New Course - Financial Time Series Analysis with R

We are pleased to announce the addition of a new course - Financial Time Series with R - to our growing library of courses on Data Science for Finance Professionals.

Course: Financial Time Series Analysis

Learn the fundamentals of analyzing a financial time series in R

This course provides an introduction to the financial times series data and how we can analyze the time series data in R. You will learn about how to explore and build time series data, calculate its key statistics, and plot time series charts. You will also learn about how to use the important time series models such as White Noise, Random Walk, Autoregression and Moving Average. You will learn how to simulate these models in R and fit these models into financial time series data using the ARIMA functions. Finally you will learn about how to use the models to predict the future.

Course Curriculum

• Financial Time Series Data
• Exploring Time Series
• Plotting Time Series
• Handling Missing Values in Time Series
• Creating a Time Series Object in R
• Check if an object is a time series object
• Plotting Financial Time Series Data (Multiple Columns)
• Characteristics of Time Series
• Stationary Process
• Transforming a Series to Stationary
• Time Series Transformation in R
• Differencing and Log Transformation
• Autocorrelation
• Time Series Models
• ARIMA Modeling
• White Noise (WN) in R
• Random Walk (RW) in R
• AutoRegressive (AR) Model in R
• Estimating AR Model in R
• Forecasting with AR Model
• Moving Average (MA) Model in R
• Estimating MA Model in R
• ARIMA Modelling in R
• ARIMA Modelling - Identification
• Case Study - Forecasting with ARIMA Modeling
• Automatic Identification of Model
• Conclusion

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