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Financial Time Series Analysis in R

27 lessons0%

Resources

Lessons

Financial Time Series Data

Exploring Time Series Data in R

Plotting Time Series in R

Handling Missing Values in Time Series

Creating a Time Series Object in R

Check if an object is a time series object in R

Plotting Financial Time Series Data (Multiple Columns) in R

Characteristics of Time Series

Stationary Process in Time Series

Transforming a Series to Stationary

Time Series Transformation in R

Differencing and Log Transformation

Autocorrelation in R

Time Series Models

Simulate White Noise (WN) in R

Simulate Random Walk (RW) in R

AutoRegressive (AR) Model in R

Estimating AutoRegressive (AR) Model in R

Forecasting with AutoRegressive (AR) Model in R

Moving Average (MA) Model in R

Estimating Moving Average (MA) Model in R

ARIMA Modelling in R

ARIMA Modelling - Identify Model for a Time Series

Forecasting with ARIMA Modeling in R - Case Study

Automatic Identification of Model Using auto.arima() Function in R

Financial Time Series in R - Course Conclusion

Lesson 27 of 27

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Financial Time Series in R - Course Conclusion | Finance Train

Financial Time Series in R - Course Conclusion

This course provided an overview of the fundamentals of time series analysis and how we can perform time series analysis in R. We reviewed some of the most important concepts of time series analysis and looked at the process involved in modeling a time series using the ARIMA models.