchitectureLSTM Architecture ML ComparisonML Comparison Algorithm ChoiceAlgorithm Choice Forecast ComparisonForecast Comparison Naive vs ARIMANaive vs ARIMA Prediction IntervalsPrediction Intervals Accuracy MetricsAccuracy Metrics Cross ValidationCross Validation CV ResultsCV Results Worked Example 1Worked Example 1 Worked Example 2Worked Example 2
‹ Lesson 4: Cluster Analysis
Home|GitHub| Statistical Data Analysis | Digital AI Finance | BSc Data Science | © Joerg Osterrieder 2025-2026