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Applying Data Analytics in Finance
  • Level Professional
  • Duration 24 hours
  • Course by University of Illinois Urbana-Champaign
  • Offered by

About

This course introduces an overview of financial analytics. You will learn why, when, and how to apply financial analytics in real-world situations. You will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. While most of the focus will be on the prices, returns, and risk of corporate stocks, the analytical techniques can be leverages in other domains. Finally, a short introduction to algorithmic trading concludes the course. After completing this course, you should be able to understand time series data, create forecasts, and determine the efficacy of the estimates. Also, you will be able to create a portfolio of assets using actual stock price data while optimizing risk and reward. Understanding financial data is an important skill as an analyst, manager, or consultant.

Modules

About the Course

    • 4 Videos
    • 5 Readings
    • 1 Quiz
Show info about module content

4 Videos

  • Coursera Course Introduction ***
  • Instructor Bio: Jose Rodriguez ***
  • Interview with Jose Rodriguez
  • Learn on Your Terms

5 Readings

  • Syllabus
  • Glossary
  • Resources for R
  • About the Discussion Forums
  • Online Education at Gies College of Business

1 Quiz

  • Orientation Quiz

Module 1 Information

    • 2 Videos
    • 2 Readings
Show info about module content

2 Videos

  • Module 1 Overview ***
  • Jose Rodriguez: Forecasting in Practice

2 Readings

  • Module 1 Overview
  • Module 1 Readings

Lesson 1-1: Elements of Forecasting

    • 2 Videos
    • 1 Quiz
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2 Videos

  • Lesson 1-1.1 Subjective Forecasting
  • Lesson 1-1.2 Business Forecasting and Time Series Data

1 Quiz

  • Lesson 1-1 Practice Quiz

Lesson 1-2: Introduction to Financial Analytics

    • 1 Videos
    • 1 Quiz
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1 Videos

  • Lesson 1-2.1 Introduction to Financial Analytics

1 Quiz

  • Lesson 1-2 Practice Quiz

Lesson 1-3: Perfomance Metrics

    • 2 Videos
    • 1 Quiz
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2 Videos

  • Lesson 1-3.1 Forecasting Performance Measurements: Distance
  • Lesson 1-3.2 Forecasting Performance Measurements: Metrics

1 Quiz

  • Lesson 1-3 Practice Quiz

Module 1 Graded Activities

    • 2 Quiz
    • 1 Lab
Show info about module content

1 Labs

  • Financial Analytics Lab

2 Quiz

  • Module 1 Quiz
  • Module 1 Lab Exercise Quiz

Module 2 Information

    • 2 Videos
    • 2 Readings
Show info about module content

2 Videos

  • Module 2 Overview ***
  • Jose Rodriguez: Forecasting Models in Practice

2 Readings

  • Module 2 Overview
  • Module 2 Readings

Lesson 2-1: Introduction to Forecasting

    • 4 Videos
    • 1 Quiz
Show info about module content

4 Videos

  • Lesson 2-1.1 Introduction to Forecasting: Average Method
  • Lesson 2-1.2 Introduction to Forecasting: Naive Method
  • Lesson 2-1.3 Introduction to Forecasting: Linear Regression ***
  • Lesson 2-1.4 Introduction to Forecasting: R Example

1 Quiz

  • Lesson 2-1 Practice Quiz

Lesson 2-2: Moving Averages - look for the moving average lecture video if no video found, we'll remove the enter lesson

    • 1 Videos
    • 1 Quiz
Show info about module content

1 Videos

  • Lesson 2-2.1 Moving Averages

1 Quiz

  • Lesson 2-2 Practice Quiz

Lesson 2-3: Exponential Smoothing

    • 3 Videos
    • 1 Quiz
Show info about module content

3 Videos

  • Lesson 2-3.1 Introduction to Exponential Smoothing
  • Lesson 2-3.2 Simple Exponential Smoothing
  • Lesson 2-3.3 Simple Exponential Smoothing: R Example

1 Quiz

  • Lesson 2-3 Practice Quiz

Lesson 2-4: HoltWinters

    • 3 Videos
    • 1 Quiz
Show info about module content

3 Videos

  • Lesson 2-4.1 Holt's Exponential Smoothing
  • Lesson 2-4.2 Holt-Winter's Forecasting Model
  • Lesson 2-4.3 Holt-Winter's Model: R Example

1 Quiz

  • Lesson 2-4 Practice Quiz

Lesson 2-5: Auto Regression

    • 2 Videos
    • 1 Quiz
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2 Videos

