Course Summary
This course teaches students how to apply data analytics in the finance industry. Students will learn how to use data analysis to make informed business decisions and gain a competitive edge.Key Learning Points
- Learn how to use data analysis to make informed business decisions
- Gain a competitive edge in the finance industry
- Apply data analytics to real-world financial problems
Related Topics for further study
Learning Outcomes
- Understand the role of data analytics in the finance industry
- Apply data analysis to real-world financial problems
- Make informed business decisions using data analysis
Prerequisites or good to have knowledge before taking this course
- Basic understanding of finance
- Basic understanding of data analytics
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Data Analytics for Business
- Data Science in Finance
- Financial Markets and Investment Strategy
Related Education Paths
- Financial Modeling and Valuation Analyst (FMVA)® Certification
- Certified Financial Planner (CFP) Certification
- Chartered Financial Analyst (CFA) Certification
Related Books
Description
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.
Knowledge
- Understand the forecasting process
- Describe time series data
- Develop an ARIMA Model
- Understand a basic trading algorithm
Outline
- Course Introduction
- Coursera Course Introduction ***
- Instructor Bio: Jose Rodriguez ***
- Interview with Jose Rodriguez
- Learn on Your Terms
- Syllabus
- Glossary
- Resources for R
- About the Discussion Forums
- Learn More About Flexible Learning Paths
- Orientation Quiz
- Module 1: Introduction to Financial Analytics and Time Series Data
- Module 1 Overview ***
- Jose Rodriguez: Forecasting in Practice
- Lesson 1-1.1 Subjective Forecasting
- Lesson 1-1.2 Business Forecasting and Time Series Data
- Lesson 1-2.1 Introduction to Financial Analytics
- Lesson 1-3.1 Forecasting Performance Measurements: Distance
- Lesson 1-3.2 Forecasting Performance Measurements: Metrics
- Module 1 Overview
- Module 1 Readings
- Lesson 1-1 Practice Quiz
- Lesson 1-2 Practice Quiz
- Lesson 1-3 Practice Quiz
- Module 1 Quiz
- Module 1 Lab Exercise Quiz
- Module 2: Performance Measures and Holt-Winters Model
- Module 2 Overview ***
- Jose Rodriguez: Forecasting Models in Practice
- 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
- Lesson 2-2.1 Moving Averages
- Lesson 2-3.1 Introduction to Exponential Smoothing
- Lesson 2-3.2 Simple Exponential Smoothing
- Lesson 2-3.3 Simple Exponential Smoothing: R Example
- 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
- Lesson 2-5.1 Autoregression
- Lesson 2-5.2 Autoregression: R Example
- Module 2 Overview
- Module 2 Readings
- Lesson 2-1 Practice Quiz
- Lesson 2-2 Practice Quiz
- Lesson 2-3 Practice Quiz
- Lesson 2-4 Practice Quiz
- Lesson 2-5 Practice Quiz
- Module 2 Quiz
- Module 2 Lab Exercise Quiz
- Module 3: Stationarity and ARIMA Model
- Module 3 Overview ***
- Jose Rodriguez: ARIMA in Practice
- Lesson 3-1.1 Stationarity: Introduction
- Lesson 3-1.2 Stationarity: Differencing
- 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
- Module 3 Overview
- Module 3 Readings
- Lesson 3-1 Practice Quiz
- Lesson 3-2 Practice Quiz
- Module 3 Quiz
- Module 3 Lab Exercise Quiz
- Module 4: Modern Portfolio Theory and Intro to Algorithmic Trading
- Module 4 Overview ***
- Jose Rodriguez: Portfolios in Practice
- 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
- 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
- Course Summary: Applying Data Analytics in Finance
- Gies Online Programs
- Module 4 Overview
- Module 4 Readings
- Congratulations!
- Get Your Course Certificate
- Lesson 4-1 Practice Quiz
- Lesson 4-2 Practice Quiz
- Module 4 Quiz
- Module 4 Lab Exercise Quiz
Summary of User Reviews
Discover how to use data analytics to drive better business decisions in the finance industry. This course has received great reviews from users who have found it to be insightful and practical for their work in finance.Key Aspect Users Liked About This Course
Many users have praised the course for its practical approach to data analytics in finance, with real-world examples and case studies that help them apply the concepts to their own work.Pros from User Reviews
- Insightful and practical course content
- Real-world examples and case studies
- Great for professionals in the finance industry
- Helpful instructor feedback
- Flexible schedule and pacing
Cons from User Reviews
- Some users found the course too basic for their level of knowledge
- Limited interaction with other learners
- Some technical issues with the platform
- Not enough focus on specific financial topics
- Course material could be more in-depth
Sung Won Kim
4.5 Raiting
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