COURSE
Financial Time Series Analysis in R
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 predictive modeling and how to use these models to predict the future.
- We've provided various step-by-step examples using real financial time series data such as stock prices, and economic factors.
What's Included
- Detailed concepts and explanations about each topic
- Step-by-step instructions for all models built in R
- All the data files used in the book
- Complete downloadable R code for all examples used in the book
Course Resources
eBook for Financial Time Series Analysis with R
Member-only
Data and R Code Files for Financial Time Series Analysis with R
Member-only
Lessons
Data Science in Finance: 9-Book Bundle
Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.
What's Included:
- Getting Started with R
- R Programming for Data Science
- Data Visualization with R
- Financial Time Series Analysis with R
- Quantitative Trading Strategies with R
- Derivatives with R
- Credit Risk Modelling With R
- Python for Data Science
- Machine Learning in Finance using Python
Each book includes PDFs, explanations, instructions, data files, and R code for all examples.
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