  • Lesson 2-5.1 Autoregression
  • Lesson 2-5.2 Autoregression: R Example

1 Quiz

  • Lesson 2-5 Practice Quiz

Module 2 Graded Activities

    • 2 Quiz
    • 1 Lab
Show info about module content

1 Labs

  • Analytical Methods Lab

2 Quiz

  • Module 2 Quiz
  • Module 2 Lab Exercise Quiz

Module 3 Information

    • 2 Videos
    • 2 Readings
Show info about module content

2 Videos

  • Module 3 Overview ***
  • Jose Rodriguez: ARIMA in Practice

2 Readings

  • Module 3 Overview
  • Module 3 Readings

Lesson 3-1: Stationarity

    • 2 Videos
    • 1 Quiz
Show info about module content

2 Videos

  • Lesson 3-1.1 Stationarity: Introduction
  • Lesson 3-1.2 Stationarity: Differencing

1 Quiz

  • Lesson 3-1 Practice Quiz

Lesson 3-2: ARIMA

    • 7 Videos
    • 1 Quiz
Show info about module content

7 Videos

  • Lesson 3-2.1 ARIMA: Introduction
  • Lesson 3-2.2 ARIMA: Components
  • Lesson 3-2.3 ARIMA: Model and R Example Part 1
  • Lesson 3-2.4 ARIMA: Model and R Example Part 2
  • Lesson 3-2.5 ARIMA: Model and R Example Part 3
  • Lesson 3-2.6 ARIMA: Model and R Example Part 4
  • Lesson 3-2.7 ARIMA: Model and R Example Part 5

1 Quiz

  • Lesson 3-2 Practice Quiz

Module 3 Graded Activities

    • 2 Quiz
    • 1 Lab
Show info about module content

1 Labs

  • ARIMA Models Lab

2 Quiz

  • Module 3 Quiz
  • Module 3 Lab Exercise Quiz

Module 4 Information

    • 2 Videos
    • 2 Readings
Show info about module content

2 Videos

  • Module 4 Overview ***
  • Jose Rodriguez: Portfolios in Practice

2 Readings

  • Module 4 Overview
  • Module 4 Readings

Lesson 4-1: Modern Portfolio Theory

    • 7 Videos
    • 1 Quiz
Show info about module content

7 Videos

  • Lesson 4-1.1 Portfolio Theory: Introduction
  • Lesson 4-1.2 Portfolio Theory: Expected Returns
  • Lesson 4-1.3 Portfolio Theory: Risk of a Security
  • Lesson 4-1.4 Portfolio Theory: Efficient Frontier
  • Lesson 4-1.5 Portfolio Theory: Portfolio Weights
  • Lesson 4-1.6 Portfolio Theory: Capital Allocation Line
  • Lesson 4-1.7 Portfolio Theory: Diversification

1 Quiz

  • Lesson 4-1 Practice Quiz

Lesson 4-2: Introduction to Algorithmic Trading

    • 5 Videos
    • 1 Quiz
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5 Videos

  • Lesson 4-2.1 Introduction to Algorithmic Trading
  • Lesson 4-2.2 Introduction to Algorithmic Trading: Trend Following Strategy
  • Lesson 4-2.3 Introduction to Algorithmic Trading: Backtesting
  • Lesson 4-2.4 Introduction to Algorithmic Trading: R Example
  • Lesson 4-2.5 Introduction to Algorithmic Trading: Conclusion

1 Quiz

  • Lesson 4-2 Practice Quiz

Module 4 Graded Activities

    • 2 Quiz
    • 1 Lab
Show info about module content

1 Labs

  • Modern Portfolio Theory & Algorithmic Trading Lab

2 Quiz

  • Module 4 Quiz
  • Module 4 Lab Exercise Quiz

Course Summary

    • 1 Videos
    • 2 Readings
    • 1 Plugin
Show info about module content

1 Videos

  • Course Summary: Applying Data Analytics in Finance

2 Readings

  • Congratulations on completing the course!
  • Get Your Course Certificate

Auto Summary

"Applying Data Analytics in Finance" is a professional-level course offered by Coursera, focusing on financial analytics within the Business & Management domain. Led by expert instructors, it covers time series data analysis, risk-reward evaluation, and modern portfolio theory. The course also includes an introduction to algorithmic trading. Over 1440 minutes, learners will gain skills in forecasting, portfolio creation, and optimizing risk and reward, making it ideal for analysts, managers, and consultants. Subscription options include a starter plan.

Sung Won Kim
Instructors

Sung Won Kim

Jose Luis Rodriguez
Instructors

Jose Luis Rodriguez