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Applied Finance in R

Grow your financial skills in R and learn how to manipulate data and make better data-driven decisions. You’ll begin this track by learning how to evaluate portfolios and value stocks using present value approaches, free cash flow, and equity and dividend discount models. Next, you’ll explore life insurance products and learn the basics of financial trading. Through interactive coding exercises, you’ll use powerful libraries, including quantmod, QRM, xts, zoo, and quantstrat, to examine and manage credit risk. You’ll then apply what you’ve learned to answer questions commonly faced by financial firms, such as how to value a fixed interest rate bond and estimate a bond's yield. Along the way, you’ll also create GARCH models and get hands-on with real data from the US Treasury, daily Microsoft returns, and S&P 500 data. Start this track to advance your R financial skills.

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1
R
Quantitative Risk Management in R

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

5 hours

Alexander J. McNeil Headshot

Alexander J. McNeil

Professor of Actuarial Science at the University of York.

2
R
Equity Valuation in R

Learn the fundamentals of valuing stocks.

4 hours

Clifford Ang Headshot

Clifford Ang

Vice President at Compass Lexecon

3
R
Bond Valuation and Analysis in R

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

4 hours

Clifford Ang Headshot

Clifford Ang

Vice President at Compass Lexecon

4
R
Financial Trading in R

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

5 hours

Ilya Kipnis Headshot

Ilya Kipnis

Professional Quantitative Analyst and R programmer

5
R
Credit Risk Modeling in R

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

4 hours

Lore Dirick Headshot

Lore Dirick

Director of Data Science Education at Flatiron School

6
R
GARCH Models in R

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

4 hours

Kris Boudt Headshot

Kris Boudt

Professor of Finance and Econometrics at VUB and VUA

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