Financial Analytics in Spreadsheets
Learn how to build a graphical dashboard with spreadsheets to track the performance of financial securities.
- 4 hours
- 15 Videos
- 56 Exercises
- 9,447 Participants
- 4,650 XP
Create Your Free Account
By pressing Continue you accept the Terms of Use and Privacy Policy. You also accept that you are aware that your data will be stored outside of the EU and that you are above the age of 16.
Loved by learners at thousands of top companies:
Course Description
Monitoring the evolution of traded assets is key in finance. In this course, you will learn how to build a graphical dashboard with spreadsheets to track the performance of financial securities. You will focus on historical prices and dividends of the hypothetical stock ABC. You will learn how to visualize its prices, how to measure essential reward and risk indicators, and see if your investment in ABC outperformed a benchmark index. At the end of the course, you should be able to use spreadsheets to build great monitoring tools used by traders and financial analysts in their day-to-day business life!
-
1
Monitoring historical prices
FreeIn the first chapter, you’ll be introduced to the problem: you have a time series of monthly (historical) prices for the hypothetical stock ABC from which you have to extract some meaningful information. You’ll be given some definitions (what is a stock? what are dividends?), and at the end of the chapter, you’ll be able to graphically represent the evolution of a stock price over a specific period.
-
Monitoring the distribution of returns
In this chapter, you'll look at the full distribution of historical returns. First, you’ll learn how to build a histogram to describe the distribution of historical returns. Second, you’ll be introduced to the Gaussian distribution, a commonly used model for stock returns. You'll visually inspect if the Gaussian model is reasonable for the ABC stock returns. Finally, you'll understand potential flaws with the Gaussian model.
-
Monitoring historical returns
In this chapter, the core of the analysis will switch from historical prices to historical returns. You’ll learn (and compute) the main performance indicators of past returns, both in terms of reward and risk. Finally, you’ll be introduced to risk-adjusted performance measures: indicators that take into account both reward and risk.
-
Benchmarking performance
In this final chapter, you’ll benchmark ABC stock against a market index and verify whether ABC outperformed the benchmark or not. The comparison process will be done through several steps/metrics. First, you’ll analyze the cumulative wealth. Next, you’ll extend the comparison using different indicators such as Sharpe Ratio and Drawdown. Finally, you’ll examine the linear relation between ABC stock and the benchmark through the correlation coefficient. At the end of the chapter, you’ll be introduced to more powerful and advanced spreadsheet features that introduce interactivity in your analysis.
-
1
Monitoring historical prices
FreeIn the first chapter, you’ll be introduced to the problem: you have a time series of monthly (historical) prices for the hypothetical stock ABC from which you have to extract some meaningful information. You’ll be given some definitions (what is a stock? what are dividends?), and at the end of the chapter, you’ll be able to graphically represent the evolution of a stock price over a specific period.
-
Monitoring historical returns
In this chapter, the core of the analysis will switch from historical prices to historical returns. You’ll learn (and compute) the main performance indicators of past returns, both in terms of reward and risk. Finally, you’ll be introduced to risk-adjusted performance measures: indicators that take into account both reward and risk.
-
Monitoring the distribution of returns
In this chapter, you'll look at the full distribution of historical returns. First, you’ll learn how to build a histogram to describe the distribution of historical returns. Second, you’ll be introduced to the Gaussian distribution, a commonly used model for stock returns. You'll visually inspect if the Gaussian model is reasonable for the ABC stock returns. Finally, you'll understand potential flaws with the Gaussian model.
-
Benchmarking performance
In this final chapter, you’ll benchmark ABC stock against a market index and verify whether ABC outperformed the benchmark or not. The comparison process will be done through several steps/metrics. First, you’ll analyze the cumulative wealth. Next, you’ll extend the comparison using different indicators such as Sharpe Ratio and Drawdown. Finally, you’ll examine the linear relation between ABC stock and the benchmark through the correlation coefficient. At the end of the chapter, you’ll be introduced to more powerful and advanced spreadsheet features that introduce interactivity in your analysis.
What do other learners have to say?
“I've used other sites, but DataCamp's been the one that I've stuck with.”
Devon Edwards Joseph
Lloyd's Banking Group
“DataCamp is the top resource I recommend for learning data science.”
Louis Maiden
Harvard Business School
“DataCamp is by far my favorite website to learn from.”
Ronald Bowers
Decision Science Analytics @ USAA
David Ardia
Professor of Quantitative Methods for Finance
David is professor of quantitative methods for finance. His research lies in the areas of econometrics, quantitative finance, and risk management. In 2018, he was elected “Swiss risk manager of the year” by the Swiss Risk Association. He is a big fan of open-source initiatives and is the co-author of several R packages such as "DEoptim", "GAS", "MSGARCH", and "sentometrics". He is a member of the Sentometrics organization. When he does not code, he is a foodie in Montréal. For more details go here.
See More
Riccardo Mancini
Freelance Quantitative Analyst
Riccardo is a Market Risk Analyst for a financial services firm. He is passionate about coding in R, quantitative models applied to finance, and… soccer!
See MoreCollaborators
-
Chester Ismay
-
Sara Billen